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https://github.com/comfyanonymous/ComfyUI.git
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node-essen
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| Author | SHA1 | Date | |
|---|---|---|---|
| 0358446ef0 | |||
| f7817d0303 | |||
| 6137685768 | |||
| d39d98f878 | |||
| 2e5c147fb5 | |||
| ae20354b69 |
114
.coderabbit.yaml
114
.coderabbit.yaml
@ -1,114 +0,0 @@
|
||||
# yaml-language-server: $schema=https://coderabbit.ai/integrations/schema.v2.json
|
||||
language: "en-US"
|
||||
early_access: false
|
||||
|
||||
reviews:
|
||||
profile: "chill"
|
||||
request_changes_workflow: false
|
||||
high_level_summary: false
|
||||
poem: false
|
||||
review_status: false
|
||||
review_details: false
|
||||
commit_status: true
|
||||
collapse_walkthrough: true
|
||||
changed_files_summary: false
|
||||
sequence_diagrams: false
|
||||
estimate_code_review_effort: false
|
||||
assess_linked_issues: false
|
||||
related_issues: false
|
||||
related_prs: false
|
||||
suggested_labels: false
|
||||
auto_apply_labels: false
|
||||
suggested_reviewers: false
|
||||
auto_assign_reviewers: false
|
||||
in_progress_fortune: false
|
||||
enable_prompt_for_ai_agents: true
|
||||
|
||||
path_filters:
|
||||
- "!comfy_api_nodes/apis/**"
|
||||
- "!**/generated/*.pyi"
|
||||
- "!.ci/**"
|
||||
- "!script_examples/**"
|
||||
- "!**/__pycache__/**"
|
||||
- "!**/*.ipynb"
|
||||
- "!**/*.png"
|
||||
- "!**/*.bat"
|
||||
|
||||
path_instructions:
|
||||
- path: "comfy/**"
|
||||
instructions: |
|
||||
Core ML/diffusion engine. Focus on:
|
||||
- Backward compatibility (breaking changes affect all custom nodes)
|
||||
- Memory management and GPU resource handling
|
||||
- Performance implications in hot paths
|
||||
- Thread safety for concurrent execution
|
||||
- path: "comfy_api_nodes/**"
|
||||
instructions: |
|
||||
Third-party API integration nodes. Focus on:
|
||||
- No hardcoded API keys or secrets
|
||||
- Proper error handling for API failures (timeouts, rate limits, auth errors)
|
||||
- Correct Pydantic model usage
|
||||
- Security of user data passed to external APIs
|
||||
- path: "comfy_extras/**"
|
||||
instructions: |
|
||||
Community-contributed extra nodes. Focus on:
|
||||
- Consistency with node patterns (INPUT_TYPES, RETURN_TYPES, FUNCTION, CATEGORY)
|
||||
- No breaking changes to existing node interfaces
|
||||
- path: "comfy_execution/**"
|
||||
instructions: |
|
||||
Execution engine (graph execution, caching, jobs). Focus on:
|
||||
- Caching correctness
|
||||
- Concurrent execution safety
|
||||
- Graph validation edge cases
|
||||
- path: "nodes.py"
|
||||
instructions: |
|
||||
Core node definitions (2500+ lines). Focus on:
|
||||
- Backward compatibility of NODE_CLASS_MAPPINGS
|
||||
- Consistency of INPUT_TYPES return format
|
||||
- path: "alembic_db/**"
|
||||
instructions: |
|
||||
Database migrations. Focus on:
|
||||
- Migration safety and rollback support
|
||||
- Data preservation during schema changes
|
||||
|
||||
auto_review:
|
||||
enabled: true
|
||||
auto_incremental_review: true
|
||||
drafts: true
|
||||
|
||||
finishing_touches:
|
||||
docstrings:
|
||||
enabled: false
|
||||
unit_tests:
|
||||
enabled: false
|
||||
|
||||
tools:
|
||||
ruff:
|
||||
enabled: true
|
||||
pylint:
|
||||
enabled: false
|
||||
flake8:
|
||||
enabled: false
|
||||
gitleaks:
|
||||
enabled: true
|
||||
shellcheck:
|
||||
enabled: false
|
||||
markdownlint:
|
||||
enabled: false
|
||||
yamllint:
|
||||
enabled: false
|
||||
languagetool:
|
||||
enabled: false
|
||||
github-checks:
|
||||
enabled: true
|
||||
timeout_ms: 90000
|
||||
ast-grep:
|
||||
essential_rules: true
|
||||
|
||||
chat:
|
||||
auto_reply: true
|
||||
|
||||
knowledge_base:
|
||||
opt_out: false
|
||||
learnings:
|
||||
scope: "auto"
|
||||
@ -229,9 +229,9 @@ AMD users can install rocm and pytorch with pip if you don't have it already ins
|
||||
|
||||
```pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm7.1```
|
||||
|
||||
This is the command to install the nightly with ROCm 7.2 which might have some performance improvements:
|
||||
This is the command to install the nightly with ROCm 7.1 which might have some performance improvements:
|
||||
|
||||
```pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/rocm7.2```
|
||||
```pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/rocm7.1```
|
||||
|
||||
|
||||
### AMD GPUs (Experimental: Windows and Linux), RDNA 3, 3.5 and 4 only.
|
||||
|
||||
@ -1,44 +0,0 @@
|
||||
#version 300 es
|
||||
precision highp float;
|
||||
|
||||
uniform sampler2D u_image0;
|
||||
uniform float u_float0; // Brightness slider -100..100
|
||||
uniform float u_float1; // Contrast slider -100..100
|
||||
|
||||
in vec2 v_texCoord;
|
||||
out vec4 fragColor;
|
||||
|
||||
const float MID_GRAY = 0.18; // 18% reflectance
|
||||
|
||||
// sRGB gamma 2.2 approximation
|
||||
vec3 srgbToLinear(vec3 c) {
|
||||
return pow(max(c, 0.0), vec3(2.2));
|
||||
}
|
||||
|
||||
vec3 linearToSrgb(vec3 c) {
|
||||
return pow(max(c, 0.0), vec3(1.0/2.2));
|
||||
}
|
||||
|
||||
float mapBrightness(float b) {
|
||||
return clamp(b / 100.0, -1.0, 1.0);
|
||||
}
|
||||
|
||||
float mapContrast(float c) {
|
||||
return clamp(c / 100.0 + 1.0, 0.0, 2.0);
|
||||
}
|
||||
|
||||
void main() {
|
||||
vec4 orig = texture(u_image0, v_texCoord);
|
||||
|
||||
float brightness = mapBrightness(u_float0);
|
||||
float contrast = mapContrast(u_float1);
|
||||
|
||||
vec3 lin = srgbToLinear(orig.rgb);
|
||||
|
||||
lin = (lin - MID_GRAY) * contrast + brightness + MID_GRAY;
|
||||
|
||||
// Convert back to sRGB
|
||||
vec3 result = linearToSrgb(clamp(lin, 0.0, 1.0));
|
||||
|
||||
fragColor = vec4(result, orig.a);
|
||||
}
|
||||
@ -1,72 +0,0 @@
|
||||
#version 300 es
|
||||
precision highp float;
|
||||
|
||||
uniform sampler2D u_image0;
|
||||
uniform vec2 u_resolution;
|
||||
uniform int u_int0; // Mode
|
||||
uniform float u_float0; // Amount (0 to 100)
|
||||
|
||||
in vec2 v_texCoord;
|
||||
out vec4 fragColor;
|
||||
|
||||
const int MODE_LINEAR = 0;
|
||||
const int MODE_RADIAL = 1;
|
||||
const int MODE_BARREL = 2;
|
||||
const int MODE_SWIRL = 3;
|
||||
const int MODE_DIAGONAL = 4;
|
||||
|
||||
const float AMOUNT_SCALE = 0.0005;
|
||||
const float RADIAL_MULT = 4.0;
|
||||
const float BARREL_MULT = 8.0;
|
||||
const float INV_SQRT2 = 0.70710678118;
|
||||
|
||||
void main() {
|
||||
vec2 uv = v_texCoord;
|
||||
vec4 original = texture(u_image0, uv);
|
||||
|
||||
float amount = u_float0 * AMOUNT_SCALE;
|
||||
|
||||
if (amount < 0.000001) {
|
||||
fragColor = original;
|
||||
return;
|
||||
}
|
||||
|
||||
// Aspect-corrected coordinates for circular effects
|
||||
float aspect = u_resolution.x / u_resolution.y;
|
||||
vec2 centered = uv - 0.5;
|
||||
vec2 corrected = vec2(centered.x * aspect, centered.y);
|
||||
float r = length(corrected);
|
||||
vec2 dir = r > 0.0001 ? corrected / r : vec2(0.0);
|
||||
vec2 offset = vec2(0.0);
|
||||
|
||||
if (u_int0 == MODE_LINEAR) {
|
||||
// Horizontal shift (no aspect correction needed)
|
||||
offset = vec2(amount, 0.0);
|
||||
}
|
||||
else if (u_int0 == MODE_RADIAL) {
|
||||
// Outward from center, stronger at edges
|
||||
offset = dir * r * amount * RADIAL_MULT;
|
||||
offset.x /= aspect; // Convert back to UV space
|
||||
}
|
||||
else if (u_int0 == MODE_BARREL) {
|
||||
// Lens distortion simulation (r² falloff)
|
||||
offset = dir * r * r * amount * BARREL_MULT;
|
||||
offset.x /= aspect; // Convert back to UV space
|
||||
}
|
||||
else if (u_int0 == MODE_SWIRL) {
|
||||
// Perpendicular to radial (rotational aberration)
|
||||
vec2 perp = vec2(-dir.y, dir.x);
|
||||
offset = perp * r * amount * RADIAL_MULT;
|
||||
offset.x /= aspect; // Convert back to UV space
|
||||
}
|
||||
else if (u_int0 == MODE_DIAGONAL) {
|
||||
// 45° offset (no aspect correction needed)
|
||||
offset = vec2(amount, amount) * INV_SQRT2;
|
||||
}
|
||||
|
||||
float red = texture(u_image0, uv + offset).r;
|
||||
float green = original.g;
|
||||
float blue = texture(u_image0, uv - offset).b;
|
||||
|
||||
fragColor = vec4(red, green, blue, original.a);
|
||||
}
|
||||
@ -1,78 +0,0 @@
|
||||
#version 300 es
|
||||
precision highp float;
|
||||
|
||||
uniform sampler2D u_image0;
|
||||
uniform float u_float0; // temperature (-100 to 100)
|
||||
uniform float u_float1; // tint (-100 to 100)
|
||||
uniform float u_float2; // vibrance (-100 to 100)
|
||||
uniform float u_float3; // saturation (-100 to 100)
|
||||
|
||||
in vec2 v_texCoord;
|
||||
out vec4 fragColor;
|
||||
|
||||
const float INPUT_SCALE = 0.01;
|
||||
const float TEMP_TINT_PRIMARY = 0.3;
|
||||
const float TEMP_TINT_SECONDARY = 0.15;
|
||||
const float VIBRANCE_BOOST = 2.0;
|
||||
const float SATURATION_BOOST = 2.0;
|
||||
const float SKIN_PROTECTION = 0.5;
|
||||
const float EPSILON = 0.001;
|
||||
const vec3 LUMA_WEIGHTS = vec3(0.299, 0.587, 0.114);
|
||||
|
||||
void main() {
|
||||
vec4 tex = texture(u_image0, v_texCoord);
|
||||
vec3 color = tex.rgb;
|
||||
|
||||
// Scale inputs: -100/100 → -1/1
|
||||
float temperature = u_float0 * INPUT_SCALE;
|
||||
float tint = u_float1 * INPUT_SCALE;
|
||||
float vibrance = u_float2 * INPUT_SCALE;
|
||||
float saturation = u_float3 * INPUT_SCALE;
|
||||
|
||||
// Temperature (warm/cool): positive = warm, negative = cool
|
||||
color.r += temperature * TEMP_TINT_PRIMARY;
|
||||
color.b -= temperature * TEMP_TINT_PRIMARY;
|
||||
|
||||
// Tint (green/magenta): positive = green, negative = magenta
|
||||
color.g += tint * TEMP_TINT_PRIMARY;
|
||||
color.r -= tint * TEMP_TINT_SECONDARY;
|
||||
color.b -= tint * TEMP_TINT_SECONDARY;
|
||||
|
||||
// Single clamp after temperature/tint
|
||||
color = clamp(color, 0.0, 1.0);
|
||||
|
||||
// Vibrance with skin protection
|
||||
if (vibrance != 0.0) {
|
||||
float maxC = max(color.r, max(color.g, color.b));
|
||||
float minC = min(color.r, min(color.g, color.b));
|
||||
float sat = maxC - minC;
|
||||
float gray = dot(color, LUMA_WEIGHTS);
|
||||
|
||||
if (vibrance < 0.0) {
|
||||
// Desaturate: -100 → gray
|
||||
color = mix(vec3(gray), color, 1.0 + vibrance);
|
||||
} else {
|
||||
// Boost less saturated colors more
|
||||
float vibranceAmt = vibrance * (1.0 - sat);
|
||||
|
||||
// Branchless skin tone protection
|
||||
float isWarmTone = step(color.b, color.g) * step(color.g, color.r);
|
||||
float warmth = (color.r - color.b) / max(maxC, EPSILON);
|
||||
float skinTone = isWarmTone * warmth * sat * (1.0 - sat);
|
||||
vibranceAmt *= (1.0 - skinTone * SKIN_PROTECTION);
|
||||
|
||||
color = mix(vec3(gray), color, 1.0 + vibranceAmt * VIBRANCE_BOOST);
|
||||
}
|
||||
}
|
||||
|
||||
// Saturation
|
||||
if (saturation != 0.0) {
|
||||
float gray = dot(color, LUMA_WEIGHTS);
|
||||
float satMix = saturation < 0.0
|
||||
? 1.0 + saturation // -100 → gray
|
||||
: 1.0 + saturation * SATURATION_BOOST; // +100 → 3x boost
|
||||
color = mix(vec3(gray), color, satMix);
|
||||
}
|
||||
|
||||
fragColor = vec4(clamp(color, 0.0, 1.0), tex.a);
|
||||
}
|
||||
@ -1,94 +0,0 @@
|
||||
#version 300 es
|
||||
precision highp float;
|
||||
|
||||
uniform sampler2D u_image0;
|
||||
uniform float u_float0; // Blur radius (0–20, default ~5)
|
||||
uniform float u_float1; // Edge threshold (0–100, default ~30)
|
||||
uniform int u_int0; // Step size (0/1 = every pixel, 2+ = skip pixels)
|
||||
|
||||
in vec2 v_texCoord;
|
||||
out vec4 fragColor;
|
||||
|
||||
const int MAX_RADIUS = 20;
|
||||
const float EPSILON = 0.0001;
|
||||
|
||||
// Perceptual luminance
|
||||
float getLuminance(vec3 rgb) {
|
||||
return dot(rgb, vec3(0.299, 0.587, 0.114));
|
||||
}
|
||||
|
||||
vec4 bilateralFilter(vec2 uv, vec2 texelSize, int radius,
|
||||
float sigmaSpatial, float sigmaColor)
|
||||
{
|
||||
vec4 center = texture(u_image0, uv);
|
||||
vec3 centerRGB = center.rgb;
|
||||
|
||||
float invSpatial2 = -0.5 / (sigmaSpatial * sigmaSpatial);
|
||||
float invColor2 = -0.5 / (sigmaColor * sigmaColor + EPSILON);
|
||||
|
||||
vec3 sumRGB = vec3(0.0);
|
||||
float sumWeight = 0.0;
|
||||
|
||||
int step = max(u_int0, 1);
|
||||
float radius2 = float(radius * radius);
|
||||
|
||||
for (int dy = -MAX_RADIUS; dy <= MAX_RADIUS; dy++) {
|
||||
if (dy < -radius || dy > radius) continue;
|
||||
if (abs(dy) % step != 0) continue;
|
||||
|
||||
for (int dx = -MAX_RADIUS; dx <= MAX_RADIUS; dx++) {
|
||||
if (dx < -radius || dx > radius) continue;
|
||||
if (abs(dx) % step != 0) continue;
|
||||
|
||||
vec2 offset = vec2(float(dx), float(dy));
|
||||
float dist2 = dot(offset, offset);
|
||||
if (dist2 > radius2) continue;
|
||||
|
||||
vec3 sampleRGB = texture(u_image0, uv + offset * texelSize).rgb;
|
||||
|
||||
// Spatial Gaussian
|
||||
float spatialWeight = exp(dist2 * invSpatial2);
|
||||
|
||||
// Perceptual color distance (weighted RGB)
|
||||
vec3 diff = sampleRGB - centerRGB;
|
||||
float colorDist = dot(diff * diff, vec3(0.299, 0.587, 0.114));
|
||||
float colorWeight = exp(colorDist * invColor2);
|
||||
|
||||
float w = spatialWeight * colorWeight;
|
||||
sumRGB += sampleRGB * w;
|
||||
sumWeight += w;
|
||||
}
|
||||
}
|
||||
|
||||
vec3 resultRGB = sumRGB / max(sumWeight, EPSILON);
|
||||
return vec4(resultRGB, center.a); // preserve center alpha
|
||||
}
|
||||
|
||||
void main() {
|
||||
vec2 texelSize = 1.0 / vec2(textureSize(u_image0, 0));
|
||||
|
||||
float radiusF = clamp(u_float0, 0.0, float(MAX_RADIUS));
|
||||
int radius = int(radiusF + 0.5);
|
||||
|
||||
if (radius == 0) {
|
||||
fragColor = texture(u_image0, v_texCoord);
|
||||
return;
|
||||
}
|
||||
|
||||
// Edge threshold → color sigma
|
||||
// Squared curve for better low-end control
|
||||
float t = clamp(u_float1, 0.0, 100.0) / 100.0;
|
||||
t *= t;
|
||||
float sigmaColor = mix(0.01, 0.5, t);
|
||||
|
||||
// Spatial sigma tied to radius
|
||||
float sigmaSpatial = max(radiusF * 0.75, 0.5);
|
||||
|
||||
fragColor = bilateralFilter(
|
||||
v_texCoord,
|
||||
texelSize,
|
||||
radius,
|
||||
sigmaSpatial,
|
||||
sigmaColor
|
||||
);
|
||||
}
|
||||
@ -1,124 +0,0 @@
|
||||
#version 300 es
|
||||
precision highp float;
|
||||
|
||||
uniform sampler2D u_image0;
|
||||
uniform vec2 u_resolution;
|
||||
uniform float u_float0; // grain amount [0.0 – 1.0] typical: 0.2–0.8
|
||||
uniform float u_float1; // grain size [0.3 – 3.0] lower = finer grain
|
||||
uniform float u_float2; // color amount [0.0 – 1.0] 0 = monochrome, 1 = RGB grain
|
||||
uniform float u_float3; // luminance bias [0.0 – 1.0] 0 = uniform, 1 = shadows only
|
||||
uniform int u_int0; // noise mode [0 or 1] 0 = smooth, 1 = grainy
|
||||
|
||||
in vec2 v_texCoord;
|
||||
layout(location = 0) out vec4 fragColor0;
|
||||
|
||||
// High-quality integer hash (pcg-like)
|
||||
uint pcg(uint v) {
|
||||
uint state = v * 747796405u + 2891336453u;
|
||||
uint word = ((state >> ((state >> 28u) + 4u)) ^ state) * 277803737u;
|
||||
return (word >> 22u) ^ word;
|
||||
}
|
||||
|
||||
// 2D -> 1D hash input
|
||||
uint hash2d(uvec2 p) {
|
||||
return pcg(p.x + pcg(p.y));
|
||||
}
|
||||
|
||||
// Hash to float [0, 1]
|
||||
float hashf(uvec2 p) {
|
||||
return float(hash2d(p)) / float(0xffffffffu);
|
||||
}
|
||||
|
||||
// Hash to float with offset (for RGB channels)
|
||||
float hashf(uvec2 p, uint offset) {
|
||||
return float(pcg(hash2d(p) + offset)) / float(0xffffffffu);
|
||||
}
|
||||
|
||||
// Convert uniform [0,1] to roughly Gaussian distribution
|
||||
// Using simple approximation: average of multiple samples
|
||||
float toGaussian(uvec2 p) {
|
||||
float sum = hashf(p, 0u) + hashf(p, 1u) + hashf(p, 2u) + hashf(p, 3u);
|
||||
return (sum - 2.0) * 0.7; // Centered, scaled
|
||||
}
|
||||
|
||||
float toGaussian(uvec2 p, uint offset) {
|
||||
float sum = hashf(p, offset) + hashf(p, offset + 1u)
|
||||
+ hashf(p, offset + 2u) + hashf(p, offset + 3u);
|
||||
return (sum - 2.0) * 0.7;
|
||||
}
|
||||
|
||||
// Smooth noise with better interpolation
|
||||
float smoothNoise(vec2 p) {
|
||||
vec2 i = floor(p);
|
||||
vec2 f = fract(p);
|
||||
|
||||
// Quintic interpolation (less banding than cubic)
|
||||
f = f * f * f * (f * (f * 6.0 - 15.0) + 10.0);
|
||||
|
||||
uvec2 ui = uvec2(i);
|
||||
float a = toGaussian(ui);
|
||||
float b = toGaussian(ui + uvec2(1u, 0u));
|
||||
float c = toGaussian(ui + uvec2(0u, 1u));
|
||||
float d = toGaussian(ui + uvec2(1u, 1u));
|
||||
|
||||
return mix(mix(a, b, f.x), mix(c, d, f.x), f.y);
|
||||
}
|
||||
|
||||
float smoothNoise(vec2 p, uint offset) {
|
||||
vec2 i = floor(p);
|
||||
vec2 f = fract(p);
|
||||
|
||||
f = f * f * f * (f * (f * 6.0 - 15.0) + 10.0);
|
||||
|
||||
uvec2 ui = uvec2(i);
|
||||
float a = toGaussian(ui, offset);
|
||||
float b = toGaussian(ui + uvec2(1u, 0u), offset);
|
||||
float c = toGaussian(ui + uvec2(0u, 1u), offset);
|
||||
float d = toGaussian(ui + uvec2(1u, 1u), offset);
|
||||
|
||||
return mix(mix(a, b, f.x), mix(c, d, f.x), f.y);
|
||||
}
|
||||
|
||||
void main() {
|
||||
vec4 color = texture(u_image0, v_texCoord);
|
||||
|
||||
// Luminance (Rec.709)
|
||||
float luma = dot(color.rgb, vec3(0.2126, 0.7152, 0.0722));
|
||||
|
||||
// Grain UV (resolution-independent)
|
||||
vec2 grainUV = v_texCoord * u_resolution / max(u_float1, 0.01);
|
||||
uvec2 grainPixel = uvec2(grainUV);
|
||||
|
||||
float g;
|
||||
vec3 grainRGB;
|
||||
|
||||
if (u_int0 == 1) {
|
||||
// Grainy mode: pure hash noise (no interpolation = no banding)
|
||||
g = toGaussian(grainPixel);
|
||||
grainRGB = vec3(
|
||||
toGaussian(grainPixel, 100u),
|
||||
toGaussian(grainPixel, 200u),
|
||||
toGaussian(grainPixel, 300u)
|
||||
);
|
||||
} else {
|
||||
// Smooth mode: interpolated with quintic curve
|
||||
g = smoothNoise(grainUV);
|
||||
grainRGB = vec3(
|
||||
smoothNoise(grainUV, 100u),
|
||||
smoothNoise(grainUV, 200u),
|
||||
smoothNoise(grainUV, 300u)
|
||||
);
|
||||
}
|
||||
|
||||
// Luminance weighting (less grain in highlights)
|
||||
float lumWeight = mix(1.0, 1.0 - luma, clamp(u_float3, 0.0, 1.0));
|
||||
|
||||
// Strength
|
||||
float strength = u_float0 * 0.15;
|
||||
|
||||
// Color vs monochrome grain
|
||||
vec3 grainColor = mix(vec3(g), grainRGB, clamp(u_float2, 0.0, 1.0));
|
||||
|
||||
color.rgb += grainColor * strength * lumWeight;
|
||||
fragColor0 = vec4(clamp(color.rgb, 0.0, 1.0), color.a);
|
||||
}
|
||||
@ -1,133 +0,0 @@
|
||||
#version 300 es
|
||||
precision mediump float;
|
||||
|
||||
uniform sampler2D u_image0;
|
||||
uniform vec2 u_resolution;
|
||||
uniform int u_int0; // Blend mode
|
||||
uniform int u_int1; // Color tint
|
||||
uniform float u_float0; // Intensity
|
||||
uniform float u_float1; // Radius
|
||||
uniform float u_float2; // Threshold
|
||||
|
||||
in vec2 v_texCoord;
|
||||
out vec4 fragColor;
|
||||
|
||||
const int BLEND_ADD = 0;
|
||||
const int BLEND_SCREEN = 1;
|
||||
const int BLEND_SOFT = 2;
|
||||
const int BLEND_OVERLAY = 3;
|
||||
const int BLEND_LIGHTEN = 4;
|
||||
|
||||
const float GOLDEN_ANGLE = 2.39996323;
|
||||
const int MAX_SAMPLES = 48;
|
||||
const vec3 LUMA = vec3(0.299, 0.587, 0.114);
|
||||
|
||||
float hash(vec2 p) {
|
||||
p = fract(p * vec2(123.34, 456.21));
|
||||
p += dot(p, p + 45.32);
|
||||
return fract(p.x * p.y);
|
||||
}
|
||||
|
||||
vec3 hexToRgb(int h) {
|
||||
return vec3(
|
||||
float((h >> 16) & 255),
|
||||
float((h >> 8) & 255),
|
||||
float(h & 255)
|
||||
) * (1.0 / 255.0);
|
||||
}
|
||||
|
||||
vec3 blend(vec3 base, vec3 glow, int mode) {
|
||||
if (mode == BLEND_SCREEN) {
|
||||
return 1.0 - (1.0 - base) * (1.0 - glow);
|
||||
}
|
||||
if (mode == BLEND_SOFT) {
|
||||
return mix(
|
||||
base - (1.0 - 2.0 * glow) * base * (1.0 - base),
|
||||
base + (2.0 * glow - 1.0) * (sqrt(base) - base),
|
||||
step(0.5, glow)
|
||||
);
|
||||
}
|
||||
if (mode == BLEND_OVERLAY) {
|
||||
return mix(
|
||||
2.0 * base * glow,
|
||||
1.0 - 2.0 * (1.0 - base) * (1.0 - glow),
|
||||
step(0.5, base)
|
||||
);
|
||||
}
|
||||
if (mode == BLEND_LIGHTEN) {
|
||||
return max(base, glow);
|
||||
}
|
||||
return base + glow;
|
||||
}
|
||||
|
||||
void main() {
|
||||
vec4 original = texture(u_image0, v_texCoord);
|
||||
|
||||
float intensity = u_float0 * 0.05;
|
||||
float radius = u_float1 * u_float1 * 0.012;
|
||||
|
||||
if (intensity < 0.001 || radius < 0.1) {
|
||||
fragColor = original;
|
||||
return;
|
||||
}
|
||||
|
||||
float threshold = 1.0 - u_float2 * 0.01;
|
||||
float t0 = threshold - 0.15;
|
||||
float t1 = threshold + 0.15;
|
||||
|
||||
vec2 texelSize = 1.0 / u_resolution;
|
||||
float radius2 = radius * radius;
|
||||
|
||||
float sampleScale = clamp(radius * 0.75, 0.35, 1.0);
|
||||
int samples = int(float(MAX_SAMPLES) * sampleScale);
|
||||
|
||||
float noise = hash(gl_FragCoord.xy);
|
||||
float angleOffset = noise * GOLDEN_ANGLE;
|
||||
float radiusJitter = 0.85 + noise * 0.3;
|
||||
|
||||
float ca = cos(GOLDEN_ANGLE);
|
||||
float sa = sin(GOLDEN_ANGLE);
|
||||
vec2 dir = vec2(cos(angleOffset), sin(angleOffset));
|
||||
|
||||
vec3 glow = vec3(0.0);
|
||||
float totalWeight = 0.0;
|
||||
|
||||
// Center tap
|
||||
float centerMask = smoothstep(t0, t1, dot(original.rgb, LUMA));
|
||||
glow += original.rgb * centerMask * 2.0;
|
||||
totalWeight += 2.0;
|
||||
|
||||
for (int i = 1; i < MAX_SAMPLES; i++) {
|
||||
if (i >= samples) break;
|
||||
|
||||
float fi = float(i);
|
||||
float dist = sqrt(fi / float(samples)) * radius * radiusJitter;
|
||||
|
||||
vec2 offset = dir * dist * texelSize;
|
||||
vec3 c = texture(u_image0, v_texCoord + offset).rgb;
|
||||
float mask = smoothstep(t0, t1, dot(c, LUMA));
|
||||
|
||||
float w = 1.0 - (dist * dist) / (radius2 * 1.5);
|
||||
w = max(w, 0.0);
|
||||
w *= w;
|
||||
|
||||
glow += c * mask * w;
|
||||
totalWeight += w;
|
||||
|
||||
dir = vec2(
|
||||
dir.x * ca - dir.y * sa,
|
||||
dir.x * sa + dir.y * ca
|
||||
);
|
||||
}
|
||||
|
||||
glow *= intensity / max(totalWeight, 0.001);
|
||||
|
||||
if (u_int1 > 0) {
|
||||
glow *= hexToRgb(u_int1);
|
||||
}
|
||||
|
||||
vec3 result = blend(original.rgb, glow, u_int0);
|
||||
result += (noise - 0.5) * (1.0 / 255.0);
|
||||
|
||||
fragColor = vec4(clamp(result, 0.0, 1.0), original.a);
|
||||
}
|
||||
@ -1,222 +0,0 @@
|
||||
#version 300 es
|
||||
precision highp float;
|
||||
|
||||
uniform sampler2D u_image0;
|
||||
uniform int u_int0; // Mode: 0=Master, 1=Reds, 2=Yellows, 3=Greens, 4=Cyans, 5=Blues, 6=Magentas, 7=Colorize
|
||||
uniform int u_int1; // Color Space: 0=HSL, 1=HSB/HSV
|
||||
uniform float u_float0; // Hue (-180 to 180)
|
||||
uniform float u_float1; // Saturation (-100 to 100)
|
||||
uniform float u_float2; // Lightness/Brightness (-100 to 100)
|
||||
uniform float u_float3; // Overlap (0 to 100) - feathering between adjacent color ranges
|
||||
|
||||
in vec2 v_texCoord;
|
||||
out vec4 fragColor;
|
||||
|
||||
// Color range modes
|
||||
const int MODE_MASTER = 0;
|
||||
const int MODE_RED = 1;
|
||||
const int MODE_YELLOW = 2;
|
||||
const int MODE_GREEN = 3;
|
||||
const int MODE_CYAN = 4;
|
||||
const int MODE_BLUE = 5;
|
||||
const int MODE_MAGENTA = 6;
|
||||
const int MODE_COLORIZE = 7;
|
||||
|
||||
// Color space modes
|
||||
const int COLORSPACE_HSL = 0;
|
||||
const int COLORSPACE_HSB = 1;
|
||||
|
||||
const float EPSILON = 0.0001;
|
||||
|
||||
//=============================================================================
|
||||
// RGB <-> HSL Conversions
|
||||
//=============================================================================
|
||||
|
||||
vec3 rgb2hsl(vec3 c) {
|
||||
float maxC = max(max(c.r, c.g), c.b);
|
||||
float minC = min(min(c.r, c.g), c.b);
|
||||
float delta = maxC - minC;
|
||||
|
||||
float h = 0.0;
|
||||
float s = 0.0;
|
||||
float l = (maxC + minC) * 0.5;
|
||||
|
||||
if (delta > EPSILON) {
|
||||
s = l < 0.5
|
||||
? delta / (maxC + minC)
|
||||
: delta / (2.0 - maxC - minC);
|
||||
|
||||
if (maxC == c.r) {
|
||||
h = (c.g - c.b) / delta + (c.g < c.b ? 6.0 : 0.0);
|
||||
} else if (maxC == c.g) {
|
||||
h = (c.b - c.r) / delta + 2.0;
|
||||
} else {
|
||||
h = (c.r - c.g) / delta + 4.0;
|
||||
}
|
||||
h /= 6.0;
|
||||
}
|
||||
|
||||
return vec3(h, s, l);
|
||||
}
|
||||
|
||||
float hue2rgb(float p, float q, float t) {
|
||||
t = fract(t);
|
||||
if (t < 1.0/6.0) return p + (q - p) * 6.0 * t;
|
||||
if (t < 0.5) return q;
|
||||
if (t < 2.0/3.0) return p + (q - p) * (2.0/3.0 - t) * 6.0;
|
||||
return p;
|
||||
}
|
||||
|
||||
vec3 hsl2rgb(vec3 hsl) {
|
||||
if (hsl.y < EPSILON) return vec3(hsl.z);
|
||||
|
||||
float q = hsl.z < 0.5
|
||||
? hsl.z * (1.0 + hsl.y)
|
||||
: hsl.z + hsl.y - hsl.z * hsl.y;
|
||||
float p = 2.0 * hsl.z - q;
|
||||
|
||||
return vec3(
|
||||
hue2rgb(p, q, hsl.x + 1.0/3.0),
|
||||
hue2rgb(p, q, hsl.x),
|
||||
hue2rgb(p, q, hsl.x - 1.0/3.0)
|
||||
);
|
||||
}
|
||||
|
||||
vec3 rgb2hsb(vec3 c) {
|
||||
float maxC = max(max(c.r, c.g), c.b);
|
||||
float minC = min(min(c.r, c.g), c.b);
|
||||
float delta = maxC - minC;
|
||||
|
||||
float h = 0.0;
|
||||
float s = (maxC > EPSILON) ? delta / maxC : 0.0;
|
||||
float b = maxC;
|
||||
|
||||
if (delta > EPSILON) {
|
||||
if (maxC == c.r) {
|
||||
h = (c.g - c.b) / delta + (c.g < c.b ? 6.0 : 0.0);
|
||||
} else if (maxC == c.g) {
|
||||
h = (c.b - c.r) / delta + 2.0;
|
||||
} else {
|
||||
h = (c.r - c.g) / delta + 4.0;
|
||||
}
|
||||
h /= 6.0;
|
||||
}
|
||||
|
||||
return vec3(h, s, b);
|
||||
}
|
||||
|
||||
vec3 hsb2rgb(vec3 hsb) {
|
||||
vec3 rgb = clamp(abs(mod(hsb.x * 6.0 + vec3(0.0, 4.0, 2.0), 6.0) - 3.0) - 1.0, 0.0, 1.0);
|
||||
return hsb.z * mix(vec3(1.0), rgb, hsb.y);
|
||||
}
|
||||
|
||||
//=============================================================================
|
||||
// Color Range Weight Calculation
|
||||
//=============================================================================
|
||||
|
||||
float hueDistance(float a, float b) {
|
||||
float d = abs(a - b);
|
||||
return min(d, 1.0 - d);
|
||||
}
|
||||
|
||||
float getHueWeight(float hue, float center, float overlap) {
|
||||
float baseWidth = 1.0 / 6.0;
|
||||
float feather = baseWidth * overlap;
|
||||
|
||||
float d = hueDistance(hue, center);
|
||||
|
||||
float inner = baseWidth * 0.5;
|
||||
float outer = inner + feather;
|
||||
|
||||
return 1.0 - smoothstep(inner, outer, d);
|
||||
}
|
||||
|
||||
float getModeWeight(float hue, int mode, float overlap) {
|
||||
if (mode == MODE_MASTER || mode == MODE_COLORIZE) return 1.0;
|
||||
|
||||
if (mode == MODE_RED) {
|
||||
return max(
|
||||
getHueWeight(hue, 0.0, overlap),
|
||||
getHueWeight(hue, 1.0, overlap)
|
||||
);
|
||||
}
|
||||
|
||||
float center = float(mode - 1) / 6.0;
|
||||
return getHueWeight(hue, center, overlap);
|
||||
}
|
||||
|
||||
//=============================================================================
|
||||
// Adjustment Functions
|
||||
//=============================================================================
|
||||
|
||||
float adjustLightness(float l, float amount) {
|
||||
return amount > 0.0
|
||||
? l + (1.0 - l) * amount
|
||||
: l + l * amount;
|
||||
}
|
||||
|
||||
float adjustBrightness(float b, float amount) {
|
||||
return clamp(b + amount, 0.0, 1.0);
|
||||
}
|
||||
|
||||
float adjustSaturation(float s, float amount) {
|
||||
return amount > 0.0
|
||||
? s + (1.0 - s) * amount
|
||||
: s + s * amount;
|
||||
}
|
||||
|
||||
vec3 colorize(vec3 rgb, float hue, float sat, float light) {
|
||||
float lum = dot(rgb, vec3(0.299, 0.587, 0.114));
|
||||
float l = adjustLightness(lum, light);
|
||||
|
||||
vec3 hsl = vec3(fract(hue), clamp(sat, 0.0, 1.0), clamp(l, 0.0, 1.0));
|
||||
return hsl2rgb(hsl);
|
||||
}
|
||||
|
||||
//=============================================================================
|
||||
// Main
|
||||
//=============================================================================
|
||||
|
||||
void main() {
|
||||
vec4 original = texture(u_image0, v_texCoord);
|
||||
|
||||
float hueShift = u_float0 / 360.0; // -180..180 -> -0.5..0.5
|
||||
float satAmount = u_float1 / 100.0; // -100..100 -> -1..1
|
||||
float lightAmount= u_float2 / 100.0; // -100..100 -> -1..1
|
||||
float overlap = u_float3 / 100.0; // 0..100 -> 0..1
|
||||
|
||||
vec3 result;
|
||||
|
||||
if (u_int0 == MODE_COLORIZE) {
|
||||
result = colorize(original.rgb, hueShift, satAmount, lightAmount);
|
||||
fragColor = vec4(result, original.a);
|
||||
return;
|
||||
}
|
||||
|
||||
vec3 hsx = (u_int1 == COLORSPACE_HSL)
|
||||
? rgb2hsl(original.rgb)
|
||||
: rgb2hsb(original.rgb);
|
||||
|
||||
float weight = getModeWeight(hsx.x, u_int0, overlap);
|
||||
|
||||
if (u_int0 != MODE_MASTER && hsx.y < EPSILON) {
|
||||
weight = 0.0;
|
||||
}
|
||||
|
||||
if (weight > EPSILON) {
|
||||
float h = fract(hsx.x + hueShift * weight);
|
||||
float s = clamp(adjustSaturation(hsx.y, satAmount * weight), 0.0, 1.0);
|
||||
float v = (u_int1 == COLORSPACE_HSL)
|
||||
? clamp(adjustLightness(hsx.z, lightAmount * weight), 0.0, 1.0)
|
||||
: clamp(adjustBrightness(hsx.z, lightAmount * weight), 0.0, 1.0);
|
||||
|
||||
vec3 adjusted = vec3(h, s, v);
|
||||
result = (u_int1 == COLORSPACE_HSL)
|
||||
? hsl2rgb(adjusted)
|
||||
: hsb2rgb(adjusted);
|
||||
} else {
|
||||
result = original.rgb;
|
||||
}
|
||||
|
||||
fragColor = vec4(result, original.a);
|
||||
}
|
||||
@ -1,111 +0,0 @@
|
||||
#version 300 es
|
||||
#pragma passes 2
|
||||
precision highp float;
|
||||
|
||||
// Blur type constants
|
||||
const int BLUR_GAUSSIAN = 0;
|
||||
const int BLUR_BOX = 1;
|
||||
const int BLUR_RADIAL = 2;
|
||||
|
||||
// Radial blur config
|
||||
const int RADIAL_SAMPLES = 12;
|
||||
const float RADIAL_STRENGTH = 0.0003;
|
||||
|
||||
uniform sampler2D u_image0;
|
||||
uniform vec2 u_resolution;
|
||||
uniform int u_int0; // Blur type (BLUR_GAUSSIAN, BLUR_BOX, BLUR_RADIAL)
|
||||
uniform float u_float0; // Blur radius/amount
|
||||
uniform int u_pass; // Pass index (0 = horizontal, 1 = vertical)
|
||||
|
||||
in vec2 v_texCoord;
|
||||
layout(location = 0) out vec4 fragColor0;
|
||||
|
||||
float gaussian(float x, float sigma) {
|
||||
return exp(-(x * x) / (2.0 * sigma * sigma));
|
||||
}
|
||||
|
||||
void main() {
|
||||
vec2 texelSize = 1.0 / u_resolution;
|
||||
float radius = max(u_float0, 0.0);
|
||||
|
||||
// Radial (angular) blur - single pass, doesn't use separable
|
||||
if (u_int0 == BLUR_RADIAL) {
|
||||
// Only execute on first pass
|
||||
if (u_pass > 0) {
|
||||
fragColor0 = texture(u_image0, v_texCoord);
|
||||
return;
|
||||
}
|
||||
|
||||
vec2 center = vec2(0.5);
|
||||
vec2 dir = v_texCoord - center;
|
||||
float dist = length(dir);
|
||||
|
||||
if (dist < 1e-4) {
|
||||
fragColor0 = texture(u_image0, v_texCoord);
|
||||
return;
|
||||
}
|
||||
|
||||
vec4 sum = vec4(0.0);
|
||||
float totalWeight = 0.0;
|
||||
float angleStep = radius * RADIAL_STRENGTH;
|
||||
|
||||
dir /= dist;
|
||||
|
||||
float cosStep = cos(angleStep);
|
||||
float sinStep = sin(angleStep);
|
||||
|
||||
float negAngle = -float(RADIAL_SAMPLES) * angleStep;
|
||||
vec2 rotDir = vec2(
|
||||
dir.x * cos(negAngle) - dir.y * sin(negAngle),
|
||||
dir.x * sin(negAngle) + dir.y * cos(negAngle)
|
||||
);
|
||||
|
||||
for (int i = -RADIAL_SAMPLES; i <= RADIAL_SAMPLES; i++) {
|
||||
vec2 uv = center + rotDir * dist;
|
||||
float w = 1.0 - abs(float(i)) / float(RADIAL_SAMPLES);
|
||||
sum += texture(u_image0, uv) * w;
|
||||
totalWeight += w;
|
||||
|
||||
rotDir = vec2(
|
||||
rotDir.x * cosStep - rotDir.y * sinStep,
|
||||
rotDir.x * sinStep + rotDir.y * cosStep
|
||||
);
|
||||
}
|
||||
|
||||
fragColor0 = sum / max(totalWeight, 0.001);
|
||||
return;
|
||||
}
|
||||
|
||||
// Separable Gaussian / Box blur
|
||||
int samples = int(ceil(radius));
|
||||
|
||||
if (samples == 0) {
|
||||
fragColor0 = texture(u_image0, v_texCoord);
|
||||
return;
|
||||
}
|
||||
|
||||
// Direction: pass 0 = horizontal, pass 1 = vertical
|
||||
vec2 dir = (u_pass == 0) ? vec2(1.0, 0.0) : vec2(0.0, 1.0);
|
||||
|
||||
vec4 color = vec4(0.0);
|
||||
float totalWeight = 0.0;
|
||||
float sigma = radius / 2.0;
|
||||
|
||||
for (int i = -samples; i <= samples; i++) {
|
||||
vec2 offset = dir * float(i) * texelSize;
|
||||
vec4 sample_color = texture(u_image0, v_texCoord + offset);
|
||||
|
||||
float weight;
|
||||
if (u_int0 == BLUR_GAUSSIAN) {
|
||||
weight = gaussian(float(i), sigma);
|
||||
} else {
|
||||
// BLUR_BOX
|
||||
weight = 1.0;
|
||||
}
|
||||
|
||||
color += sample_color * weight;
|
||||
totalWeight += weight;
|
||||
}
|
||||
|
||||
fragColor0 = color / totalWeight;
|
||||
}
|
||||
@ -1,19 +0,0 @@
|
||||
#version 300 es
|
||||
precision highp float;
|
||||
|
||||
uniform sampler2D u_image0;
|
||||
|
||||
in vec2 v_texCoord;
|
||||
layout(location = 0) out vec4 fragColor0;
|
||||
layout(location = 1) out vec4 fragColor1;
|
||||
layout(location = 2) out vec4 fragColor2;
|
||||
layout(location = 3) out vec4 fragColor3;
|
||||
|
||||
void main() {
|
||||
vec4 color = texture(u_image0, v_texCoord);
|
||||
// Output each channel as grayscale to separate render targets
|
||||
fragColor0 = vec4(vec3(color.r), 1.0); // Red channel
|
||||
fragColor1 = vec4(vec3(color.g), 1.0); // Green channel
|
||||
fragColor2 = vec4(vec3(color.b), 1.0); // Blue channel
|
||||
fragColor3 = vec4(vec3(color.a), 1.0); // Alpha channel
|
||||
}
|
||||
@ -1,71 +0,0 @@
|
||||
#version 300 es
|
||||
precision highp float;
|
||||
|
||||
// Levels Adjustment
|
||||
// u_int0: channel (0=RGB, 1=R, 2=G, 3=B) default: 0
|
||||
// u_float0: input black (0-255) default: 0
|
||||
// u_float1: input white (0-255) default: 255
|
||||
// u_float2: gamma (0.01-9.99) default: 1.0
|
||||
// u_float3: output black (0-255) default: 0
|
||||
// u_float4: output white (0-255) default: 255
|
||||
|
||||
uniform sampler2D u_image0;
|
||||
uniform int u_int0;
|
||||
uniform float u_float0;
|
||||
uniform float u_float1;
|
||||
uniform float u_float2;
|
||||
uniform float u_float3;
|
||||
uniform float u_float4;
|
||||
|
||||
in vec2 v_texCoord;
|
||||
out vec4 fragColor;
|
||||
|
||||
vec3 applyLevels(vec3 color, float inBlack, float inWhite, float gamma, float outBlack, float outWhite) {
|
||||
float inRange = max(inWhite - inBlack, 0.0001);
|
||||
vec3 result = clamp((color - inBlack) / inRange, 0.0, 1.0);
|
||||
result = pow(result, vec3(1.0 / gamma));
|
||||
result = mix(vec3(outBlack), vec3(outWhite), result);
|
||||
return result;
|
||||
}
|
||||
|
||||
float applySingleChannel(float value, float inBlack, float inWhite, float gamma, float outBlack, float outWhite) {
|
||||
float inRange = max(inWhite - inBlack, 0.0001);
|
||||
float result = clamp((value - inBlack) / inRange, 0.0, 1.0);
|
||||
result = pow(result, 1.0 / gamma);
|
||||
result = mix(outBlack, outWhite, result);
|
||||
return result;
|
||||
}
|
||||
|
||||
void main() {
|
||||
vec4 texColor = texture(u_image0, v_texCoord);
|
||||
vec3 color = texColor.rgb;
|
||||
|
||||
float inBlack = u_float0 / 255.0;
|
||||
float inWhite = u_float1 / 255.0;
|
||||
float gamma = u_float2;
|
||||
float outBlack = u_float3 / 255.0;
|
||||
float outWhite = u_float4 / 255.0;
|
||||
|
||||
vec3 result;
|
||||
|
||||
if (u_int0 == 0) {
|
||||
result = applyLevels(color, inBlack, inWhite, gamma, outBlack, outWhite);
|
||||
}
|
||||
else if (u_int0 == 1) {
|
||||
result = color;
|
||||
result.r = applySingleChannel(color.r, inBlack, inWhite, gamma, outBlack, outWhite);
|
||||
}
|
||||
else if (u_int0 == 2) {
|
||||
result = color;
|
||||
result.g = applySingleChannel(color.g, inBlack, inWhite, gamma, outBlack, outWhite);
|
||||
}
|
||||
else if (u_int0 == 3) {
|
||||
result = color;
|
||||
result.b = applySingleChannel(color.b, inBlack, inWhite, gamma, outBlack, outWhite);
|
||||
}
|
||||
else {
|
||||
result = color;
|
||||
}
|
||||
|
||||
fragColor = vec4(result, texColor.a);
|
||||
}
|
||||
@ -1,28 +0,0 @@
|
||||
# GLSL Shader Sources
|
||||
|
||||
This folder contains the GLSL fragment shaders extracted from blueprint JSON files for easier editing and version control.
|
||||
|
||||
## File Naming Convention
|
||||
|
||||
`{Blueprint_Name}_{node_id}.frag`
|
||||
|
||||
- **Blueprint_Name**: The JSON filename with spaces/special chars replaced by underscores
|
||||
- **node_id**: The GLSLShader node ID within the subgraph
|
||||
|
||||
## Usage
|
||||
|
||||
```bash
|
||||
# Extract shaders from blueprint JSONs to this folder
|
||||
python update_blueprints.py extract
|
||||
|
||||
# Patch edited shaders back into blueprint JSONs
|
||||
python update_blueprints.py patch
|
||||
```
|
||||
|
||||
## Workflow
|
||||
|
||||
1. Run `extract` to pull current shaders from JSONs
|
||||
2. Edit `.frag` files
|
||||
3. Run `patch` to update the blueprint JSONs
|
||||
4. Test
|
||||
5. Commit both `.frag` files and updated JSONs
|
||||
@ -1,28 +0,0 @@
|
||||
#version 300 es
|
||||
precision highp float;
|
||||
|
||||
uniform sampler2D u_image0;
|
||||
uniform vec2 u_resolution;
|
||||
uniform float u_float0; // strength [0.0 – 2.0] typical: 0.3–1.0
|
||||
|
||||
in vec2 v_texCoord;
|
||||
layout(location = 0) out vec4 fragColor0;
|
||||
|
||||
void main() {
|
||||
vec2 texel = 1.0 / u_resolution;
|
||||
|
||||
// Sample center and neighbors
|
||||
vec4 center = texture(u_image0, v_texCoord);
|
||||
vec4 top = texture(u_image0, v_texCoord + vec2( 0.0, -texel.y));
|
||||
vec4 bottom = texture(u_image0, v_texCoord + vec2( 0.0, texel.y));
|
||||
vec4 left = texture(u_image0, v_texCoord + vec2(-texel.x, 0.0));
|
||||
vec4 right = texture(u_image0, v_texCoord + vec2( texel.x, 0.0));
|
||||
|
||||
// Edge enhancement (Laplacian)
|
||||
vec4 edges = center * 4.0 - top - bottom - left - right;
|
||||
|
||||
// Add edges back scaled by strength
|
||||
vec4 sharpened = center + edges * u_float0;
|
||||
|
||||
fragColor0 = vec4(clamp(sharpened.rgb, 0.0, 1.0), center.a);
|
||||
}
|
||||
@ -1,61 +0,0 @@
|
||||
#version 300 es
|
||||
precision highp float;
|
||||
|
||||
uniform sampler2D u_image0;
|
||||
uniform vec2 u_resolution;
|
||||
uniform float u_float0; // amount [0.0 - 3.0] typical: 0.5-1.5
|
||||
uniform float u_float1; // radius [0.5 - 10.0] blur radius in pixels
|
||||
uniform float u_float2; // threshold [0.0 - 0.1] min difference to sharpen
|
||||
|
||||
in vec2 v_texCoord;
|
||||
layout(location = 0) out vec4 fragColor0;
|
||||
|
||||
float gaussian(float x, float sigma) {
|
||||
return exp(-(x * x) / (2.0 * sigma * sigma));
|
||||
}
|
||||
|
||||
float getLuminance(vec3 color) {
|
||||
return dot(color, vec3(0.2126, 0.7152, 0.0722));
|
||||
}
|
||||
|
||||
void main() {
|
||||
vec2 texel = 1.0 / u_resolution;
|
||||
float radius = max(u_float1, 0.5);
|
||||
float amount = u_float0;
|
||||
float threshold = u_float2;
|
||||
|
||||
vec4 original = texture(u_image0, v_texCoord);
|
||||
|
||||
// Gaussian blur for the "unsharp" mask
|
||||
int samples = int(ceil(radius));
|
||||
float sigma = radius / 2.0;
|
||||
|
||||
vec4 blurred = vec4(0.0);
|
||||
float totalWeight = 0.0;
|
||||
|
||||
for (int x = -samples; x <= samples; x++) {
|
||||
for (int y = -samples; y <= samples; y++) {
|
||||
vec2 offset = vec2(float(x), float(y)) * texel;
|
||||
vec4 sample_color = texture(u_image0, v_texCoord + offset);
|
||||
|
||||
float dist = length(vec2(float(x), float(y)));
|
||||
float weight = gaussian(dist, sigma);
|
||||
blurred += sample_color * weight;
|
||||
totalWeight += weight;
|
||||
}
|
||||
}
|
||||
blurred /= totalWeight;
|
||||
|
||||
// Unsharp mask = original - blurred
|
||||
vec3 mask = original.rgb - blurred.rgb;
|
||||
|
||||
// Luminance-based threshold with smooth falloff
|
||||
float lumaDelta = abs(getLuminance(original.rgb) - getLuminance(blurred.rgb));
|
||||
float thresholdScale = smoothstep(0.0, threshold, lumaDelta);
|
||||
mask *= thresholdScale;
|
||||
|
||||
// Sharpen: original + mask * amount
|
||||
vec3 sharpened = original.rgb + mask * amount;
|
||||
|
||||
fragColor0 = vec4(clamp(sharpened, 0.0, 1.0), original.a);
|
||||
}
|
||||
@ -1,159 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Shader Blueprint Updater
|
||||
|
||||
Syncs GLSL shader files between this folder and blueprint JSON files.
|
||||
|
||||
File naming convention:
|
||||
{Blueprint Name}_{node_id}.frag
|
||||
|
||||
Usage:
|
||||
python update_blueprints.py extract # Extract shaders from JSONs to here
|
||||
python update_blueprints.py patch # Patch shaders back into JSONs
|
||||
python update_blueprints.py # Same as patch (default)
|
||||
"""
|
||||
|
||||
import json
|
||||
import logging
|
||||
import sys
|
||||
import re
|
||||
from pathlib import Path
|
||||
|
||||
logging.basicConfig(level=logging.INFO, format='%(message)s')
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
GLSL_DIR = Path(__file__).parent
|
||||
BLUEPRINTS_DIR = GLSL_DIR.parent
|
||||
|
||||
|
||||
def get_blueprint_files():
|
||||
"""Get all blueprint JSON files."""
|
||||
return sorted(BLUEPRINTS_DIR.glob("*.json"))
|
||||
|
||||
|
||||
def sanitize_filename(name):
|
||||
"""Convert blueprint name to safe filename."""
|
||||
return re.sub(r'[^\w\-]', '_', name)
|
||||
|
||||
|
||||
def extract_shaders():
|
||||
"""Extract all shaders from blueprint JSONs to this folder."""
|
||||
extracted = 0
|
||||
for json_path in get_blueprint_files():
|
||||
blueprint_name = json_path.stem
|
||||
|
||||
try:
|
||||
with open(json_path, 'r') as f:
|
||||
data = json.load(f)
|
||||
except (json.JSONDecodeError, IOError) as e:
|
||||
logger.warning("Skipping %s: %s", json_path.name, e)
|
||||
continue
|
||||
|
||||
# Find GLSLShader nodes in subgraphs
|
||||
for subgraph in data.get('definitions', {}).get('subgraphs', []):
|
||||
for node in subgraph.get('nodes', []):
|
||||
if node.get('type') == 'GLSLShader':
|
||||
node_id = node.get('id')
|
||||
widgets = node.get('widgets_values', [])
|
||||
|
||||
# Find shader code (first string that looks like GLSL)
|
||||
for widget in widgets:
|
||||
if isinstance(widget, str) and widget.startswith('#version'):
|
||||
safe_name = sanitize_filename(blueprint_name)
|
||||
frag_name = f"{safe_name}_{node_id}.frag"
|
||||
frag_path = GLSL_DIR / frag_name
|
||||
|
||||
with open(frag_path, 'w') as f:
|
||||
f.write(widget)
|
||||
|
||||
logger.info(" Extracted: %s", frag_name)
|
||||
extracted += 1
|
||||
break
|
||||
|
||||
logger.info("\nExtracted %d shader(s)", extracted)
|
||||
|
||||
|
||||
def patch_shaders():
|
||||
"""Patch shaders from this folder back into blueprint JSONs."""
|
||||
# Build lookup: blueprint_name -> [(node_id, shader_code), ...]
|
||||
shader_updates = {}
|
||||
|
||||
for frag_path in sorted(GLSL_DIR.glob("*.frag")):
|
||||
# Parse filename: {blueprint_name}_{node_id}.frag
|
||||
parts = frag_path.stem.rsplit('_', 1)
|
||||
if len(parts) != 2:
|
||||
logger.warning("Skipping %s: invalid filename format", frag_path.name)
|
||||
continue
|
||||
|
||||
blueprint_name, node_id_str = parts
|
||||
|
||||
try:
|
||||
node_id = int(node_id_str)
|
||||
except ValueError:
|
||||
logger.warning("Skipping %s: invalid node_id", frag_path.name)
|
||||
continue
|
||||
|
||||
with open(frag_path, 'r') as f:
|
||||
shader_code = f.read()
|
||||
|
||||
if blueprint_name not in shader_updates:
|
||||
shader_updates[blueprint_name] = []
|
||||
shader_updates[blueprint_name].append((node_id, shader_code))
|
||||
|
||||
# Apply updates to JSON files
|
||||
patched = 0
|
||||
for json_path in get_blueprint_files():
|
||||
blueprint_name = sanitize_filename(json_path.stem)
|
||||
|
||||
if blueprint_name not in shader_updates:
|
||||
continue
|
||||
|
||||
try:
|
||||
with open(json_path, 'r') as f:
|
||||
data = json.load(f)
|
||||
except (json.JSONDecodeError, IOError) as e:
|
||||
logger.error("Error reading %s: %s", json_path.name, e)
|
||||
continue
|
||||
|
||||
modified = False
|
||||
for node_id, shader_code in shader_updates[blueprint_name]:
|
||||
# Find the node and update
|
||||
for subgraph in data.get('definitions', {}).get('subgraphs', []):
|
||||
for node in subgraph.get('nodes', []):
|
||||
if node.get('id') == node_id and node.get('type') == 'GLSLShader':
|
||||
widgets = node.get('widgets_values', [])
|
||||
if len(widgets) > 0 and widgets[0] != shader_code:
|
||||
widgets[0] = shader_code
|
||||
modified = True
|
||||
logger.info(" Patched: %s (node %d)", json_path.name, node_id)
|
||||
patched += 1
|
||||
|
||||
if modified:
|
||||
with open(json_path, 'w') as f:
|
||||
json.dump(data, f)
|
||||
|
||||
if patched == 0:
|
||||
logger.info("No changes to apply.")
|
||||
else:
|
||||
logger.info("\nPatched %d shader(s)", patched)
|
||||
|
||||
|
||||
def main():
|
||||
if len(sys.argv) < 2:
|
||||
command = "patch"
|
||||
else:
|
||||
command = sys.argv[1].lower()
|
||||
|
||||
if command == "extract":
|
||||
logger.info("Extracting shaders from blueprints...")
|
||||
extract_shaders()
|
||||
elif command in ("patch", "update", "apply"):
|
||||
logger.info("Patching shaders into blueprints...")
|
||||
patch_shaders()
|
||||
else:
|
||||
logger.info(__doc__)
|
||||
sys.exit(1)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
@ -1 +0,0 @@
|
||||
{"revision": 0, "last_node_id": 29, "last_link_id": 0, "nodes": [{"id": 29, "type": "4c9d6ea4-b912-40e5-8766-6793a9758c53", "pos": [1970, -230], "size": [180, 86], "flags": {}, "order": 5, "mode": 0, "inputs": [{"label": "image", "localized_name": "images.image0", "name": "images.image0", "type": "IMAGE", "link": null}], "outputs": [{"label": "R", "localized_name": "IMAGE0", "name": "IMAGE0", "type": "IMAGE", "links": []}, {"label": "G", "localized_name": "IMAGE1", "name": "IMAGE1", "type": "IMAGE", "links": []}, {"label": "B", "localized_name": "IMAGE2", "name": "IMAGE2", "type": "IMAGE", "links": []}, {"label": "A", "localized_name": "IMAGE3", "name": "IMAGE3", "type": "IMAGE", "links": []}], "title": "Image Channels", "properties": {"proxyWidgets": []}, "widgets_values": []}], "links": [], "version": 0.4, "definitions": {"subgraphs": [{"id": "4c9d6ea4-b912-40e5-8766-6793a9758c53", "version": 1, "state": {"lastGroupId": 0, "lastNodeId": 28, "lastLinkId": 39, "lastRerouteId": 0}, "revision": 0, "config": {}, "name": "Image Channels", "inputNode": {"id": -10, "bounding": [1820, -185, 120, 60]}, "outputNode": {"id": -20, "bounding": [2460, -215, 120, 120]}, "inputs": [{"id": "3522932b-2d86-4a1f-a02a-cb29f3a9d7fe", "name": "images.image0", "type": "IMAGE", "linkIds": [39], "localized_name": "images.image0", "label": "image", "pos": [1920, -165]}], "outputs": [{"id": "605cb9c3-b065-4d9b-81d2-3ec331889b2b", "name": "IMAGE0", "type": "IMAGE", "linkIds": [26], "localized_name": "IMAGE0", "label": "R", "pos": [2480, -195]}, {"id": "fb44a77e-0522-43e9-9527-82e7465b3596", "name": "IMAGE1", "type": "IMAGE", "linkIds": [27], "localized_name": "IMAGE1", "label": "G", "pos": [2480, -175]}, {"id": "81460ee6-0131-402a-874f-6bf3001fc4ff", "name": "IMAGE2", "type": "IMAGE", "linkIds": [28], "localized_name": "IMAGE2", "label": "B", "pos": [2480, -155]}, {"id": "ae690246-80d4-4951-b1d9-9306d8a77417", "name": "IMAGE3", "type": "IMAGE", "linkIds": [29], "localized_name": "IMAGE3", "label": "A", "pos": [2480, -135]}], "widgets": [], "nodes": [{"id": 23, "type": "GLSLShader", "pos": [2000, -330], "size": [400, 172], "flags": {}, "order": 0, "mode": 0, "inputs": [{"label": "image", "localized_name": "images.image0", "name": "images.image0", "type": "IMAGE", "link": 39}, {"localized_name": "fragment_shader", "name": "fragment_shader", "type": "STRING", "widget": {"name": "fragment_shader"}, "link": null}, {"localized_name": "size_mode", "name": "size_mode", "type": "COMFY_DYNAMICCOMBO_V3", "widget": {"name": "size_mode"}, "link": null}, {"label": "image1", "localized_name": "images.image1", "name": "images.image1", "shape": 7, "type": "IMAGE", "link": null}], "outputs": [{"label": "R", "localized_name": "IMAGE0", "name": "IMAGE0", "type": "IMAGE", "links": [26]}, {"label": "G", "localized_name": "IMAGE1", "name": "IMAGE1", "type": "IMAGE", "links": [27]}, {"label": "B", "localized_name": "IMAGE2", "name": "IMAGE2", "type": "IMAGE", "links": [28]}, {"label": "A", "localized_name": "IMAGE3", "name": "IMAGE3", "type": "IMAGE", "links": [29]}], "properties": {"Node name for S&R": "GLSLShader"}, "widgets_values": ["#version 300 es\nprecision highp float;\n\nuniform sampler2D u_image0;\n\nin vec2 v_texCoord;\nlayout(location = 0) out vec4 fragColor0;\nlayout(location = 1) out vec4 fragColor1;\nlayout(location = 2) out vec4 fragColor2;\nlayout(location = 3) out vec4 fragColor3;\n\nvoid main() {\n vec4 color = texture(u_image0, v_texCoord);\n // Output each channel as grayscale to separate render targets\n fragColor0 = vec4(vec3(color.r), 1.0); // Red channel\n fragColor1 = vec4(vec3(color.g), 1.0); // Green channel\n fragColor2 = vec4(vec3(color.b), 1.0); // Blue channel\n fragColor3 = vec4(vec3(color.a), 1.0); // Alpha channel\n}\n", "from_input"]}], "groups": [], "links": [{"id": 39, "origin_id": -10, "origin_slot": 0, "target_id": 23, "target_slot": 0, "type": "IMAGE"}, {"id": 26, "origin_id": 23, "origin_slot": 0, "target_id": -20, "target_slot": 0, "type": "IMAGE"}, {"id": 27, "origin_id": 23, "origin_slot": 1, "target_id": -20, "target_slot": 1, "type": "IMAGE"}, {"id": 28, "origin_id": 23, "origin_slot": 2, "target_id": -20, "target_slot": 2, "type": "IMAGE"}, {"id": 29, "origin_id": 23, "origin_slot": 3, "target_id": -20, "target_slot": 3, "type": "IMAGE"}], "extra": {"workflowRendererVersion": "LG"}, "category": "Image Tools/Color adjust"}]}}
|
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|
||||
{"revision": 0, "last_node_id": 15, "last_link_id": 0, "nodes": [{"id": 15, "type": "24d8bbfd-39d4-4774-bff0-3de40cc7a471", "pos": [-1490, 2040], "size": [400, 260], "flags": {}, "order": 0, "mode": 0, "inputs": [{"name": "prompt", "type": "STRING", "widget": {"name": "prompt"}, "link": null}, {"label": "reference images", "name": "images", "type": "IMAGE", "link": null}], "outputs": [{"name": "STRING", "type": "STRING", "links": null}], "title": "Prompt Enhance", "properties": {"proxyWidgets": [["-1", "prompt"]], "cnr_id": "comfy-core", "ver": "0.14.1"}, "widgets_values": [""]}], "links": [], "version": 0.4, "definitions": {"subgraphs": [{"id": "24d8bbfd-39d4-4774-bff0-3de40cc7a471", "version": 1, "state": {"lastGroupId": 0, "lastNodeId": 15, "lastLinkId": 14, "lastRerouteId": 0}, "revision": 0, "config": {}, "name": "Prompt Enhance", "inputNode": {"id": -10, "bounding": [-2170, 2110, 138.876953125, 80]}, "outputNode": {"id": -20, "bounding": [-640, 2110, 120, 60]}, "inputs": [{"id": "aeab7216-00e0-4528-a09b-bba50845c5a6", "name": "prompt", "type": "STRING", "linkIds": [11], "pos": [-2051.123046875, 2130]}, {"id": "7b73fd36-aa31-4771-9066-f6c83879994b", "name": "images", "type": "IMAGE", "linkIds": [14], "label": "reference images", "pos": [-2051.123046875, 2150]}], "outputs": [{"id": "c7b0d930-68a1-48d1-b496-0519e5837064", "name": "STRING", "type": "STRING", "linkIds": [13], "pos": [-620, 2130]}], "widgets": [], "nodes": [{"id": 11, "type": "GeminiNode", "pos": [-1560, 1990], "size": [470, 470], "flags": {}, "order": 0, "mode": 0, "inputs": [{"localized_name": "images", "name": "images", "shape": 7, "type": "IMAGE", "link": 14}, {"localized_name": "audio", "name": "audio", "shape": 7, "type": "AUDIO", "link": null}, {"localized_name": "video", "name": "video", "shape": 7, "type": "VIDEO", "link": null}, {"localized_name": "files", "name": "files", "shape": 7, "type": "GEMINI_INPUT_FILES", "link": null}, {"localized_name": "prompt", "name": "prompt", "type": "STRING", "widget": {"name": "prompt"}, "link": 11}, {"localized_name": "model", "name": "model", "type": "COMBO", "widget": {"name": "model"}, "link": null}, {"localized_name": "seed", "name": "seed", "type": "INT", "widget": {"name": "seed"}, "link": null}, {"localized_name": "system_prompt", "name": "system_prompt", "shape": 7, "type": "STRING", "widget": {"name": "system_prompt"}, "link": null}], "outputs": [{"localized_name": "STRING", "name": "STRING", "type": "STRING", "links": [13]}], "properties": {"cnr_id": "comfy-core", "ver": "0.14.1", "Node name for S&R": "GeminiNode"}, "widgets_values": ["", "gemini-3-pro-preview", 42, "randomize", "You are an expert in prompt writing.\nBased on the input, rewrite the user's input into a detailed prompt.\nincluding camera settings, lighting, composition, and style.\nReturn the prompt only"], "color": "#432", "bgcolor": "#653"}], "groups": [], "links": [{"id": 11, "origin_id": -10, "origin_slot": 0, "target_id": 11, "target_slot": 4, "type": "STRING"}, {"id": 13, "origin_id": 11, "origin_slot": 0, "target_id": -20, "target_slot": 0, "type": "STRING"}, {"id": 14, "origin_id": -10, "origin_slot": 1, "target_id": 11, "target_slot": 0, "type": "IMAGE"}], "extra": {"workflowRendererVersion": "LG"}, "category": "Text generation/Prompt enhance"}]}, "extra": {}}
|
||||
@ -1 +0,0 @@
|
||||
{"revision": 0, "last_node_id": 25, "last_link_id": 0, "nodes": [{"id": 25, "type": "621ba4e2-22a8-482d-a369-023753198b7b", "pos": [4610, -790], "size": [230, 58], "flags": {}, "order": 4, "mode": 0, "inputs": [{"label": "image", "localized_name": "images.image0", "name": "images.image0", "type": "IMAGE", "link": null}], "outputs": [{"label": "IMAGE", "localized_name": "IMAGE0", "name": "IMAGE0", "type": "IMAGE", "links": []}], "title": "Sharpen", "properties": {"proxyWidgets": [["24", "value"]]}, "widgets_values": []}], "links": [], "version": 0.4, "definitions": {"subgraphs": [{"id": "621ba4e2-22a8-482d-a369-023753198b7b", "version": 1, "state": {"lastGroupId": 0, "lastNodeId": 24, "lastLinkId": 36, "lastRerouteId": 0}, "revision": 0, "config": {}, "name": "Sharpen", "inputNode": {"id": -10, "bounding": [4090, -825, 120, 60]}, "outputNode": {"id": -20, "bounding": [5150, -825, 120, 60]}, "inputs": [{"id": "37011fb7-14b7-4e0e-b1a0-6a02e8da1fd7", "name": "images.image0", "type": "IMAGE", "linkIds": [34], "localized_name": "images.image0", "label": "image", "pos": [4190, -805]}], "outputs": [{"id": "e9182b3f-635c-4cd4-a152-4b4be17ae4b9", "name": "IMAGE0", "type": "IMAGE", "linkIds": [35], "localized_name": "IMAGE0", "label": "IMAGE", "pos": [5170, -805]}], "widgets": [], "nodes": [{"id": 24, "type": "PrimitiveFloat", "pos": [4280, -1240], "size": [270, 58], "flags": {}, "order": 0, "mode": 0, "inputs": [{"label": "strength", "localized_name": "value", "name": "value", "type": "FLOAT", "widget": {"name": "value"}, "link": null}], "outputs": [{"localized_name": "FLOAT", "name": "FLOAT", "type": "FLOAT", "links": [36]}], "properties": {"Node name for S&R": "PrimitiveFloat", "min": 0, "max": 3, "precision": 2, "step": 0.05}, "widgets_values": [0.5]}, {"id": 23, "type": "GLSLShader", "pos": [4570, -1240], "size": [370, 192], "flags": {}, "order": 1, "mode": 0, "inputs": [{"label": "image0", "localized_name": "images.image0", "name": "images.image0", "type": "IMAGE", "link": 34}, {"label": "image1", "localized_name": "images.image1", "name": "images.image1", "shape": 7, "type": "IMAGE", "link": null}, {"label": "u_float0", "localized_name": "floats.u_float0", "name": "floats.u_float0", "shape": 7, "type": "FLOAT", "link": 36}, {"label": "u_float1", "localized_name": "floats.u_float1", "name": "floats.u_float1", "shape": 7, "type": "FLOAT", "link": null}, {"label": "u_int0", "localized_name": "ints.u_int0", "name": "ints.u_int0", "shape": 7, "type": "INT", "link": null}, {"localized_name": "fragment_shader", "name": "fragment_shader", "type": "STRING", "widget": {"name": "fragment_shader"}, "link": null}, {"localized_name": "size_mode", "name": "size_mode", "type": "COMFY_DYNAMICCOMBO_V3", "widget": {"name": "size_mode"}, "link": null}], "outputs": [{"localized_name": "IMAGE0", "name": "IMAGE0", "type": "IMAGE", "links": [35]}, {"localized_name": "IMAGE1", "name": "IMAGE1", "type": "IMAGE", "links": null}, {"localized_name": "IMAGE2", "name": "IMAGE2", "type": "IMAGE", "links": null}, {"localized_name": "IMAGE3", "name": "IMAGE3", "type": "IMAGE", "links": null}], "properties": {"Node name for S&R": "GLSLShader"}, "widgets_values": ["#version 300 es\nprecision highp float;\n\nuniform sampler2D u_image0;\nuniform vec2 u_resolution;\nuniform float u_float0; // strength [0.0 – 2.0] typical: 0.3–1.0\n\nin vec2 v_texCoord;\nlayout(location = 0) out vec4 fragColor0;\n\nvoid main() {\n vec2 texel = 1.0 / u_resolution;\n \n // Sample center and neighbors\n vec4 center = texture(u_image0, v_texCoord);\n vec4 top = texture(u_image0, v_texCoord + vec2( 0.0, -texel.y));\n vec4 bottom = texture(u_image0, v_texCoord + vec2( 0.0, texel.y));\n vec4 left = texture(u_image0, v_texCoord + vec2(-texel.x, 0.0));\n vec4 right = texture(u_image0, v_texCoord + vec2( texel.x, 0.0));\n \n // Edge enhancement (Laplacian)\n vec4 edges = center * 4.0 - top - bottom - left - right;\n \n // Add edges back scaled by strength\n vec4 sharpened = center + edges * u_float0;\n \n fragColor0 = vec4(clamp(sharpened.rgb, 0.0, 1.0), center.a);\n}", "from_input"]}], "groups": [], "links": [{"id": 36, "origin_id": 24, "origin_slot": 0, "target_id": 23, "target_slot": 2, "type": "FLOAT"}, {"id": 34, "origin_id": -10, "origin_slot": 0, "target_id": 23, "target_slot": 0, "type": "IMAGE"}, {"id": 35, "origin_id": 23, "origin_slot": 0, "target_id": -20, "target_slot": 0, "type": "IMAGE"}], "extra": {"workflowRendererVersion": "LG"}, "category": "Image Tools/Sharpen"}]}}
|
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|
||||
{"revision": 0, "last_node_id": 13, "last_link_id": 0, "nodes": [{"id": 13, "type": "cf95b747-3e17-46cb-8097-cac60ff9b2e1", "pos": [1120, 330], "size": [240, 58], "flags": {}, "order": 3, "mode": 0, "inputs": [{"localized_name": "video", "name": "video", "type": "VIDEO", "link": null}, {"name": "model_name", "type": "COMBO", "widget": {"name": "model_name"}, "link": null}], "outputs": [{"localized_name": "VIDEO", "name": "VIDEO", "type": "VIDEO", "links": []}], "title": "Video Upscale(GAN x4)", "properties": {"proxyWidgets": [["-1", "model_name"]], "cnr_id": "comfy-core", "ver": "0.14.1"}, "widgets_values": ["RealESRGAN_x4plus.safetensors"]}], "links": [], "version": 0.4, "definitions": {"subgraphs": [{"id": "cf95b747-3e17-46cb-8097-cac60ff9b2e1", "version": 1, "state": {"lastGroupId": 0, "lastNodeId": 13, "lastLinkId": 19, "lastRerouteId": 0}, "revision": 0, "config": {}, "name": "Video Upscale(GAN x4)", "inputNode": {"id": -10, "bounding": [550, 460, 120, 80]}, "outputNode": {"id": -20, "bounding": [1490, 460, 120, 60]}, "inputs": [{"id": "666d633e-93e7-42dc-8d11-2b7b99b0f2a6", "name": "video", "type": "VIDEO", "linkIds": [10], "localized_name": "video", "pos": [650, 480]}, {"id": "2e23a087-caa8-4d65-99e6-662761aa905a", "name": "model_name", "type": "COMBO", "linkIds": [19], "pos": [650, 500]}], "outputs": [{"id": "0c1768ea-3ec2-412f-9af6-8e0fa36dae70", "name": "VIDEO", "type": "VIDEO", "linkIds": [15], "localized_name": "VIDEO", "pos": [1510, 480]}], "widgets": [], "nodes": [{"id": 2, "type": "ImageUpscaleWithModel", "pos": [1110, 450], "size": [320, 46], "flags": {}, "order": 1, "mode": 0, "inputs": [{"localized_name": "upscale_model", "name": "upscale_model", "type": "UPSCALE_MODEL", "link": 1}, {"localized_name": "image", "name": "image", "type": "IMAGE", "link": 14}], "outputs": [{"localized_name": "IMAGE", "name": "IMAGE", "type": "IMAGE", "links": [13]}], "properties": {"cnr_id": "comfy-core", "ver": "0.10.0", "Node name for S&R": "ImageUpscaleWithModel"}}, {"id": 11, "type": "CreateVideo", "pos": [1110, 550], "size": [320, 78], "flags": {}, "order": 3, "mode": 0, "inputs": [{"localized_name": "images", "name": "images", "type": "IMAGE", "link": 13}, {"localized_name": "audio", "name": "audio", "shape": 7, "type": "AUDIO", "link": 16}, {"localized_name": "fps", "name": "fps", "type": "FLOAT", "widget": {"name": "fps"}, "link": 12}], "outputs": [{"localized_name": "VIDEO", "name": "VIDEO", "type": "VIDEO", "links": [15]}], "properties": {"cnr_id": "comfy-core", "ver": "0.10.0", "Node name for S&R": "CreateVideo"}, "widgets_values": [30]}, {"id": 10, "type": "GetVideoComponents", "pos": [1110, 330], "size": [320, 70], "flags": {}, "order": 2, "mode": 0, "inputs": [{"localized_name": "video", "name": "video", "type": "VIDEO", "link": 10}], "outputs": [{"localized_name": "images", "name": "images", "type": "IMAGE", "links": [14]}, {"localized_name": "audio", "name": "audio", "type": "AUDIO", "links": [16]}, {"localized_name": "fps", "name": "fps", "type": "FLOAT", "links": [12]}], "properties": {"cnr_id": "comfy-core", "ver": "0.10.0", "Node name for S&R": "GetVideoComponents"}}, {"id": 1, "type": "UpscaleModelLoader", "pos": [750, 450], "size": [280, 60], "flags": {}, "order": 0, "mode": 0, "inputs": [{"localized_name": "model_name", "name": "model_name", "type": "COMBO", "widget": {"name": "model_name"}, "link": 19}], "outputs": [{"localized_name": "UPSCALE_MODEL", "name": "UPSCALE_MODEL", "type": "UPSCALE_MODEL", "links": [1]}], "properties": {"cnr_id": "comfy-core", "ver": "0.10.0", "Node name for S&R": "UpscaleModelLoader", "models": [{"name": "RealESRGAN_x4plus.safetensors", "url": "https://huggingface.co/Comfy-Org/Real-ESRGAN_repackaged/resolve/main/RealESRGAN_x4plus.safetensors", "directory": "upscale_models"}]}, "widgets_values": ["RealESRGAN_x4plus.safetensors"]}], "groups": [], "links": [{"id": 1, "origin_id": 1, "origin_slot": 0, "target_id": 2, "target_slot": 0, "type": "UPSCALE_MODEL"}, {"id": 14, "origin_id": 10, "origin_slot": 0, "target_id": 2, "target_slot": 1, "type": "IMAGE"}, {"id": 13, "origin_id": 2, "origin_slot": 0, "target_id": 11, "target_slot": 0, "type": "IMAGE"}, {"id": 16, "origin_id": 10, "origin_slot": 1, "target_id": 11, "target_slot": 1, "type": "AUDIO"}, {"id": 12, "origin_id": 10, "origin_slot": 2, "target_id": 11, "target_slot": 2, "type": "FLOAT"}, {"id": 10, "origin_id": -10, "origin_slot": 0, "target_id": 10, "target_slot": 0, "type": "VIDEO"}, {"id": 15, "origin_id": 11, "origin_slot": 0, "target_id": -20, "target_slot": 0, "type": "VIDEO"}, {"id": 19, "origin_id": -10, "origin_slot": 1, "target_id": 1, "target_slot": 0, "type": "COMBO"}], "extra": {"workflowRendererVersion": "LG"}, "category": "Video generation and editing/Enhance video"}]}, "extra": {}}
|
||||
@ -176,8 +176,6 @@ class InputTypeOptions(TypedDict):
|
||||
"""COMBO type only. Specifies the configuration for a multi-select widget.
|
||||
Available after ComfyUI frontend v1.13.4
|
||||
https://github.com/Comfy-Org/ComfyUI_frontend/pull/2987"""
|
||||
gradient_stops: NotRequired[list[list[float]]]
|
||||
"""Gradient color stops for gradientslider display mode. Each stop is [offset, r, g, b] (``FLOAT``)."""
|
||||
|
||||
|
||||
class HiddenInputTypeDict(TypedDict):
|
||||
|
||||
@ -426,8 +426,10 @@ class CLIP:
|
||||
def generate(self, tokens, do_sample=True, max_length=256, temperature=1.0, top_k=50, top_p=0.95, min_p=0.0, repetition_penalty=1.0, seed=None):
|
||||
self.cond_stage_model.reset_clip_options()
|
||||
|
||||
if self.layer_idx is not None:
|
||||
self.cond_stage_model.set_clip_options({"layer": self.layer_idx})
|
||||
|
||||
self.load_model()
|
||||
self.cond_stage_model.set_clip_options({"layer": None})
|
||||
self.cond_stage_model.set_clip_options({"execution_device": self.patcher.load_device})
|
||||
return self.cond_stage_model.generate(tokens, do_sample=do_sample, max_length=max_length, temperature=temperature, top_k=top_k, top_p=top_p, min_p=min_p, repetition_penalty=repetition_penalty, seed=seed)
|
||||
|
||||
|
||||
@ -308,14 +308,14 @@ class SDClipModel(torch.nn.Module, ClipTokenWeightEncoder):
|
||||
def load_sd(self, sd):
|
||||
return self.transformer.load_state_dict(sd, strict=False, assign=getattr(self, "can_assign_sd", False))
|
||||
|
||||
def generate(self, tokens, do_sample, max_length, temperature, top_k, top_p, min_p, repetition_penalty, seed):
|
||||
def generate(self, tokens, do_sample, max_length, temperature, top_k, top_p, min_p, repetition_penalty, seed, stop_tokens=[]):
|
||||
if isinstance(tokens, dict):
|
||||
tokens_only = next(iter(tokens.values())) # todo: get this better?
|
||||
else:
|
||||
tokens_only = tokens
|
||||
tokens_only = [[t[0] for t in b] for b in tokens_only]
|
||||
embeds = self.process_tokens(tokens_only, device=self.execution_device)[0]
|
||||
return self.transformer.generate(embeds, do_sample, max_length, temperature, top_k, top_p, min_p, repetition_penalty, seed)
|
||||
return self.transformer.generate(embeds, do_sample, max_length, temperature, top_k, top_p, min_p, repetition_penalty, seed, stop_tokens)
|
||||
|
||||
def parse_parentheses(string):
|
||||
result = []
|
||||
@ -573,8 +573,6 @@ class SDTokenizer:
|
||||
min_length = tokenizer_options.get("{}_min_length".format(self.embedding_key), self.min_length)
|
||||
min_padding = tokenizer_options.get("{}_min_padding".format(self.embedding_key), self.min_padding)
|
||||
|
||||
min_length = kwargs.get("min_length", min_length)
|
||||
|
||||
text = escape_important(text)
|
||||
if kwargs.get("disable_weights", self.disable_weights):
|
||||
parsed_weights = [(text, 1.0)]
|
||||
|
||||
@ -33,8 +33,6 @@ class AnimaTokenizer:
|
||||
def state_dict(self):
|
||||
return {}
|
||||
|
||||
def decode(self, token_ids, **kwargs):
|
||||
return self.qwen3_06b.decode(token_ids, **kwargs)
|
||||
|
||||
class Qwen3_06BModel(sd1_clip.SDClipModel):
|
||||
def __init__(self, device="cpu", layer="last", layer_idx=None, dtype=None, attention_mask=True, model_options={}):
|
||||
|
||||
@ -105,7 +105,6 @@ class Qwen3_06BConfig:
|
||||
rope_scale = None
|
||||
final_norm: bool = True
|
||||
lm_head: bool = False
|
||||
stop_tokens = [151643, 151645]
|
||||
|
||||
@dataclass
|
||||
class Qwen3_06B_ACE15_Config:
|
||||
@ -129,7 +128,6 @@ class Qwen3_06B_ACE15_Config:
|
||||
rope_scale = None
|
||||
final_norm: bool = True
|
||||
lm_head: bool = False
|
||||
stop_tokens = [151643, 151645]
|
||||
|
||||
@dataclass
|
||||
class Qwen3_2B_ACE15_lm_Config:
|
||||
@ -153,7 +151,6 @@ class Qwen3_2B_ACE15_lm_Config:
|
||||
rope_scale = None
|
||||
final_norm: bool = True
|
||||
lm_head: bool = False
|
||||
stop_tokens = [151643, 151645]
|
||||
|
||||
@dataclass
|
||||
class Qwen3_4B_ACE15_lm_Config:
|
||||
@ -177,7 +174,6 @@ class Qwen3_4B_ACE15_lm_Config:
|
||||
rope_scale = None
|
||||
final_norm: bool = True
|
||||
lm_head: bool = False
|
||||
stop_tokens = [151643, 151645]
|
||||
|
||||
@dataclass
|
||||
class Qwen3_4BConfig:
|
||||
@ -201,7 +197,6 @@ class Qwen3_4BConfig:
|
||||
rope_scale = None
|
||||
final_norm: bool = True
|
||||
lm_head: bool = False
|
||||
stop_tokens = [151643, 151645]
|
||||
|
||||
@dataclass
|
||||
class Qwen3_8BConfig:
|
||||
@ -225,7 +220,6 @@ class Qwen3_8BConfig:
|
||||
rope_scale = None
|
||||
final_norm: bool = True
|
||||
lm_head: bool = False
|
||||
stop_tokens = [151643, 151645]
|
||||
|
||||
@dataclass
|
||||
class Ovis25_2BConfig:
|
||||
@ -296,7 +290,6 @@ class Gemma2_2B_Config:
|
||||
rope_scale = None
|
||||
final_norm: bool = True
|
||||
lm_head: bool = False
|
||||
stop_tokens = [1]
|
||||
|
||||
@dataclass
|
||||
class Gemma3_4B_Config:
|
||||
@ -321,7 +314,6 @@ class Gemma3_4B_Config:
|
||||
rope_scale = [8.0, 1.0]
|
||||
final_norm: bool = True
|
||||
lm_head: bool = False
|
||||
stop_tokens = [1, 106]
|
||||
|
||||
GEMMA3_VISION_CONFIG = {"num_channels": 3, "hidden_act": "gelu_pytorch_tanh", "hidden_size": 1152, "image_size": 896, "intermediate_size": 4304, "model_type": "siglip_vision_model", "num_attention_heads": 16, "num_hidden_layers": 27, "patch_size": 14}
|
||||
|
||||
@ -355,7 +347,6 @@ class Gemma3_12B_Config:
|
||||
lm_head: bool = False
|
||||
vision_config = GEMMA3_VISION_CONFIG
|
||||
mm_tokens_per_image = 256
|
||||
stop_tokens = [1, 106]
|
||||
|
||||
class RMSNorm(nn.Module):
|
||||
def __init__(self, dim: int, eps: float = 1e-5, add=False, device=None, dtype=None):
|
||||
@ -812,13 +803,10 @@ class BaseGenerate:
|
||||
comfy.ops.uncast_bias_weight(module, weight, None, offload_stream)
|
||||
return x
|
||||
|
||||
def generate(self, embeds=None, do_sample=True, max_length=256, temperature=1.0, top_k=50, top_p=0.9, min_p=0.0, repetition_penalty=1.0, seed=42, stop_tokens=None, initial_tokens=[], execution_dtype=None, min_tokens=0):
|
||||
def generate(self, embeds=None, do_sample=True, max_length=256, temperature=1.0, top_k=50, top_p=0.9, min_p=0.0, repetition_penalty=1.0, seed=42, stop_tokens=[], initial_tokens=[], execution_dtype=None, min_tokens=0):
|
||||
device = embeds.device
|
||||
model_config = self.model.config
|
||||
|
||||
if stop_tokens is None:
|
||||
stop_tokens = self.model.config.stop_tokens
|
||||
|
||||
if execution_dtype is None:
|
||||
if comfy.model_management.should_use_bf16(device):
|
||||
execution_dtype = torch.bfloat16
|
||||
@ -937,7 +925,7 @@ class Qwen25_3B(BaseLlama, torch.nn.Module):
|
||||
self.model = Llama2_(config, device=device, dtype=dtype, ops=operations)
|
||||
self.dtype = dtype
|
||||
|
||||
class Qwen3_06B(BaseLlama, BaseQwen3, BaseGenerate, torch.nn.Module):
|
||||
class Qwen3_06B(BaseLlama, BaseQwen3, torch.nn.Module):
|
||||
def __init__(self, config_dict, dtype, device, operations):
|
||||
super().__init__()
|
||||
config = Qwen3_06BConfig(**config_dict)
|
||||
@ -964,7 +952,7 @@ class Qwen3_2B_ACE15_lm(BaseLlama, BaseQwen3, torch.nn.Module):
|
||||
self.model = Llama2_(config, device=device, dtype=dtype, ops=operations)
|
||||
self.dtype = dtype
|
||||
|
||||
class Qwen3_4B(BaseLlama, BaseQwen3, BaseGenerate, torch.nn.Module):
|
||||
class Qwen3_4B(BaseLlama, BaseQwen3, torch.nn.Module):
|
||||
def __init__(self, config_dict, dtype, device, operations):
|
||||
super().__init__()
|
||||
config = Qwen3_4BConfig(**config_dict)
|
||||
@ -982,7 +970,7 @@ class Qwen3_4B_ACE15_lm(BaseLlama, BaseQwen3, torch.nn.Module):
|
||||
self.model = Llama2_(config, device=device, dtype=dtype, ops=operations)
|
||||
self.dtype = dtype
|
||||
|
||||
class Qwen3_8B(BaseLlama, BaseQwen3, BaseGenerate, torch.nn.Module):
|
||||
class Qwen3_8B(BaseLlama, BaseQwen3, torch.nn.Module):
|
||||
def __init__(self, config_dict, dtype, device, operations):
|
||||
super().__init__()
|
||||
config = Qwen3_8BConfig(**config_dict)
|
||||
@ -1046,7 +1034,7 @@ class Qwen25_7BVLI(BaseLlama, BaseGenerate, torch.nn.Module):
|
||||
|
||||
return super().forward(x, attention_mask=attention_mask, embeds=embeds, num_tokens=num_tokens, intermediate_output=intermediate_output, final_layer_norm_intermediate=final_layer_norm_intermediate, dtype=dtype, position_ids=position_ids)
|
||||
|
||||
class Gemma2_2B(BaseLlama, BaseGenerate, torch.nn.Module):
|
||||
class Gemma2_2B(BaseLlama, torch.nn.Module):
|
||||
def __init__(self, config_dict, dtype, device, operations):
|
||||
super().__init__()
|
||||
config = Gemma2_2B_Config(**config_dict)
|
||||
|
||||
@ -31,6 +31,9 @@ class Gemma2_2BModel(sd1_clip.SDClipModel):
|
||||
def __init__(self, device="cpu", layer="hidden", layer_idx=-2, dtype=None, attention_mask=True, model_options={}):
|
||||
super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config={}, dtype=dtype, special_tokens={"start": 2, "pad": 0}, layer_norm_hidden_state=False, model_class=comfy.text_encoders.llama.Gemma2_2B, enable_attention_masks=attention_mask, return_attention_masks=attention_mask, model_options=model_options)
|
||||
|
||||
def generate(self, embeds, do_sample, max_length, temperature, top_k, top_p, min_p, repetition_penalty, seed):
|
||||
return super().generate(embeds, do_sample, max_length, temperature, top_k, top_p, min_p, repetition_penalty, seed, stop_tokens=[107])
|
||||
|
||||
class Gemma3_4BModel(sd1_clip.SDClipModel):
|
||||
def __init__(self, device="cpu", layer="hidden", layer_idx=-2, dtype=None, attention_mask=True, model_options={}):
|
||||
llama_quantization_metadata = model_options.get("llama_quantization_metadata", None)
|
||||
@ -40,6 +43,9 @@ class Gemma3_4BModel(sd1_clip.SDClipModel):
|
||||
|
||||
super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config={}, dtype=dtype, special_tokens={"start": 2, "pad": 0}, layer_norm_hidden_state=False, model_class=comfy.text_encoders.llama.Gemma3_4B, enable_attention_masks=attention_mask, return_attention_masks=attention_mask, model_options=model_options)
|
||||
|
||||
def generate(self, embeds, do_sample, max_length, temperature, top_k, top_p, min_p, repetition_penalty, seed):
|
||||
return super().generate(embeds, do_sample, max_length, temperature, top_k, top_p, min_p, repetition_penalty, seed, stop_tokens=[106])
|
||||
|
||||
class Gemma3_4B_Vision_Model(sd1_clip.SDClipModel):
|
||||
def __init__(self, device="cpu", layer="hidden", layer_idx=-2, dtype=None, attention_mask=True, model_options={}):
|
||||
llama_quantization_metadata = model_options.get("llama_quantization_metadata", None)
|
||||
|
||||
@ -444,7 +444,7 @@ class VideoFromComponents(VideoInput):
|
||||
output.mux(packet)
|
||||
|
||||
if audio_stream and self.__components.audio:
|
||||
frame = av.AudioFrame.from_ndarray(waveform.float().cpu().contiguous().numpy(), format='fltp', layout=layout)
|
||||
frame = av.AudioFrame.from_ndarray(waveform.float().cpu().numpy(), format='fltp', layout=layout)
|
||||
frame.sample_rate = audio_sample_rate
|
||||
frame.pts = 0
|
||||
output.mux(audio_stream.encode(frame))
|
||||
|
||||
@ -73,7 +73,6 @@ class RemoteOptions:
|
||||
class NumberDisplay(str, Enum):
|
||||
number = "number"
|
||||
slider = "slider"
|
||||
gradient_slider = "gradientslider"
|
||||
|
||||
|
||||
class ControlAfterGenerate(str, Enum):
|
||||
@ -297,15 +296,13 @@ class Float(ComfyTypeIO):
|
||||
'''Float input.'''
|
||||
def __init__(self, id: str, display_name: str=None, optional=False, tooltip: str=None, lazy: bool=None,
|
||||
default: float=None, min: float=None, max: float=None, step: float=None, round: float=None,
|
||||
display_mode: NumberDisplay=None, gradient_stops: list[list[float]]=None,
|
||||
socketless: bool=None, force_input: bool=None, extra_dict=None, raw_link: bool=None, advanced: bool=None):
|
||||
display_mode: NumberDisplay=None, socketless: bool=None, force_input: bool=None, extra_dict=None, raw_link: bool=None, advanced: bool=None):
|
||||
super().__init__(id, display_name, optional, tooltip, lazy, default, socketless, None, force_input, extra_dict, raw_link, advanced)
|
||||
self.min = min
|
||||
self.max = max
|
||||
self.step = step
|
||||
self.round = round
|
||||
self.display_mode = display_mode
|
||||
self.gradient_stops = gradient_stops
|
||||
self.default: float
|
||||
|
||||
def as_dict(self):
|
||||
@ -315,7 +312,6 @@ class Float(ComfyTypeIO):
|
||||
"step": self.step,
|
||||
"round": self.round,
|
||||
"display": self.display_mode,
|
||||
"gradient_stops": self.gradient_stops,
|
||||
})
|
||||
|
||||
@comfytype(io_type="STRING")
|
||||
|
||||
@ -1,88 +0,0 @@
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
|
||||
class SpeechToTextRequest(BaseModel):
|
||||
model_id: str = Field(...)
|
||||
cloud_storage_url: str = Field(...)
|
||||
language_code: str | None = Field(None, description="ISO-639-1 or ISO-639-3 language code")
|
||||
tag_audio_events: bool | None = Field(None, description="Annotate sounds like (laughter) in transcript")
|
||||
num_speakers: int | None = Field(None, description="Max speakers predicted")
|
||||
timestamps_granularity: str = Field(default="word", description="Timing precision: none, word, or character")
|
||||
diarize: bool | None = Field(None, description="Annotate which speaker is talking")
|
||||
diarization_threshold: float | None = Field(None, description="Speaker separation sensitivity")
|
||||
temperature: float | None = Field(None, description="Randomness control")
|
||||
seed: int = Field(..., description="Seed for deterministic sampling")
|
||||
|
||||
|
||||
class SpeechToTextWord(BaseModel):
|
||||
text: str = Field(..., description="The word text")
|
||||
type: str = Field(default="word", description="Type of text element (word, spacing, etc.)")
|
||||
start: float | None = Field(None, description="Start time in seconds (when timestamps enabled)")
|
||||
end: float | None = Field(None, description="End time in seconds (when timestamps enabled)")
|
||||
speaker_id: str | None = Field(None, description="Speaker identifier when diarization is enabled")
|
||||
logprob: float | None = Field(None, description="Log probability of the word")
|
||||
|
||||
|
||||
class SpeechToTextResponse(BaseModel):
|
||||
language_code: str = Field(..., description="Detected or specified language code")
|
||||
language_probability: float | None = Field(None, description="Confidence of language detection")
|
||||
text: str = Field(..., description="Full transcript text")
|
||||
words: list[SpeechToTextWord] | None = Field(None, description="Word-level timing information")
|
||||
|
||||
|
||||
class TextToSpeechVoiceSettings(BaseModel):
|
||||
stability: float | None = Field(None, description="Voice stability")
|
||||
similarity_boost: float | None = Field(None, description="Similarity boost")
|
||||
style: float | None = Field(None, description="Style exaggeration")
|
||||
use_speaker_boost: bool | None = Field(None, description="Boost similarity to original speaker")
|
||||
speed: float | None = Field(None, description="Speech speed")
|
||||
|
||||
|
||||
class TextToSpeechRequest(BaseModel):
|
||||
text: str = Field(..., description="Text to convert to speech")
|
||||
model_id: str = Field(..., description="Model ID for TTS")
|
||||
language_code: str | None = Field(None, description="ISO-639-1 or ISO-639-3 language code")
|
||||
voice_settings: TextToSpeechVoiceSettings | None = Field(None, description="Voice settings")
|
||||
seed: int = Field(..., description="Seed for deterministic sampling")
|
||||
apply_text_normalization: str | None = Field(None, description="Text normalization mode: auto, on, off")
|
||||
|
||||
|
||||
class TextToSoundEffectsRequest(BaseModel):
|
||||
text: str = Field(..., description="Text prompt to convert into a sound effect")
|
||||
duration_seconds: float = Field(..., description="Duration of generated sound in seconds")
|
||||
prompt_influence: float = Field(..., description="How closely generation follows the prompt")
|
||||
loop: bool | None = Field(None, description="Whether to create a smoothly looping sound effect")
|
||||
|
||||
|
||||
class AddVoiceRequest(BaseModel):
|
||||
name: str = Field(..., description="Name that identifies the voice")
|
||||
remove_background_noise: bool = Field(..., description="Remove background noise from voice samples")
|
||||
|
||||
|
||||
class AddVoiceResponse(BaseModel):
|
||||
voice_id: str = Field(..., description="The newly created voice's unique identifier")
|
||||
|
||||
|
||||
class SpeechToSpeechRequest(BaseModel):
|
||||
model_id: str = Field(..., description="Model ID for speech-to-speech")
|
||||
voice_settings: str = Field(..., description="JSON string of voice settings")
|
||||
seed: int = Field(..., description="Seed for deterministic sampling")
|
||||
remove_background_noise: bool = Field(..., description="Remove background noise from input audio")
|
||||
|
||||
|
||||
class DialogueInput(BaseModel):
|
||||
text: str = Field(..., description="Text content to convert to speech")
|
||||
voice_id: str = Field(..., description="Voice identifier for this dialogue segment")
|
||||
|
||||
|
||||
class DialogueSettings(BaseModel):
|
||||
stability: float | None = Field(None, description="Voice stability (0-1)")
|
||||
|
||||
|
||||
class TextToDialogueRequest(BaseModel):
|
||||
inputs: list[DialogueInput] = Field(..., description="List of dialogue segments")
|
||||
model_id: str = Field(..., description="Model ID for dialogue generation")
|
||||
language_code: str | None = Field(None, description="ISO-639-1 language code")
|
||||
settings: DialogueSettings | None = Field(None, description="Voice settings")
|
||||
seed: int | None = Field(None, description="Seed for deterministic sampling")
|
||||
apply_text_normalization: str | None = Field(None, description="Text normalization mode: auto, on, off")
|
||||
@ -1,924 +0,0 @@
|
||||
import json
|
||||
import uuid
|
||||
|
||||
from typing_extensions import override
|
||||
|
||||
from comfy_api.latest import IO, ComfyExtension, Input
|
||||
from comfy_api_nodes.apis.elevenlabs import (
|
||||
AddVoiceRequest,
|
||||
AddVoiceResponse,
|
||||
DialogueInput,
|
||||
DialogueSettings,
|
||||
SpeechToSpeechRequest,
|
||||
SpeechToTextRequest,
|
||||
SpeechToTextResponse,
|
||||
TextToDialogueRequest,
|
||||
TextToSoundEffectsRequest,
|
||||
TextToSpeechRequest,
|
||||
TextToSpeechVoiceSettings,
|
||||
)
|
||||
from comfy_api_nodes.util import (
|
||||
ApiEndpoint,
|
||||
audio_bytes_to_audio_input,
|
||||
audio_ndarray_to_bytesio,
|
||||
audio_tensor_to_contiguous_ndarray,
|
||||
sync_op,
|
||||
sync_op_raw,
|
||||
upload_audio_to_comfyapi,
|
||||
validate_string,
|
||||
)
|
||||
|
||||
ELEVENLABS_MUSIC_SECTIONS = "ELEVENLABS_MUSIC_SECTIONS" # Custom type for music sections
|
||||
ELEVENLABS_COMPOSITION_PLAN = "ELEVENLABS_COMPOSITION_PLAN" # Custom type for composition plan
|
||||
ELEVENLABS_VOICE = "ELEVENLABS_VOICE" # Custom type for voice selection
|
||||
|
||||
# Predefined ElevenLabs voices: (voice_id, display_name, gender, accent)
|
||||
ELEVENLABS_VOICES = [
|
||||
("CwhRBWXzGAHq8TQ4Fs17", "Roger", "male", "american"),
|
||||
("EXAVITQu4vr4xnSDxMaL", "Sarah", "female", "american"),
|
||||
("FGY2WhTYpPnrIDTdsKH5", "Laura", "female", "american"),
|
||||
("IKne3meq5aSn9XLyUdCD", "Charlie", "male", "australian"),
|
||||
("JBFqnCBsd6RMkjVDRZzb", "George", "male", "british"),
|
||||
("N2lVS1w4EtoT3dr4eOWO", "Callum", "male", "american"),
|
||||
("SAz9YHcvj6GT2YYXdXww", "River", "neutral", "american"),
|
||||
("SOYHLrjzK2X1ezoPC6cr", "Harry", "male", "american"),
|
||||
("TX3LPaxmHKxFdv7VOQHJ", "Liam", "male", "american"),
|
||||
("Xb7hH8MSUJpSbSDYk0k2", "Alice", "female", "british"),
|
||||
("XrExE9yKIg1WjnnlVkGX", "Matilda", "female", "american"),
|
||||
("bIHbv24MWmeRgasZH58o", "Will", "male", "american"),
|
||||
("cgSgspJ2msm6clMCkdW9", "Jessica", "female", "american"),
|
||||
("cjVigY5qzO86Huf0OWal", "Eric", "male", "american"),
|
||||
("hpp4J3VqNfWAUOO0d1Us", "Bella", "female", "american"),
|
||||
("iP95p4xoKVk53GoZ742B", "Chris", "male", "american"),
|
||||
("nPczCjzI2devNBz1zQrb", "Brian", "male", "american"),
|
||||
("onwK4e9ZLuTAKqWW03F9", "Daniel", "male", "british"),
|
||||
("pFZP5JQG7iQjIQuC4Bku", "Lily", "female", "british"),
|
||||
("pNInz6obpgDQGcFmaJgB", "Adam", "male", "american"),
|
||||
("pqHfZKP75CvOlQylNhV4", "Bill", "male", "american"),
|
||||
]
|
||||
|
||||
ELEVENLABS_VOICE_OPTIONS = [f"{name} ({gender}, {accent})" for _, name, gender, accent in ELEVENLABS_VOICES]
|
||||
ELEVENLABS_VOICE_MAP = {
|
||||
f"{name} ({gender}, {accent})": voice_id for voice_id, name, gender, accent in ELEVENLABS_VOICES
|
||||
}
|
||||
|
||||
|
||||
class ElevenLabsSpeechToText(IO.ComfyNode):
|
||||
@classmethod
|
||||
def define_schema(cls) -> IO.Schema:
|
||||
return IO.Schema(
|
||||
node_id="ElevenLabsSpeechToText",
|
||||
display_name="ElevenLabs Speech to Text",
|
||||
category="api node/audio/ElevenLabs",
|
||||
description="Transcribe audio to text. "
|
||||
"Supports automatic language detection, speaker diarization, and audio event tagging.",
|
||||
inputs=[
|
||||
IO.Audio.Input(
|
||||
"audio",
|
||||
tooltip="Audio to transcribe.",
|
||||
),
|
||||
IO.DynamicCombo.Input(
|
||||
"model",
|
||||
options=[
|
||||
IO.DynamicCombo.Option(
|
||||
"scribe_v2",
|
||||
[
|
||||
IO.Boolean.Input(
|
||||
"tag_audio_events",
|
||||
default=False,
|
||||
tooltip="Annotate sounds like (laughter), (music), etc. in transcript.",
|
||||
),
|
||||
IO.Boolean.Input(
|
||||
"diarize",
|
||||
default=False,
|
||||
tooltip="Annotate which speaker is talking.",
|
||||
),
|
||||
IO.Float.Input(
|
||||
"diarization_threshold",
|
||||
default=0.22,
|
||||
min=0.1,
|
||||
max=0.4,
|
||||
step=0.01,
|
||||
display_mode=IO.NumberDisplay.slider,
|
||||
tooltip="Speaker separation sensitivity. "
|
||||
"Lower values are more sensitive to speaker changes.",
|
||||
),
|
||||
IO.Float.Input(
|
||||
"temperature",
|
||||
default=0.0,
|
||||
min=0.0,
|
||||
max=2.0,
|
||||
step=0.01,
|
||||
display_mode=IO.NumberDisplay.slider,
|
||||
tooltip="Randomness control. "
|
||||
"0.0 uses model default. Higher values increase randomness.",
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"timestamps_granularity",
|
||||
options=["word", "character", "none"],
|
||||
default="word",
|
||||
tooltip="Timing precision for transcript words.",
|
||||
),
|
||||
],
|
||||
),
|
||||
],
|
||||
tooltip="Model to use for transcription.",
|
||||
),
|
||||
IO.String.Input(
|
||||
"language_code",
|
||||
default="",
|
||||
tooltip="ISO-639-1 or ISO-639-3 language code (e.g., 'en', 'es', 'fra'). "
|
||||
"Leave empty for automatic detection.",
|
||||
),
|
||||
IO.Int.Input(
|
||||
"num_speakers",
|
||||
default=0,
|
||||
min=0,
|
||||
max=32,
|
||||
display_mode=IO.NumberDisplay.slider,
|
||||
tooltip="Maximum number of speakers to predict. Set to 0 for automatic detection.",
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=1,
|
||||
min=0,
|
||||
max=2147483647,
|
||||
tooltip="Seed for reproducibility (determinism not guaranteed).",
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.String.Output(display_name="text"),
|
||||
IO.String.Output(display_name="language_code"),
|
||||
IO.String.Output(display_name="words_json"),
|
||||
],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
expr="""{"type":"usd","usd":0.0073,"format":{"approximate":true,"suffix":"/minute"}}""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
audio: Input.Audio,
|
||||
model: dict,
|
||||
language_code: str,
|
||||
num_speakers: int,
|
||||
seed: int,
|
||||
) -> IO.NodeOutput:
|
||||
if model["diarize"] and num_speakers:
|
||||
raise ValueError(
|
||||
"Number of speakers cannot be specified when diarization is enabled. "
|
||||
"Either disable diarization or set num_speakers to 0."
|
||||
)
|
||||
request = SpeechToTextRequest(
|
||||
model_id=model["model"],
|
||||
cloud_storage_url=await upload_audio_to_comfyapi(
|
||||
cls, audio, container_format="mp4", codec_name="aac", mime_type="audio/mp4"
|
||||
),
|
||||
language_code=language_code if language_code.strip() else None,
|
||||
tag_audio_events=model["tag_audio_events"],
|
||||
num_speakers=num_speakers if num_speakers > 0 else None,
|
||||
timestamps_granularity=model["timestamps_granularity"],
|
||||
diarize=model["diarize"],
|
||||
diarization_threshold=model["diarization_threshold"] if model["diarize"] else None,
|
||||
seed=seed,
|
||||
temperature=model["temperature"],
|
||||
)
|
||||
response = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(path="/proxy/elevenlabs/v1/speech-to-text", method="POST"),
|
||||
response_model=SpeechToTextResponse,
|
||||
data=request,
|
||||
content_type="multipart/form-data",
|
||||
)
|
||||
words_json = json.dumps(
|
||||
[w.model_dump(exclude_none=True) for w in response.words] if response.words else [],
|
||||
indent=2,
|
||||
)
|
||||
return IO.NodeOutput(response.text, response.language_code, words_json)
|
||||
|
||||
|
||||
class ElevenLabsVoiceSelector(IO.ComfyNode):
|
||||
@classmethod
|
||||
def define_schema(cls) -> IO.Schema:
|
||||
return IO.Schema(
|
||||
node_id="ElevenLabsVoiceSelector",
|
||||
display_name="ElevenLabs Voice Selector",
|
||||
category="api node/audio/ElevenLabs",
|
||||
description="Select a predefined ElevenLabs voice for text-to-speech generation.",
|
||||
inputs=[
|
||||
IO.Combo.Input(
|
||||
"voice",
|
||||
options=ELEVENLABS_VOICE_OPTIONS,
|
||||
tooltip="Choose a voice from the predefined ElevenLabs voices.",
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.Custom(ELEVENLABS_VOICE).Output(display_name="voice"),
|
||||
],
|
||||
is_api_node=False,
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def execute(cls, voice: str) -> IO.NodeOutput:
|
||||
voice_id = ELEVENLABS_VOICE_MAP.get(voice)
|
||||
if not voice_id:
|
||||
raise ValueError(f"Unknown voice: {voice}")
|
||||
return IO.NodeOutput(voice_id)
|
||||
|
||||
|
||||
class ElevenLabsTextToSpeech(IO.ComfyNode):
|
||||
@classmethod
|
||||
def define_schema(cls) -> IO.Schema:
|
||||
return IO.Schema(
|
||||
node_id="ElevenLabsTextToSpeech",
|
||||
display_name="ElevenLabs Text to Speech",
|
||||
category="api node/audio/ElevenLabs",
|
||||
description="Convert text to speech.",
|
||||
inputs=[
|
||||
IO.Custom(ELEVENLABS_VOICE).Input(
|
||||
"voice",
|
||||
tooltip="Voice to use for speech synthesis. Connect from Voice Selector or Instant Voice Clone.",
|
||||
),
|
||||
IO.String.Input(
|
||||
"text",
|
||||
multiline=True,
|
||||
default="",
|
||||
tooltip="The text to convert to speech.",
|
||||
),
|
||||
IO.Float.Input(
|
||||
"stability",
|
||||
default=0.5,
|
||||
min=0.0,
|
||||
max=1.0,
|
||||
step=0.01,
|
||||
display_mode=IO.NumberDisplay.slider,
|
||||
tooltip="Voice stability. Lower values give broader emotional range, "
|
||||
"higher values produce more consistent but potentially monotonous speech.",
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"apply_text_normalization",
|
||||
options=["auto", "on", "off"],
|
||||
tooltip="Text normalization mode. 'auto' lets the system decide, "
|
||||
"'on' always applies normalization, 'off' skips it.",
|
||||
),
|
||||
IO.DynamicCombo.Input(
|
||||
"model",
|
||||
options=[
|
||||
IO.DynamicCombo.Option(
|
||||
"eleven_multilingual_v2",
|
||||
[
|
||||
IO.Float.Input(
|
||||
"speed",
|
||||
default=1.0,
|
||||
min=0.7,
|
||||
max=1.3,
|
||||
step=0.01,
|
||||
display_mode=IO.NumberDisplay.slider,
|
||||
tooltip="Speech speed. 1.0 is normal, <1.0 slower, >1.0 faster.",
|
||||
),
|
||||
IO.Float.Input(
|
||||
"similarity_boost",
|
||||
default=0.75,
|
||||
min=0.0,
|
||||
max=1.0,
|
||||
step=0.01,
|
||||
display_mode=IO.NumberDisplay.slider,
|
||||
tooltip="Similarity boost. Higher values make the voice more similar to the original.",
|
||||
),
|
||||
IO.Boolean.Input(
|
||||
"use_speaker_boost",
|
||||
default=False,
|
||||
tooltip="Boost similarity to the original speaker voice.",
|
||||
),
|
||||
IO.Float.Input(
|
||||
"style",
|
||||
default=0.0,
|
||||
min=0.0,
|
||||
max=0.2,
|
||||
step=0.01,
|
||||
display_mode=IO.NumberDisplay.slider,
|
||||
tooltip="Style exaggeration. Higher values increase stylistic expression "
|
||||
"but may reduce stability.",
|
||||
),
|
||||
],
|
||||
),
|
||||
IO.DynamicCombo.Option(
|
||||
"eleven_v3",
|
||||
[
|
||||
IO.Float.Input(
|
||||
"speed",
|
||||
default=1.0,
|
||||
min=0.7,
|
||||
max=1.3,
|
||||
step=0.01,
|
||||
display_mode=IO.NumberDisplay.slider,
|
||||
tooltip="Speech speed. 1.0 is normal, <1.0 slower, >1.0 faster.",
|
||||
),
|
||||
IO.Float.Input(
|
||||
"similarity_boost",
|
||||
default=0.75,
|
||||
min=0.0,
|
||||
max=1.0,
|
||||
step=0.01,
|
||||
display_mode=IO.NumberDisplay.slider,
|
||||
tooltip="Similarity boost. Higher values make the voice more similar to the original.",
|
||||
),
|
||||
],
|
||||
),
|
||||
],
|
||||
tooltip="Model to use for text-to-speech.",
|
||||
),
|
||||
IO.String.Input(
|
||||
"language_code",
|
||||
default="",
|
||||
tooltip="ISO-639-1 or ISO-639-3 language code (e.g., 'en', 'es', 'fra'). "
|
||||
"Leave empty for automatic detection.",
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=1,
|
||||
min=0,
|
||||
max=2147483647,
|
||||
tooltip="Seed for reproducibility (determinism not guaranteed).",
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"output_format",
|
||||
options=["mp3_44100_192", "opus_48000_192"],
|
||||
tooltip="Audio output format.",
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.Audio.Output(),
|
||||
],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
expr="""{"type":"usd","usd":0.24,"format":{"approximate":true,"suffix":"/1K chars"}}""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
voice: str,
|
||||
text: str,
|
||||
stability: float,
|
||||
apply_text_normalization: str,
|
||||
model: dict,
|
||||
language_code: str,
|
||||
seed: int,
|
||||
output_format: str,
|
||||
) -> IO.NodeOutput:
|
||||
validate_string(text, min_length=1)
|
||||
request = TextToSpeechRequest(
|
||||
text=text,
|
||||
model_id=model["model"],
|
||||
language_code=language_code if language_code.strip() else None,
|
||||
voice_settings=TextToSpeechVoiceSettings(
|
||||
stability=stability,
|
||||
similarity_boost=model["similarity_boost"],
|
||||
speed=model["speed"],
|
||||
use_speaker_boost=model.get("use_speaker_boost", None),
|
||||
style=model.get("style", None),
|
||||
),
|
||||
seed=seed,
|
||||
apply_text_normalization=apply_text_normalization,
|
||||
)
|
||||
response = await sync_op_raw(
|
||||
cls,
|
||||
ApiEndpoint(
|
||||
path=f"/proxy/elevenlabs/v1/text-to-speech/{voice}",
|
||||
method="POST",
|
||||
query_params={"output_format": output_format},
|
||||
),
|
||||
data=request,
|
||||
as_binary=True,
|
||||
)
|
||||
return IO.NodeOutput(audio_bytes_to_audio_input(response))
|
||||
|
||||
|
||||
class ElevenLabsAudioIsolation(IO.ComfyNode):
|
||||
@classmethod
|
||||
def define_schema(cls) -> IO.Schema:
|
||||
return IO.Schema(
|
||||
node_id="ElevenLabsAudioIsolation",
|
||||
display_name="ElevenLabs Voice Isolation",
|
||||
category="api node/audio/ElevenLabs",
|
||||
description="Remove background noise from audio, isolating vocals or speech.",
|
||||
inputs=[
|
||||
IO.Audio.Input(
|
||||
"audio",
|
||||
tooltip="Audio to process for background noise removal.",
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.Audio.Output(),
|
||||
],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
expr="""{"type":"usd","usd":0.24,"format":{"approximate":true,"suffix":"/minute"}}""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
audio: Input.Audio,
|
||||
) -> IO.NodeOutput:
|
||||
audio_data_np = audio_tensor_to_contiguous_ndarray(audio["waveform"])
|
||||
audio_bytes_io = audio_ndarray_to_bytesio(audio_data_np, audio["sample_rate"], "mp4", "aac")
|
||||
response = await sync_op_raw(
|
||||
cls,
|
||||
ApiEndpoint(path="/proxy/elevenlabs/v1/audio-isolation", method="POST"),
|
||||
files={"audio": ("audio.mp4", audio_bytes_io, "audio/mp4")},
|
||||
content_type="multipart/form-data",
|
||||
as_binary=True,
|
||||
)
|
||||
return IO.NodeOutput(audio_bytes_to_audio_input(response))
|
||||
|
||||
|
||||
class ElevenLabsTextToSoundEffects(IO.ComfyNode):
|
||||
@classmethod
|
||||
def define_schema(cls) -> IO.Schema:
|
||||
return IO.Schema(
|
||||
node_id="ElevenLabsTextToSoundEffects",
|
||||
display_name="ElevenLabs Text to Sound Effects",
|
||||
category="api node/audio/ElevenLabs",
|
||||
description="Generate sound effects from text descriptions.",
|
||||
inputs=[
|
||||
IO.String.Input(
|
||||
"text",
|
||||
multiline=True,
|
||||
default="",
|
||||
tooltip="Text description of the sound effect to generate.",
|
||||
),
|
||||
IO.DynamicCombo.Input(
|
||||
"model",
|
||||
options=[
|
||||
IO.DynamicCombo.Option(
|
||||
"eleven_sfx_v2",
|
||||
[
|
||||
IO.Float.Input(
|
||||
"duration",
|
||||
default=5.0,
|
||||
min=0.5,
|
||||
max=30.0,
|
||||
step=0.1,
|
||||
display_mode=IO.NumberDisplay.slider,
|
||||
tooltip="Duration of generated sound in seconds.",
|
||||
),
|
||||
IO.Boolean.Input(
|
||||
"loop",
|
||||
default=False,
|
||||
tooltip="Create a smoothly looping sound effect.",
|
||||
),
|
||||
IO.Float.Input(
|
||||
"prompt_influence",
|
||||
default=0.3,
|
||||
min=0.0,
|
||||
max=1.0,
|
||||
step=0.01,
|
||||
display_mode=IO.NumberDisplay.slider,
|
||||
tooltip="How closely generation follows the prompt. "
|
||||
"Higher values make the sound follow the text more closely.",
|
||||
),
|
||||
],
|
||||
),
|
||||
],
|
||||
tooltip="Model to use for sound effect generation.",
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"output_format",
|
||||
options=["mp3_44100_192", "opus_48000_192"],
|
||||
tooltip="Audio output format.",
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.Audio.Output(),
|
||||
],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
expr="""{"type":"usd","usd":0.14,"format":{"approximate":true,"suffix":"/minute"}}""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
text: str,
|
||||
model: dict,
|
||||
output_format: str,
|
||||
) -> IO.NodeOutput:
|
||||
validate_string(text, min_length=1)
|
||||
response = await sync_op_raw(
|
||||
cls,
|
||||
ApiEndpoint(
|
||||
path="/proxy/elevenlabs/v1/sound-generation",
|
||||
method="POST",
|
||||
query_params={"output_format": output_format},
|
||||
),
|
||||
data=TextToSoundEffectsRequest(
|
||||
text=text,
|
||||
duration_seconds=model["duration"],
|
||||
prompt_influence=model["prompt_influence"],
|
||||
loop=model.get("loop", None),
|
||||
),
|
||||
as_binary=True,
|
||||
)
|
||||
return IO.NodeOutput(audio_bytes_to_audio_input(response))
|
||||
|
||||
|
||||
class ElevenLabsInstantVoiceClone(IO.ComfyNode):
|
||||
@classmethod
|
||||
def define_schema(cls) -> IO.Schema:
|
||||
return IO.Schema(
|
||||
node_id="ElevenLabsInstantVoiceClone",
|
||||
display_name="ElevenLabs Instant Voice Clone",
|
||||
category="api node/audio/ElevenLabs",
|
||||
description="Create a cloned voice from audio samples. "
|
||||
"Provide 1-8 audio recordings of the voice to clone.",
|
||||
inputs=[
|
||||
IO.Autogrow.Input(
|
||||
"files",
|
||||
template=IO.Autogrow.TemplatePrefix(
|
||||
IO.Audio.Input("audio"),
|
||||
prefix="audio",
|
||||
min=1,
|
||||
max=8,
|
||||
),
|
||||
tooltip="Audio recordings for voice cloning.",
|
||||
),
|
||||
IO.Boolean.Input(
|
||||
"remove_background_noise",
|
||||
default=False,
|
||||
tooltip="Remove background noise from voice samples using audio isolation.",
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.Custom(ELEVENLABS_VOICE).Output(display_name="voice"),
|
||||
],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(expr="""{"type":"usd","usd":0.15}"""),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
files: IO.Autogrow.Type,
|
||||
remove_background_noise: bool,
|
||||
) -> IO.NodeOutput:
|
||||
file_tuples: list[tuple[str, tuple[str, bytes, str]]] = []
|
||||
for key in files:
|
||||
audio = files[key]
|
||||
sample_rate: int = audio["sample_rate"]
|
||||
waveform = audio["waveform"]
|
||||
audio_data_np = audio_tensor_to_contiguous_ndarray(waveform)
|
||||
audio_bytes_io = audio_ndarray_to_bytesio(audio_data_np, sample_rate, "mp4", "aac")
|
||||
file_tuples.append(("files", (f"{key}.mp4", audio_bytes_io.getvalue(), "audio/mp4")))
|
||||
|
||||
response = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(path="/proxy/elevenlabs/v1/voices/add", method="POST"),
|
||||
response_model=AddVoiceResponse,
|
||||
data=AddVoiceRequest(
|
||||
name=str(uuid.uuid4()),
|
||||
remove_background_noise=remove_background_noise,
|
||||
),
|
||||
files=file_tuples,
|
||||
content_type="multipart/form-data",
|
||||
)
|
||||
return IO.NodeOutput(response.voice_id)
|
||||
|
||||
|
||||
ELEVENLABS_STS_VOICE_SETTINGS = [
|
||||
IO.Float.Input(
|
||||
"speed",
|
||||
default=1.0,
|
||||
min=0.7,
|
||||
max=1.3,
|
||||
step=0.01,
|
||||
display_mode=IO.NumberDisplay.slider,
|
||||
tooltip="Speech speed. 1.0 is normal, <1.0 slower, >1.0 faster.",
|
||||
),
|
||||
IO.Float.Input(
|
||||
"similarity_boost",
|
||||
default=0.75,
|
||||
min=0.0,
|
||||
max=1.0,
|
||||
step=0.01,
|
||||
display_mode=IO.NumberDisplay.slider,
|
||||
tooltip="Similarity boost. Higher values make the voice more similar to the original.",
|
||||
),
|
||||
IO.Boolean.Input(
|
||||
"use_speaker_boost",
|
||||
default=False,
|
||||
tooltip="Boost similarity to the original speaker voice.",
|
||||
),
|
||||
IO.Float.Input(
|
||||
"style",
|
||||
default=0.0,
|
||||
min=0.0,
|
||||
max=0.2,
|
||||
step=0.01,
|
||||
display_mode=IO.NumberDisplay.slider,
|
||||
tooltip="Style exaggeration. Higher values increase stylistic expression but may reduce stability.",
|
||||
),
|
||||
]
|
||||
|
||||
|
||||
class ElevenLabsSpeechToSpeech(IO.ComfyNode):
|
||||
@classmethod
|
||||
def define_schema(cls) -> IO.Schema:
|
||||
return IO.Schema(
|
||||
node_id="ElevenLabsSpeechToSpeech",
|
||||
display_name="ElevenLabs Speech to Speech",
|
||||
category="api node/audio/ElevenLabs",
|
||||
description="Transform speech from one voice to another while preserving the original content and emotion.",
|
||||
inputs=[
|
||||
IO.Custom(ELEVENLABS_VOICE).Input(
|
||||
"voice",
|
||||
tooltip="Target voice for the transformation. "
|
||||
"Connect from Voice Selector or Instant Voice Clone.",
|
||||
),
|
||||
IO.Audio.Input(
|
||||
"audio",
|
||||
tooltip="Source audio to transform.",
|
||||
),
|
||||
IO.Float.Input(
|
||||
"stability",
|
||||
default=0.5,
|
||||
min=0.0,
|
||||
max=1.0,
|
||||
step=0.01,
|
||||
display_mode=IO.NumberDisplay.slider,
|
||||
tooltip="Voice stability. Lower values give broader emotional range, "
|
||||
"higher values produce more consistent but potentially monotonous speech.",
|
||||
),
|
||||
IO.DynamicCombo.Input(
|
||||
"model",
|
||||
options=[
|
||||
IO.DynamicCombo.Option(
|
||||
"eleven_multilingual_sts_v2",
|
||||
ELEVENLABS_STS_VOICE_SETTINGS,
|
||||
),
|
||||
IO.DynamicCombo.Option(
|
||||
"eleven_english_sts_v2",
|
||||
ELEVENLABS_STS_VOICE_SETTINGS,
|
||||
),
|
||||
],
|
||||
tooltip="Model to use for speech-to-speech transformation.",
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"output_format",
|
||||
options=["mp3_44100_192", "opus_48000_192"],
|
||||
tooltip="Audio output format.",
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=0,
|
||||
min=0,
|
||||
max=4294967295,
|
||||
tooltip="Seed for reproducibility.",
|
||||
),
|
||||
IO.Boolean.Input(
|
||||
"remove_background_noise",
|
||||
default=False,
|
||||
tooltip="Remove background noise from input audio using audio isolation.",
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.Audio.Output(),
|
||||
],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
expr="""{"type":"usd","usd":0.24,"format":{"approximate":true,"suffix":"/minute"}}""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
voice: str,
|
||||
audio: Input.Audio,
|
||||
stability: float,
|
||||
model: dict,
|
||||
output_format: str,
|
||||
seed: int,
|
||||
remove_background_noise: bool,
|
||||
) -> IO.NodeOutput:
|
||||
audio_data_np = audio_tensor_to_contiguous_ndarray(audio["waveform"])
|
||||
audio_bytes_io = audio_ndarray_to_bytesio(audio_data_np, audio["sample_rate"], "mp4", "aac")
|
||||
voice_settings = TextToSpeechVoiceSettings(
|
||||
stability=stability,
|
||||
similarity_boost=model["similarity_boost"],
|
||||
style=model["style"],
|
||||
use_speaker_boost=model["use_speaker_boost"],
|
||||
speed=model["speed"],
|
||||
)
|
||||
response = await sync_op_raw(
|
||||
cls,
|
||||
ApiEndpoint(
|
||||
path=f"/proxy/elevenlabs/v1/speech-to-speech/{voice}",
|
||||
method="POST",
|
||||
query_params={"output_format": output_format},
|
||||
),
|
||||
data=SpeechToSpeechRequest(
|
||||
model_id=model["model"],
|
||||
voice_settings=voice_settings.model_dump_json(exclude_none=True),
|
||||
seed=seed,
|
||||
remove_background_noise=remove_background_noise,
|
||||
),
|
||||
files={"audio": ("audio.mp4", audio_bytes_io.getvalue(), "audio/mp4")},
|
||||
content_type="multipart/form-data",
|
||||
as_binary=True,
|
||||
)
|
||||
return IO.NodeOutput(audio_bytes_to_audio_input(response))
|
||||
|
||||
|
||||
def _generate_dialogue_inputs(count: int) -> list:
|
||||
"""Generate input widgets for a given number of dialogue entries."""
|
||||
inputs = []
|
||||
for i in range(1, count + 1):
|
||||
inputs.extend(
|
||||
[
|
||||
IO.String.Input(
|
||||
f"text{i}",
|
||||
multiline=True,
|
||||
default="",
|
||||
tooltip=f"Text content for dialogue entry {i}.",
|
||||
),
|
||||
IO.Custom(ELEVENLABS_VOICE).Input(
|
||||
f"voice{i}",
|
||||
tooltip=f"Voice for dialogue entry {i}. Connect from Voice Selector or Instant Voice Clone.",
|
||||
),
|
||||
]
|
||||
)
|
||||
return inputs
|
||||
|
||||
|
||||
class ElevenLabsTextToDialogue(IO.ComfyNode):
|
||||
@classmethod
|
||||
def define_schema(cls) -> IO.Schema:
|
||||
return IO.Schema(
|
||||
node_id="ElevenLabsTextToDialogue",
|
||||
display_name="ElevenLabs Text to Dialogue",
|
||||
category="api node/audio/ElevenLabs",
|
||||
description="Generate multi-speaker dialogue from text. Each dialogue entry has its own text and voice.",
|
||||
inputs=[
|
||||
IO.Float.Input(
|
||||
"stability",
|
||||
default=0.5,
|
||||
min=0.0,
|
||||
max=1.0,
|
||||
step=0.5,
|
||||
display_mode=IO.NumberDisplay.slider,
|
||||
tooltip="Voice stability. Lower values give broader emotional range, "
|
||||
"higher values produce more consistent but potentially monotonous speech.",
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"apply_text_normalization",
|
||||
options=["auto", "on", "off"],
|
||||
tooltip="Text normalization mode. 'auto' lets the system decide, "
|
||||
"'on' always applies normalization, 'off' skips it.",
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"model",
|
||||
options=["eleven_v3"],
|
||||
tooltip="Model to use for dialogue generation.",
|
||||
),
|
||||
IO.DynamicCombo.Input(
|
||||
"inputs",
|
||||
options=[
|
||||
IO.DynamicCombo.Option("1", _generate_dialogue_inputs(1)),
|
||||
IO.DynamicCombo.Option("2", _generate_dialogue_inputs(2)),
|
||||
IO.DynamicCombo.Option("3", _generate_dialogue_inputs(3)),
|
||||
IO.DynamicCombo.Option("4", _generate_dialogue_inputs(4)),
|
||||
IO.DynamicCombo.Option("5", _generate_dialogue_inputs(5)),
|
||||
IO.DynamicCombo.Option("6", _generate_dialogue_inputs(6)),
|
||||
IO.DynamicCombo.Option("7", _generate_dialogue_inputs(7)),
|
||||
IO.DynamicCombo.Option("8", _generate_dialogue_inputs(8)),
|
||||
IO.DynamicCombo.Option("9", _generate_dialogue_inputs(9)),
|
||||
IO.DynamicCombo.Option("10", _generate_dialogue_inputs(10)),
|
||||
],
|
||||
tooltip="Number of dialogue entries.",
|
||||
),
|
||||
IO.String.Input(
|
||||
"language_code",
|
||||
default="",
|
||||
tooltip="ISO-639-1 or ISO-639-3 language code (e.g., 'en', 'es', 'fra'). "
|
||||
"Leave empty for automatic detection.",
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=1,
|
||||
min=0,
|
||||
max=4294967295,
|
||||
tooltip="Seed for reproducibility.",
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"output_format",
|
||||
options=["mp3_44100_192", "opus_48000_192"],
|
||||
tooltip="Audio output format.",
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.Audio.Output(),
|
||||
],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
expr="""{"type":"usd","usd":0.24,"format":{"approximate":true,"suffix":"/1K chars"}}""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
stability: float,
|
||||
apply_text_normalization: str,
|
||||
model: str,
|
||||
inputs: dict,
|
||||
language_code: str,
|
||||
seed: int,
|
||||
output_format: str,
|
||||
) -> IO.NodeOutput:
|
||||
num_entries = int(inputs["inputs"])
|
||||
dialogue_inputs: list[DialogueInput] = []
|
||||
for i in range(1, num_entries + 1):
|
||||
text = inputs[f"text{i}"]
|
||||
voice_id = inputs[f"voice{i}"]
|
||||
validate_string(text, min_length=1)
|
||||
dialogue_inputs.append(DialogueInput(text=text, voice_id=voice_id))
|
||||
request = TextToDialogueRequest(
|
||||
inputs=dialogue_inputs,
|
||||
model_id=model,
|
||||
language_code=language_code if language_code.strip() else None,
|
||||
settings=DialogueSettings(stability=stability),
|
||||
seed=seed,
|
||||
apply_text_normalization=apply_text_normalization,
|
||||
)
|
||||
response = await sync_op_raw(
|
||||
cls,
|
||||
ApiEndpoint(
|
||||
path="/proxy/elevenlabs/v1/text-to-dialogue",
|
||||
method="POST",
|
||||
query_params={"output_format": output_format},
|
||||
),
|
||||
data=request,
|
||||
as_binary=True,
|
||||
)
|
||||
return IO.NodeOutput(audio_bytes_to_audio_input(response))
|
||||
|
||||
|
||||
class ElevenLabsExtension(ComfyExtension):
|
||||
@override
|
||||
async def get_node_list(self) -> list[type[IO.ComfyNode]]:
|
||||
return [
|
||||
ElevenLabsSpeechToText,
|
||||
ElevenLabsVoiceSelector,
|
||||
ElevenLabsTextToSpeech,
|
||||
ElevenLabsAudioIsolation,
|
||||
ElevenLabsTextToSoundEffects,
|
||||
ElevenLabsInstantVoiceClone,
|
||||
ElevenLabsSpeechToSpeech,
|
||||
ElevenLabsTextToDialogue,
|
||||
]
|
||||
|
||||
|
||||
async def comfy_entrypoint() -> ElevenLabsExtension:
|
||||
return ElevenLabsExtension()
|
||||
@ -9,8 +9,6 @@ from .client import (
|
||||
from .conversions import (
|
||||
audio_bytes_to_audio_input,
|
||||
audio_input_to_mp3,
|
||||
audio_ndarray_to_bytesio,
|
||||
audio_tensor_to_contiguous_ndarray,
|
||||
audio_to_base64_string,
|
||||
bytesio_to_image_tensor,
|
||||
convert_mask_to_image,
|
||||
@ -80,8 +78,6 @@ __all__ = [
|
||||
# Conversions
|
||||
"audio_bytes_to_audio_input",
|
||||
"audio_input_to_mp3",
|
||||
"audio_ndarray_to_bytesio",
|
||||
"audio_tensor_to_contiguous_ndarray",
|
||||
"audio_to_base64_string",
|
||||
"bytesio_to_image_tensor",
|
||||
"convert_mask_to_image",
|
||||
|
||||
@ -10,7 +10,6 @@ class Canny(io.ComfyNode):
|
||||
def define_schema(cls):
|
||||
return io.Schema(
|
||||
node_id="Canny",
|
||||
display_name="Canny",
|
||||
search_aliases=["edge detection", "outline", "contour detection", "line art"],
|
||||
category="image/preprocessors",
|
||||
essentials_category="Image Tools",
|
||||
|
||||
@ -1,895 +0,0 @@
|
||||
import os
|
||||
import sys
|
||||
import re
|
||||
import logging
|
||||
import ctypes.util
|
||||
import importlib.util
|
||||
from typing import TypedDict
|
||||
|
||||
import numpy as np
|
||||
import torch
|
||||
|
||||
import nodes
|
||||
from comfy_api.latest import ComfyExtension, io, ui
|
||||
from typing_extensions import override
|
||||
from utils.install_util import get_missing_requirements_message
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
def _check_opengl_availability():
|
||||
"""Early check for OpenGL availability. Raises RuntimeError if unlikely to work."""
|
||||
logger.debug("_check_opengl_availability: starting")
|
||||
missing = []
|
||||
|
||||
# Check Python packages (using find_spec to avoid importing)
|
||||
logger.debug("_check_opengl_availability: checking for glfw package")
|
||||
if importlib.util.find_spec("glfw") is None:
|
||||
missing.append("glfw")
|
||||
|
||||
logger.debug("_check_opengl_availability: checking for OpenGL package")
|
||||
if importlib.util.find_spec("OpenGL") is None:
|
||||
missing.append("PyOpenGL")
|
||||
|
||||
if missing:
|
||||
raise RuntimeError(
|
||||
f"OpenGL dependencies not available.\n{get_missing_requirements_message()}\n"
|
||||
)
|
||||
|
||||
# On Linux without display, check if headless backends are available
|
||||
logger.debug(f"_check_opengl_availability: platform={sys.platform}")
|
||||
if sys.platform.startswith("linux"):
|
||||
has_display = os.environ.get("DISPLAY") or os.environ.get("WAYLAND_DISPLAY")
|
||||
logger.debug(f"_check_opengl_availability: has_display={bool(has_display)}")
|
||||
if not has_display:
|
||||
# Check for EGL or OSMesa libraries
|
||||
logger.debug("_check_opengl_availability: checking for EGL library")
|
||||
has_egl = ctypes.util.find_library("EGL")
|
||||
logger.debug("_check_opengl_availability: checking for OSMesa library")
|
||||
has_osmesa = ctypes.util.find_library("OSMesa")
|
||||
|
||||
# Error disabled for CI as it fails this check
|
||||
# if not has_egl and not has_osmesa:
|
||||
# raise RuntimeError(
|
||||
# "GLSL Shader node: No display and no headless backend (EGL/OSMesa) found.\n"
|
||||
# "See error below for installation instructions."
|
||||
# )
|
||||
logger.debug(f"Headless mode: EGL={'yes' if has_egl else 'no'}, OSMesa={'yes' if has_osmesa else 'no'}")
|
||||
|
||||
logger.debug("_check_opengl_availability: completed")
|
||||
|
||||
|
||||
# Run early check at import time
|
||||
logger.debug("nodes_glsl: running _check_opengl_availability at import time")
|
||||
_check_opengl_availability()
|
||||
|
||||
# OpenGL modules - initialized lazily when context is created
|
||||
gl = None
|
||||
glfw = None
|
||||
EGL = None
|
||||
|
||||
|
||||
def _import_opengl():
|
||||
"""Import OpenGL module. Called after context is created."""
|
||||
global gl
|
||||
if gl is None:
|
||||
logger.debug("_import_opengl: importing OpenGL.GL")
|
||||
import OpenGL.GL as _gl
|
||||
gl = _gl
|
||||
logger.debug("_import_opengl: import completed")
|
||||
return gl
|
||||
|
||||
|
||||
class SizeModeInput(TypedDict):
|
||||
size_mode: str
|
||||
width: int
|
||||
height: int
|
||||
|
||||
|
||||
MAX_IMAGES = 5 # u_image0-4
|
||||
MAX_UNIFORMS = 5 # u_float0-4, u_int0-4
|
||||
MAX_OUTPUTS = 4 # fragColor0-3 (MRT)
|
||||
|
||||
# Vertex shader using gl_VertexID trick - no VBO needed.
|
||||
# Draws a single triangle that covers the entire screen:
|
||||
#
|
||||
# (-1,3)
|
||||
# /|
|
||||
# / | <- visible area is the unit square from (-1,-1) to (1,1)
|
||||
# / | parts outside get clipped away
|
||||
# (-1,-1)---(3,-1)
|
||||
#
|
||||
# v_texCoord is computed from clip space: * 0.5 + 0.5 maps (-1,1) -> (0,1)
|
||||
VERTEX_SHADER = """#version 330 core
|
||||
out vec2 v_texCoord;
|
||||
void main() {
|
||||
vec2 verts[3] = vec2[](vec2(-1, -1), vec2(3, -1), vec2(-1, 3));
|
||||
v_texCoord = verts[gl_VertexID] * 0.5 + 0.5;
|
||||
gl_Position = vec4(verts[gl_VertexID], 0, 1);
|
||||
}
|
||||
"""
|
||||
|
||||
DEFAULT_FRAGMENT_SHADER = """#version 300 es
|
||||
precision highp float;
|
||||
|
||||
uniform sampler2D u_image0;
|
||||
uniform vec2 u_resolution;
|
||||
|
||||
in vec2 v_texCoord;
|
||||
layout(location = 0) out vec4 fragColor0;
|
||||
|
||||
void main() {
|
||||
fragColor0 = texture(u_image0, v_texCoord);
|
||||
}
|
||||
"""
|
||||
|
||||
|
||||
def _convert_es_to_desktop(source: str) -> str:
|
||||
"""Convert GLSL ES (WebGL) shader source to desktop GLSL 330 core."""
|
||||
# Remove any existing #version directive
|
||||
source = re.sub(r"#version\s+\d+(\s+es)?\s*\n?", "", source, flags=re.IGNORECASE)
|
||||
# Remove precision qualifiers (not needed in desktop GLSL)
|
||||
source = re.sub(r"precision\s+(lowp|mediump|highp)\s+\w+\s*;\s*\n?", "", source)
|
||||
# Prepend desktop GLSL version
|
||||
return "#version 330 core\n" + source
|
||||
|
||||
|
||||
def _detect_output_count(source: str) -> int:
|
||||
"""Detect how many fragColor outputs are used in the shader.
|
||||
|
||||
Returns the count of outputs needed (1 to MAX_OUTPUTS).
|
||||
"""
|
||||
matches = re.findall(r"fragColor(\d+)", source)
|
||||
if not matches:
|
||||
return 1 # Default to 1 output if none found
|
||||
max_index = max(int(m) for m in matches)
|
||||
return min(max_index + 1, MAX_OUTPUTS)
|
||||
|
||||
|
||||
def _detect_pass_count(source: str) -> int:
|
||||
"""Detect multi-pass rendering from #pragma passes N directive.
|
||||
|
||||
Returns the number of passes (1 if not specified).
|
||||
"""
|
||||
match = re.search(r'#pragma\s+passes\s+(\d+)', source)
|
||||
if match:
|
||||
return max(1, int(match.group(1)))
|
||||
return 1
|
||||
|
||||
|
||||
def _init_glfw():
|
||||
"""Initialize GLFW. Returns (window, glfw_module). Raises RuntimeError on failure."""
|
||||
logger.debug("_init_glfw: starting")
|
||||
# On macOS, glfw.init() must be called from main thread or it hangs forever
|
||||
if sys.platform == "darwin":
|
||||
logger.debug("_init_glfw: skipping on macOS")
|
||||
raise RuntimeError("GLFW backend not supported on macOS")
|
||||
|
||||
logger.debug("_init_glfw: importing glfw module")
|
||||
import glfw as _glfw
|
||||
|
||||
logger.debug("_init_glfw: calling glfw.init()")
|
||||
if not _glfw.init():
|
||||
raise RuntimeError("glfw.init() failed")
|
||||
|
||||
try:
|
||||
logger.debug("_init_glfw: setting window hints")
|
||||
_glfw.window_hint(_glfw.VISIBLE, _glfw.FALSE)
|
||||
_glfw.window_hint(_glfw.CONTEXT_VERSION_MAJOR, 3)
|
||||
_glfw.window_hint(_glfw.CONTEXT_VERSION_MINOR, 3)
|
||||
_glfw.window_hint(_glfw.OPENGL_PROFILE, _glfw.OPENGL_CORE_PROFILE)
|
||||
|
||||
logger.debug("_init_glfw: calling create_window()")
|
||||
window = _glfw.create_window(64, 64, "ComfyUI GLSL", None, None)
|
||||
if not window:
|
||||
raise RuntimeError("glfw.create_window() failed")
|
||||
|
||||
logger.debug("_init_glfw: calling make_context_current()")
|
||||
_glfw.make_context_current(window)
|
||||
logger.debug("_init_glfw: completed successfully")
|
||||
return window, _glfw
|
||||
except Exception:
|
||||
logger.debug("_init_glfw: failed, terminating glfw")
|
||||
_glfw.terminate()
|
||||
raise
|
||||
|
||||
|
||||
def _init_egl():
|
||||
"""Initialize EGL for headless rendering. Returns (display, context, surface, EGL_module). Raises RuntimeError on failure."""
|
||||
logger.debug("_init_egl: starting")
|
||||
from OpenGL import EGL as _EGL
|
||||
from OpenGL.EGL import (
|
||||
eglGetDisplay, eglInitialize, eglChooseConfig, eglCreateContext,
|
||||
eglMakeCurrent, eglCreatePbufferSurface, eglBindAPI,
|
||||
eglTerminate, eglDestroyContext, eglDestroySurface,
|
||||
EGL_DEFAULT_DISPLAY, EGL_NO_CONTEXT, EGL_NONE,
|
||||
EGL_SURFACE_TYPE, EGL_PBUFFER_BIT, EGL_RENDERABLE_TYPE, EGL_OPENGL_BIT,
|
||||
EGL_RED_SIZE, EGL_GREEN_SIZE, EGL_BLUE_SIZE, EGL_ALPHA_SIZE, EGL_DEPTH_SIZE,
|
||||
EGL_WIDTH, EGL_HEIGHT, EGL_OPENGL_API,
|
||||
)
|
||||
logger.debug("_init_egl: imports completed")
|
||||
|
||||
display = None
|
||||
context = None
|
||||
surface = None
|
||||
|
||||
try:
|
||||
logger.debug("_init_egl: calling eglGetDisplay()")
|
||||
display = eglGetDisplay(EGL_DEFAULT_DISPLAY)
|
||||
if display == _EGL.EGL_NO_DISPLAY:
|
||||
raise RuntimeError("eglGetDisplay() failed")
|
||||
|
||||
logger.debug("_init_egl: calling eglInitialize()")
|
||||
major, minor = _EGL.EGLint(), _EGL.EGLint()
|
||||
if not eglInitialize(display, major, minor):
|
||||
display = None # Not initialized, don't terminate
|
||||
raise RuntimeError("eglInitialize() failed")
|
||||
logger.debug(f"_init_egl: EGL version {major.value}.{minor.value}")
|
||||
|
||||
config_attribs = [
|
||||
EGL_SURFACE_TYPE, EGL_PBUFFER_BIT,
|
||||
EGL_RENDERABLE_TYPE, EGL_OPENGL_BIT,
|
||||
EGL_RED_SIZE, 8, EGL_GREEN_SIZE, 8, EGL_BLUE_SIZE, 8, EGL_ALPHA_SIZE, 8,
|
||||
EGL_DEPTH_SIZE, 0, EGL_NONE
|
||||
]
|
||||
configs = (_EGL.EGLConfig * 1)()
|
||||
num_configs = _EGL.EGLint()
|
||||
if not eglChooseConfig(display, config_attribs, configs, 1, num_configs) or num_configs.value == 0:
|
||||
raise RuntimeError("eglChooseConfig() failed")
|
||||
config = configs[0]
|
||||
logger.debug(f"_init_egl: config chosen, num_configs={num_configs.value}")
|
||||
|
||||
if not eglBindAPI(EGL_OPENGL_API):
|
||||
raise RuntimeError("eglBindAPI() failed")
|
||||
|
||||
logger.debug("_init_egl: calling eglCreateContext()")
|
||||
context_attribs = [
|
||||
_EGL.EGL_CONTEXT_MAJOR_VERSION, 3,
|
||||
_EGL.EGL_CONTEXT_MINOR_VERSION, 3,
|
||||
_EGL.EGL_CONTEXT_OPENGL_PROFILE_MASK, _EGL.EGL_CONTEXT_OPENGL_CORE_PROFILE_BIT,
|
||||
EGL_NONE
|
||||
]
|
||||
context = eglCreateContext(display, config, EGL_NO_CONTEXT, context_attribs)
|
||||
if context == EGL_NO_CONTEXT:
|
||||
raise RuntimeError("eglCreateContext() failed")
|
||||
|
||||
logger.debug("_init_egl: calling eglCreatePbufferSurface()")
|
||||
pbuffer_attribs = [EGL_WIDTH, 64, EGL_HEIGHT, 64, EGL_NONE]
|
||||
surface = eglCreatePbufferSurface(display, config, pbuffer_attribs)
|
||||
if surface == _EGL.EGL_NO_SURFACE:
|
||||
raise RuntimeError("eglCreatePbufferSurface() failed")
|
||||
|
||||
logger.debug("_init_egl: calling eglMakeCurrent()")
|
||||
if not eglMakeCurrent(display, surface, surface, context):
|
||||
raise RuntimeError("eglMakeCurrent() failed")
|
||||
|
||||
logger.debug("_init_egl: completed successfully")
|
||||
return display, context, surface, _EGL
|
||||
|
||||
except Exception:
|
||||
logger.debug("_init_egl: failed, cleaning up")
|
||||
# Clean up any resources on failure
|
||||
if surface is not None:
|
||||
eglDestroySurface(display, surface)
|
||||
if context is not None:
|
||||
eglDestroyContext(display, context)
|
||||
if display is not None:
|
||||
eglTerminate(display)
|
||||
raise
|
||||
|
||||
|
||||
def _init_osmesa():
|
||||
"""Initialize OSMesa for software rendering. Returns (context, buffer). Raises RuntimeError on failure."""
|
||||
import ctypes
|
||||
|
||||
logger.debug("_init_osmesa: starting")
|
||||
os.environ["PYOPENGL_PLATFORM"] = "osmesa"
|
||||
|
||||
logger.debug("_init_osmesa: importing OpenGL.osmesa")
|
||||
from OpenGL import GL as _gl
|
||||
from OpenGL.osmesa import (
|
||||
OSMesaCreateContextExt, OSMesaMakeCurrent, OSMesaDestroyContext,
|
||||
OSMESA_RGBA,
|
||||
)
|
||||
logger.debug("_init_osmesa: imports completed")
|
||||
|
||||
ctx = OSMesaCreateContextExt(OSMESA_RGBA, 24, 0, 0, None)
|
||||
if not ctx:
|
||||
raise RuntimeError("OSMesaCreateContextExt() failed")
|
||||
|
||||
width, height = 64, 64
|
||||
buffer = (ctypes.c_ubyte * (width * height * 4))()
|
||||
|
||||
logger.debug("_init_osmesa: calling OSMesaMakeCurrent()")
|
||||
if not OSMesaMakeCurrent(ctx, buffer, _gl.GL_UNSIGNED_BYTE, width, height):
|
||||
OSMesaDestroyContext(ctx)
|
||||
raise RuntimeError("OSMesaMakeCurrent() failed")
|
||||
|
||||
logger.debug("_init_osmesa: completed successfully")
|
||||
return ctx, buffer
|
||||
|
||||
|
||||
class GLContext:
|
||||
"""Manages OpenGL context and resources for shader execution.
|
||||
|
||||
Tries backends in order: GLFW (desktop) → EGL (headless GPU) → OSMesa (software).
|
||||
"""
|
||||
|
||||
_instance = None
|
||||
_initialized = False
|
||||
|
||||
def __new__(cls):
|
||||
if cls._instance is None:
|
||||
cls._instance = super().__new__(cls)
|
||||
return cls._instance
|
||||
|
||||
def __init__(self):
|
||||
if GLContext._initialized:
|
||||
logger.debug("GLContext.__init__: already initialized, skipping")
|
||||
return
|
||||
|
||||
logger.debug("GLContext.__init__: starting initialization")
|
||||
|
||||
global glfw, EGL
|
||||
|
||||
import time
|
||||
start = time.perf_counter()
|
||||
|
||||
self._backend = None
|
||||
self._window = None
|
||||
self._egl_display = None
|
||||
self._egl_context = None
|
||||
self._egl_surface = None
|
||||
self._osmesa_ctx = None
|
||||
self._osmesa_buffer = None
|
||||
self._vao = None
|
||||
|
||||
# Try backends in order: GLFW → EGL → OSMesa
|
||||
errors = []
|
||||
|
||||
logger.debug("GLContext.__init__: trying GLFW backend")
|
||||
try:
|
||||
self._window, glfw = _init_glfw()
|
||||
self._backend = "glfw"
|
||||
logger.debug("GLContext.__init__: GLFW backend succeeded")
|
||||
except Exception as e:
|
||||
logger.debug(f"GLContext.__init__: GLFW backend failed: {e}")
|
||||
errors.append(("GLFW", e))
|
||||
|
||||
if self._backend is None:
|
||||
logger.debug("GLContext.__init__: trying EGL backend")
|
||||
try:
|
||||
self._egl_display, self._egl_context, self._egl_surface, EGL = _init_egl()
|
||||
self._backend = "egl"
|
||||
logger.debug("GLContext.__init__: EGL backend succeeded")
|
||||
except Exception as e:
|
||||
logger.debug(f"GLContext.__init__: EGL backend failed: {e}")
|
||||
errors.append(("EGL", e))
|
||||
|
||||
if self._backend is None:
|
||||
logger.debug("GLContext.__init__: trying OSMesa backend")
|
||||
try:
|
||||
self._osmesa_ctx, self._osmesa_buffer = _init_osmesa()
|
||||
self._backend = "osmesa"
|
||||
logger.debug("GLContext.__init__: OSMesa backend succeeded")
|
||||
except Exception as e:
|
||||
logger.debug(f"GLContext.__init__: OSMesa backend failed: {e}")
|
||||
errors.append(("OSMesa", e))
|
||||
|
||||
if self._backend is None:
|
||||
if sys.platform == "win32":
|
||||
platform_help = (
|
||||
"Windows: Ensure GPU drivers are installed and display is available.\n"
|
||||
" CPU-only/headless mode is not supported on Windows."
|
||||
)
|
||||
elif sys.platform == "darwin":
|
||||
platform_help = (
|
||||
"macOS: GLFW is not supported.\n"
|
||||
" Install OSMesa via Homebrew: brew install mesa\n"
|
||||
" Then: pip install PyOpenGL PyOpenGL-accelerate"
|
||||
)
|
||||
else:
|
||||
platform_help = (
|
||||
"Linux: Install one of these backends:\n"
|
||||
" Desktop: sudo apt install libgl1-mesa-glx libglfw3\n"
|
||||
" Headless with GPU: sudo apt install libegl1-mesa libgl1-mesa-dri\n"
|
||||
" Headless (CPU): sudo apt install libosmesa6"
|
||||
)
|
||||
|
||||
error_details = "\n".join(f" {name}: {err}" for name, err in errors)
|
||||
raise RuntimeError(
|
||||
f"Failed to create OpenGL context.\n\n"
|
||||
f"Backend errors:\n{error_details}\n\n"
|
||||
f"{platform_help}"
|
||||
)
|
||||
|
||||
# Now import OpenGL.GL (after context is current)
|
||||
logger.debug("GLContext.__init__: importing OpenGL.GL")
|
||||
_import_opengl()
|
||||
|
||||
# Create VAO (required for core profile, but OSMesa may use compat profile)
|
||||
logger.debug("GLContext.__init__: creating VAO")
|
||||
try:
|
||||
vao = gl.glGenVertexArrays(1)
|
||||
gl.glBindVertexArray(vao)
|
||||
self._vao = vao # Only store after successful bind
|
||||
logger.debug("GLContext.__init__: VAO created successfully")
|
||||
except Exception as e:
|
||||
logger.debug(f"GLContext.__init__: VAO creation failed (may be expected for OSMesa): {e}")
|
||||
# OSMesa with older Mesa may not support VAOs
|
||||
# Clean up if we created but couldn't bind
|
||||
if vao:
|
||||
try:
|
||||
gl.glDeleteVertexArrays(1, [vao])
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
elapsed = (time.perf_counter() - start) * 1000
|
||||
|
||||
# Log device info
|
||||
renderer = gl.glGetString(gl.GL_RENDERER)
|
||||
vendor = gl.glGetString(gl.GL_VENDOR)
|
||||
version = gl.glGetString(gl.GL_VERSION)
|
||||
renderer = renderer.decode() if renderer else "Unknown"
|
||||
vendor = vendor.decode() if vendor else "Unknown"
|
||||
version = version.decode() if version else "Unknown"
|
||||
|
||||
GLContext._initialized = True
|
||||
logger.info(f"GLSL context initialized in {elapsed:.1f}ms ({self._backend}) - {renderer} ({vendor}), GL {version}")
|
||||
|
||||
def make_current(self):
|
||||
if self._backend == "glfw":
|
||||
glfw.make_context_current(self._window)
|
||||
elif self._backend == "egl":
|
||||
from OpenGL.EGL import eglMakeCurrent
|
||||
eglMakeCurrent(self._egl_display, self._egl_surface, self._egl_surface, self._egl_context)
|
||||
elif self._backend == "osmesa":
|
||||
from OpenGL.osmesa import OSMesaMakeCurrent
|
||||
OSMesaMakeCurrent(self._osmesa_ctx, self._osmesa_buffer, gl.GL_UNSIGNED_BYTE, 64, 64)
|
||||
|
||||
if self._vao is not None:
|
||||
gl.glBindVertexArray(self._vao)
|
||||
|
||||
|
||||
def _compile_shader(source: str, shader_type: int) -> int:
|
||||
"""Compile a shader and return its ID."""
|
||||
shader = gl.glCreateShader(shader_type)
|
||||
gl.glShaderSource(shader, source)
|
||||
gl.glCompileShader(shader)
|
||||
|
||||
if gl.glGetShaderiv(shader, gl.GL_COMPILE_STATUS) != gl.GL_TRUE:
|
||||
error = gl.glGetShaderInfoLog(shader).decode()
|
||||
gl.glDeleteShader(shader)
|
||||
raise RuntimeError(f"Shader compilation failed:\n{error}")
|
||||
|
||||
return shader
|
||||
|
||||
|
||||
def _create_program(vertex_source: str, fragment_source: str) -> int:
|
||||
"""Create and link a shader program."""
|
||||
vertex_shader = _compile_shader(vertex_source, gl.GL_VERTEX_SHADER)
|
||||
try:
|
||||
fragment_shader = _compile_shader(fragment_source, gl.GL_FRAGMENT_SHADER)
|
||||
except RuntimeError:
|
||||
gl.glDeleteShader(vertex_shader)
|
||||
raise
|
||||
|
||||
program = gl.glCreateProgram()
|
||||
gl.glAttachShader(program, vertex_shader)
|
||||
gl.glAttachShader(program, fragment_shader)
|
||||
gl.glLinkProgram(program)
|
||||
|
||||
gl.glDeleteShader(vertex_shader)
|
||||
gl.glDeleteShader(fragment_shader)
|
||||
|
||||
if gl.glGetProgramiv(program, gl.GL_LINK_STATUS) != gl.GL_TRUE:
|
||||
error = gl.glGetProgramInfoLog(program).decode()
|
||||
gl.glDeleteProgram(program)
|
||||
raise RuntimeError(f"Program linking failed:\n{error}")
|
||||
|
||||
return program
|
||||
|
||||
|
||||
def _render_shader_batch(
|
||||
fragment_code: str,
|
||||
width: int,
|
||||
height: int,
|
||||
image_batches: list[list[np.ndarray]],
|
||||
floats: list[float],
|
||||
ints: list[int],
|
||||
) -> list[list[np.ndarray]]:
|
||||
"""
|
||||
Render a fragment shader for multiple batches efficiently.
|
||||
|
||||
Compiles shader once, reuses framebuffer/textures across batches.
|
||||
Supports multi-pass rendering via #pragma passes N directive.
|
||||
|
||||
Args:
|
||||
fragment_code: User's fragment shader code
|
||||
width: Output width
|
||||
height: Output height
|
||||
image_batches: List of batches, each batch is a list of input images (H, W, C) float32 [0,1]
|
||||
floats: List of float uniforms
|
||||
ints: List of int uniforms
|
||||
|
||||
Returns:
|
||||
List of batch outputs, each is a list of output images (H, W, 4) float32 [0,1]
|
||||
"""
|
||||
import time
|
||||
start_time = time.perf_counter()
|
||||
|
||||
if not image_batches:
|
||||
return []
|
||||
|
||||
ctx = GLContext()
|
||||
ctx.make_current()
|
||||
|
||||
# Convert from GLSL ES to desktop GLSL 330
|
||||
fragment_source = _convert_es_to_desktop(fragment_code)
|
||||
|
||||
# Detect how many outputs the shader actually uses
|
||||
num_outputs = _detect_output_count(fragment_code)
|
||||
|
||||
# Detect multi-pass rendering
|
||||
num_passes = _detect_pass_count(fragment_code)
|
||||
|
||||
# Track resources for cleanup
|
||||
program = None
|
||||
fbo = None
|
||||
output_textures = []
|
||||
input_textures = []
|
||||
ping_pong_textures = []
|
||||
ping_pong_fbos = []
|
||||
|
||||
num_inputs = len(image_batches[0])
|
||||
|
||||
try:
|
||||
# Compile shaders (once for all batches)
|
||||
try:
|
||||
program = _create_program(VERTEX_SHADER, fragment_source)
|
||||
except RuntimeError:
|
||||
logger.error(f"Fragment shader:\n{fragment_source}")
|
||||
raise
|
||||
|
||||
gl.glUseProgram(program)
|
||||
|
||||
# Create framebuffer with only the needed color attachments
|
||||
fbo = gl.glGenFramebuffers(1)
|
||||
gl.glBindFramebuffer(gl.GL_FRAMEBUFFER, fbo)
|
||||
|
||||
draw_buffers = []
|
||||
for i in range(num_outputs):
|
||||
tex = gl.glGenTextures(1)
|
||||
output_textures.append(tex)
|
||||
gl.glBindTexture(gl.GL_TEXTURE_2D, tex)
|
||||
gl.glTexImage2D(gl.GL_TEXTURE_2D, 0, gl.GL_RGBA32F, width, height, 0, gl.GL_RGBA, gl.GL_FLOAT, None)
|
||||
gl.glTexParameteri(gl.GL_TEXTURE_2D, gl.GL_TEXTURE_MIN_FILTER, gl.GL_LINEAR)
|
||||
gl.glTexParameteri(gl.GL_TEXTURE_2D, gl.GL_TEXTURE_MAG_FILTER, gl.GL_LINEAR)
|
||||
gl.glFramebufferTexture2D(gl.GL_FRAMEBUFFER, gl.GL_COLOR_ATTACHMENT0 + i, gl.GL_TEXTURE_2D, tex, 0)
|
||||
draw_buffers.append(gl.GL_COLOR_ATTACHMENT0 + i)
|
||||
|
||||
gl.glDrawBuffers(num_outputs, draw_buffers)
|
||||
|
||||
if gl.glCheckFramebufferStatus(gl.GL_FRAMEBUFFER) != gl.GL_FRAMEBUFFER_COMPLETE:
|
||||
raise RuntimeError("Framebuffer is not complete")
|
||||
|
||||
# Create ping-pong resources for multi-pass rendering
|
||||
if num_passes > 1:
|
||||
for _ in range(2):
|
||||
pp_tex = gl.glGenTextures(1)
|
||||
ping_pong_textures.append(pp_tex)
|
||||
gl.glBindTexture(gl.GL_TEXTURE_2D, pp_tex)
|
||||
gl.glTexImage2D(gl.GL_TEXTURE_2D, 0, gl.GL_RGBA32F, width, height, 0, gl.GL_RGBA, gl.GL_FLOAT, None)
|
||||
gl.glTexParameteri(gl.GL_TEXTURE_2D, gl.GL_TEXTURE_MIN_FILTER, gl.GL_LINEAR)
|
||||
gl.glTexParameteri(gl.GL_TEXTURE_2D, gl.GL_TEXTURE_MAG_FILTER, gl.GL_LINEAR)
|
||||
gl.glTexParameteri(gl.GL_TEXTURE_2D, gl.GL_TEXTURE_WRAP_S, gl.GL_CLAMP_TO_EDGE)
|
||||
gl.glTexParameteri(gl.GL_TEXTURE_2D, gl.GL_TEXTURE_WRAP_T, gl.GL_CLAMP_TO_EDGE)
|
||||
|
||||
pp_fbo = gl.glGenFramebuffers(1)
|
||||
ping_pong_fbos.append(pp_fbo)
|
||||
gl.glBindFramebuffer(gl.GL_FRAMEBUFFER, pp_fbo)
|
||||
gl.glFramebufferTexture2D(gl.GL_FRAMEBUFFER, gl.GL_COLOR_ATTACHMENT0, gl.GL_TEXTURE_2D, pp_tex, 0)
|
||||
gl.glDrawBuffers(1, [gl.GL_COLOR_ATTACHMENT0])
|
||||
|
||||
if gl.glCheckFramebufferStatus(gl.GL_FRAMEBUFFER) != gl.GL_FRAMEBUFFER_COMPLETE:
|
||||
raise RuntimeError("Ping-pong framebuffer is not complete")
|
||||
|
||||
# Create input textures (reused for all batches)
|
||||
for i in range(num_inputs):
|
||||
tex = gl.glGenTextures(1)
|
||||
input_textures.append(tex)
|
||||
gl.glActiveTexture(gl.GL_TEXTURE0 + i)
|
||||
gl.glBindTexture(gl.GL_TEXTURE_2D, tex)
|
||||
gl.glTexParameteri(gl.GL_TEXTURE_2D, gl.GL_TEXTURE_MIN_FILTER, gl.GL_LINEAR)
|
||||
gl.glTexParameteri(gl.GL_TEXTURE_2D, gl.GL_TEXTURE_MAG_FILTER, gl.GL_LINEAR)
|
||||
gl.glTexParameteri(gl.GL_TEXTURE_2D, gl.GL_TEXTURE_WRAP_S, gl.GL_CLAMP_TO_EDGE)
|
||||
gl.glTexParameteri(gl.GL_TEXTURE_2D, gl.GL_TEXTURE_WRAP_T, gl.GL_CLAMP_TO_EDGE)
|
||||
|
||||
loc = gl.glGetUniformLocation(program, f"u_image{i}")
|
||||
if loc >= 0:
|
||||
gl.glUniform1i(loc, i)
|
||||
|
||||
# Set static uniforms (once for all batches)
|
||||
loc = gl.glGetUniformLocation(program, "u_resolution")
|
||||
if loc >= 0:
|
||||
gl.glUniform2f(loc, float(width), float(height))
|
||||
|
||||
for i, v in enumerate(floats):
|
||||
loc = gl.glGetUniformLocation(program, f"u_float{i}")
|
||||
if loc >= 0:
|
||||
gl.glUniform1f(loc, v)
|
||||
|
||||
for i, v in enumerate(ints):
|
||||
loc = gl.glGetUniformLocation(program, f"u_int{i}")
|
||||
if loc >= 0:
|
||||
gl.glUniform1i(loc, v)
|
||||
|
||||
# Get u_pass uniform location for multi-pass
|
||||
pass_loc = gl.glGetUniformLocation(program, "u_pass")
|
||||
|
||||
gl.glViewport(0, 0, width, height)
|
||||
gl.glDisable(gl.GL_BLEND) # Ensure no alpha blending - write output directly
|
||||
|
||||
# Process each batch
|
||||
all_batch_outputs = []
|
||||
for images in image_batches:
|
||||
# Update input textures with this batch's images
|
||||
for i, img in enumerate(images):
|
||||
gl.glActiveTexture(gl.GL_TEXTURE0 + i)
|
||||
gl.glBindTexture(gl.GL_TEXTURE_2D, input_textures[i])
|
||||
|
||||
# Flip vertically for GL coordinates, ensure RGBA
|
||||
h, w, c = img.shape
|
||||
if c == 3:
|
||||
img_upload = np.empty((h, w, 4), dtype=np.float32)
|
||||
img_upload[:, :, :3] = img[::-1, :, :]
|
||||
img_upload[:, :, 3] = 1.0
|
||||
else:
|
||||
img_upload = np.ascontiguousarray(img[::-1, :, :])
|
||||
|
||||
gl.glTexImage2D(gl.GL_TEXTURE_2D, 0, gl.GL_RGBA32F, w, h, 0, gl.GL_RGBA, gl.GL_FLOAT, img_upload)
|
||||
|
||||
if num_passes == 1:
|
||||
# Single pass - render directly to output FBO
|
||||
gl.glBindFramebuffer(gl.GL_FRAMEBUFFER, fbo)
|
||||
if pass_loc >= 0:
|
||||
gl.glUniform1i(pass_loc, 0)
|
||||
gl.glClearColor(0, 0, 0, 0)
|
||||
gl.glClear(gl.GL_COLOR_BUFFER_BIT)
|
||||
gl.glDrawArrays(gl.GL_TRIANGLES, 0, 3)
|
||||
else:
|
||||
# Multi-pass rendering with ping-pong
|
||||
for p in range(num_passes):
|
||||
is_last_pass = (p == num_passes - 1)
|
||||
|
||||
# Set pass uniform
|
||||
if pass_loc >= 0:
|
||||
gl.glUniform1i(pass_loc, p)
|
||||
|
||||
if is_last_pass:
|
||||
# Last pass renders to the main output FBO
|
||||
gl.glBindFramebuffer(gl.GL_FRAMEBUFFER, fbo)
|
||||
else:
|
||||
# Intermediate passes render to ping-pong FBO
|
||||
target_fbo = ping_pong_fbos[p % 2]
|
||||
gl.glBindFramebuffer(gl.GL_FRAMEBUFFER, target_fbo)
|
||||
|
||||
# Set input texture for this pass
|
||||
gl.glActiveTexture(gl.GL_TEXTURE0)
|
||||
if p == 0:
|
||||
# First pass reads from original input
|
||||
gl.glBindTexture(gl.GL_TEXTURE_2D, input_textures[0])
|
||||
else:
|
||||
# Subsequent passes read from previous pass output
|
||||
source_tex = ping_pong_textures[(p - 1) % 2]
|
||||
gl.glBindTexture(gl.GL_TEXTURE_2D, source_tex)
|
||||
|
||||
gl.glClearColor(0, 0, 0, 0)
|
||||
gl.glClear(gl.GL_COLOR_BUFFER_BIT)
|
||||
gl.glDrawArrays(gl.GL_TRIANGLES, 0, 3)
|
||||
|
||||
# Read back outputs for this batch
|
||||
# (glGetTexImage is synchronous, implicitly waits for rendering)
|
||||
batch_outputs = []
|
||||
for tex in output_textures:
|
||||
gl.glBindTexture(gl.GL_TEXTURE_2D, tex)
|
||||
data = gl.glGetTexImage(gl.GL_TEXTURE_2D, 0, gl.GL_RGBA, gl.GL_FLOAT)
|
||||
img = np.frombuffer(data, dtype=np.float32).reshape(height, width, 4)
|
||||
batch_outputs.append(img[::-1, :, :].copy())
|
||||
|
||||
# Pad with black images for unused outputs
|
||||
black_img = np.zeros((height, width, 4), dtype=np.float32)
|
||||
for _ in range(num_outputs, MAX_OUTPUTS):
|
||||
batch_outputs.append(black_img)
|
||||
|
||||
all_batch_outputs.append(batch_outputs)
|
||||
|
||||
elapsed = (time.perf_counter() - start_time) * 1000
|
||||
num_batches = len(image_batches)
|
||||
pass_info = f", {num_passes} passes" if num_passes > 1 else ""
|
||||
logger.info(f"GLSL shader executed in {elapsed:.1f}ms ({num_batches} batch{'es' if num_batches != 1 else ''}, {width}x{height}{pass_info})")
|
||||
|
||||
return all_batch_outputs
|
||||
|
||||
finally:
|
||||
# Unbind before deleting
|
||||
gl.glBindFramebuffer(gl.GL_FRAMEBUFFER, 0)
|
||||
gl.glUseProgram(0)
|
||||
|
||||
if input_textures:
|
||||
gl.glDeleteTextures(len(input_textures), input_textures)
|
||||
if output_textures:
|
||||
gl.glDeleteTextures(len(output_textures), output_textures)
|
||||
if ping_pong_textures:
|
||||
gl.glDeleteTextures(len(ping_pong_textures), ping_pong_textures)
|
||||
if fbo is not None:
|
||||
gl.glDeleteFramebuffers(1, [fbo])
|
||||
for pp_fbo in ping_pong_fbos:
|
||||
gl.glDeleteFramebuffers(1, [pp_fbo])
|
||||
if program is not None:
|
||||
gl.glDeleteProgram(program)
|
||||
|
||||
class GLSLShader(io.ComfyNode):
|
||||
|
||||
@classmethod
|
||||
def define_schema(cls) -> io.Schema:
|
||||
image_template = io.Autogrow.TemplatePrefix(
|
||||
io.Image.Input("image"),
|
||||
prefix="image",
|
||||
min=1,
|
||||
max=MAX_IMAGES,
|
||||
)
|
||||
|
||||
float_template = io.Autogrow.TemplatePrefix(
|
||||
io.Float.Input("float", default=0.0),
|
||||
prefix="u_float",
|
||||
min=0,
|
||||
max=MAX_UNIFORMS,
|
||||
)
|
||||
|
||||
int_template = io.Autogrow.TemplatePrefix(
|
||||
io.Int.Input("int", default=0),
|
||||
prefix="u_int",
|
||||
min=0,
|
||||
max=MAX_UNIFORMS,
|
||||
)
|
||||
|
||||
return io.Schema(
|
||||
node_id="GLSLShader",
|
||||
display_name="GLSL Shader",
|
||||
category="image/shader",
|
||||
description=(
|
||||
"Apply GLSL ES fragment shaders to images. "
|
||||
"u_resolution (vec2) is always available."
|
||||
),
|
||||
inputs=[
|
||||
io.String.Input(
|
||||
"fragment_shader",
|
||||
default=DEFAULT_FRAGMENT_SHADER,
|
||||
multiline=True,
|
||||
tooltip="GLSL fragment shader source code (GLSL ES 3.00 / WebGL 2.0 compatible)",
|
||||
),
|
||||
io.DynamicCombo.Input(
|
||||
"size_mode",
|
||||
options=[
|
||||
io.DynamicCombo.Option("from_input", []),
|
||||
io.DynamicCombo.Option(
|
||||
"custom",
|
||||
[
|
||||
io.Int.Input(
|
||||
"width",
|
||||
default=512,
|
||||
min=1,
|
||||
max=nodes.MAX_RESOLUTION,
|
||||
),
|
||||
io.Int.Input(
|
||||
"height",
|
||||
default=512,
|
||||
min=1,
|
||||
max=nodes.MAX_RESOLUTION,
|
||||
),
|
||||
],
|
||||
),
|
||||
],
|
||||
tooltip="Output size: 'from_input' uses first input image dimensions, 'custom' allows manual size",
|
||||
),
|
||||
io.Autogrow.Input("images", template=image_template, tooltip=f"Images are available as u_image0-{MAX_IMAGES-1} (sampler2D) in the shader code"),
|
||||
io.Autogrow.Input("floats", template=float_template, tooltip=f"Floats are available as u_float0-{MAX_UNIFORMS-1} in the shader code"),
|
||||
io.Autogrow.Input("ints", template=int_template, tooltip=f"Ints are available as u_int0-{MAX_UNIFORMS-1} in the shader code"),
|
||||
],
|
||||
outputs=[
|
||||
io.Image.Output(display_name="IMAGE0", tooltip="Available via layout(location = 0) out vec4 fragColor0 in the shader code"),
|
||||
io.Image.Output(display_name="IMAGE1", tooltip="Available via layout(location = 1) out vec4 fragColor1 in the shader code"),
|
||||
io.Image.Output(display_name="IMAGE2", tooltip="Available via layout(location = 2) out vec4 fragColor2 in the shader code"),
|
||||
io.Image.Output(display_name="IMAGE3", tooltip="Available via layout(location = 3) out vec4 fragColor3 in the shader code"),
|
||||
],
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def execute(
|
||||
cls,
|
||||
fragment_shader: str,
|
||||
size_mode: SizeModeInput,
|
||||
images: io.Autogrow.Type,
|
||||
floats: io.Autogrow.Type = None,
|
||||
ints: io.Autogrow.Type = None,
|
||||
**kwargs,
|
||||
) -> io.NodeOutput:
|
||||
image_list = [v for v in images.values() if v is not None]
|
||||
float_list = (
|
||||
[v if v is not None else 0.0 for v in floats.values()] if floats else []
|
||||
)
|
||||
int_list = [v if v is not None else 0 for v in ints.values()] if ints else []
|
||||
|
||||
if not image_list:
|
||||
raise ValueError("At least one input image is required")
|
||||
|
||||
# Determine output dimensions
|
||||
if size_mode["size_mode"] == "custom":
|
||||
out_width = size_mode["width"]
|
||||
out_height = size_mode["height"]
|
||||
else:
|
||||
out_height, out_width = image_list[0].shape[1:3]
|
||||
|
||||
batch_size = image_list[0].shape[0]
|
||||
|
||||
# Prepare batches
|
||||
image_batches = []
|
||||
for batch_idx in range(batch_size):
|
||||
batch_images = [img_tensor[batch_idx].cpu().numpy().astype(np.float32) for img_tensor in image_list]
|
||||
image_batches.append(batch_images)
|
||||
|
||||
all_batch_outputs = _render_shader_batch(
|
||||
fragment_shader,
|
||||
out_width,
|
||||
out_height,
|
||||
image_batches,
|
||||
float_list,
|
||||
int_list,
|
||||
)
|
||||
|
||||
# Collect outputs into tensors
|
||||
all_outputs = [[] for _ in range(MAX_OUTPUTS)]
|
||||
for batch_outputs in all_batch_outputs:
|
||||
for i, out_img in enumerate(batch_outputs):
|
||||
all_outputs[i].append(torch.from_numpy(out_img))
|
||||
|
||||
output_tensors = [torch.stack(all_outputs[i], dim=0) for i in range(MAX_OUTPUTS)]
|
||||
return io.NodeOutput(
|
||||
*output_tensors,
|
||||
ui=cls._build_ui_output(image_list, output_tensors[0]),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def _build_ui_output(
|
||||
cls, image_list: list[torch.Tensor], output_batch: torch.Tensor
|
||||
) -> dict[str, list]:
|
||||
"""Build UI output with input and output images for client-side shader execution."""
|
||||
combined_inputs = torch.cat(image_list, dim=0)
|
||||
input_images_ui = ui.ImageSaveHelper.save_images(
|
||||
combined_inputs,
|
||||
filename_prefix="GLSLShader_input",
|
||||
folder_type=io.FolderType.temp,
|
||||
cls=None,
|
||||
compress_level=1,
|
||||
)
|
||||
|
||||
output_images_ui = ui.ImageSaveHelper.save_images(
|
||||
output_batch,
|
||||
filename_prefix="GLSLShader_output",
|
||||
folder_type=io.FolderType.temp,
|
||||
cls=None,
|
||||
compress_level=1,
|
||||
)
|
||||
|
||||
return {"input_images": input_images_ui, "images": output_images_ui}
|
||||
|
||||
|
||||
class GLSLExtension(ComfyExtension):
|
||||
@override
|
||||
async def get_node_list(self) -> list[type[io.ComfyNode]]:
|
||||
return [GLSLShader]
|
||||
|
||||
|
||||
async def comfy_entrypoint() -> GLSLExtension:
|
||||
return GLSLExtension()
|
||||
@ -588,7 +588,6 @@ class ImageRotate(IO.ComfyNode):
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="ImageRotate",
|
||||
display_name="Image Rotate",
|
||||
search_aliases=["turn", "flip orientation"],
|
||||
category="image/transform",
|
||||
essentials_category="Image Tools",
|
||||
|
||||
@ -19,7 +19,6 @@ class Blend(io.ComfyNode):
|
||||
def define_schema(cls):
|
||||
return io.Schema(
|
||||
node_id="ImageBlend",
|
||||
display_name="Image Blend",
|
||||
category="image/postprocessing",
|
||||
inputs=[
|
||||
io.Image.Input("image1"),
|
||||
@ -77,7 +76,6 @@ class Blur(io.ComfyNode):
|
||||
def define_schema(cls):
|
||||
return io.Schema(
|
||||
node_id="ImageBlur",
|
||||
display_name="Image Blur",
|
||||
category="image/postprocessing",
|
||||
essentials_category="Image Tools",
|
||||
inputs=[
|
||||
|
||||
@ -29,7 +29,6 @@ class StringMultiline(io.ComfyNode):
|
||||
node_id="PrimitiveStringMultiline",
|
||||
display_name="String (Multiline)",
|
||||
category="utils/primitive",
|
||||
essentials_category="Basics",
|
||||
inputs=[
|
||||
io.String.Input("value", multiline=True),
|
||||
],
|
||||
|
||||
@ -42,7 +42,7 @@ class TextGenerate(io.ComfyNode):
|
||||
@classmethod
|
||||
def execute(cls, clip, prompt, max_length, sampling_mode, image=None) -> io.NodeOutput:
|
||||
|
||||
tokens = clip.tokenize(prompt, image=image, skip_template=False, min_length=1)
|
||||
tokens = clip.tokenize(prompt, image=image, skip_template=False)
|
||||
|
||||
# Get sampling parameters from dynamic combo
|
||||
do_sample = sampling_mode.get("sampling_mode") == "on"
|
||||
|
||||
2
nodes.py
2
nodes.py
@ -70,6 +70,7 @@ class CLIPTextEncode(ComfyNodeABC):
|
||||
FUNCTION = "encode"
|
||||
|
||||
CATEGORY = "conditioning"
|
||||
ESSENTIALS_CATEGORY = "Basics"
|
||||
DESCRIPTION = "Encodes a text prompt using a CLIP model into an embedding that can be used to guide the diffusion model towards generating specific images."
|
||||
SEARCH_ALIASES = ["text", "prompt", "text prompt", "positive prompt", "negative prompt", "encode text", "text encoder", "encode prompt"]
|
||||
|
||||
@ -2441,7 +2442,6 @@ async def init_builtin_extra_nodes():
|
||||
"nodes_wanmove.py",
|
||||
"nodes_image_compare.py",
|
||||
"nodes_zimage.py",
|
||||
"nodes_glsl.py",
|
||||
"nodes_lora_debug.py",
|
||||
"nodes_textgen.py",
|
||||
"nodes_color.py",
|
||||
|
||||
@ -30,6 +30,3 @@ kornia>=0.7.1
|
||||
spandrel
|
||||
pydantic~=2.0
|
||||
pydantic-settings~=2.0
|
||||
PyOpenGL
|
||||
PyOpenGL-accelerate
|
||||
glfw
|
||||
|
||||
Reference in New Issue
Block a user