mirror of
https://github.com/comfyanonymous/ComfyUI.git
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Compare commits
13 Commits
feat/cut-r
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cursor/mar
| Author | SHA1 | Date | |
|---|---|---|---|
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| 428c323780 | |||
| 46063aa927 | |||
| b565dc7a6c | |||
| 52976f3ea3 | |||
| f505cb4070 | |||
| dabfe73dc0 | |||
| 1eeaf23f20 | |||
| aa9d2fc713 | |||
| 95f6652ef5 | |||
| 5a400d837e | |||
| 81af8e4de2 | |||
| fd17b95e1c |
268
.github/workflows/cut-release.yml
vendored
268
.github/workflows/cut-release.yml
vendored
@ -1,268 +0,0 @@
|
||||
name: Cut Release
|
||||
|
||||
# Promote a prepared "candidate" branch (cherry-picks + version bump
|
||||
# already committed) into a real release: create the canonical
|
||||
# `release/v<version>` branch and the `v<version>` annotated tag at the
|
||||
# candidate's HEAD, atomically.
|
||||
#
|
||||
# After this runs, kick off `release-stable-all.yml` manually with the new
|
||||
# tag to build portable artifacts — same as previous backports.
|
||||
#
|
||||
# The candidate branch is left in place; clean it up manually once you've
|
||||
# verified the release.
|
||||
|
||||
on:
|
||||
workflow_dispatch:
|
||||
inputs:
|
||||
source_branch:
|
||||
description: 'Candidate branch with cherry-picks + version bump (e.g. kosinkadink/release-v0.20.3-prep)'
|
||||
required: true
|
||||
type: string
|
||||
version:
|
||||
description: 'Target version (e.g. 0.20.3 — no leading v)'
|
||||
required: true
|
||||
type: string
|
||||
release_branch:
|
||||
description: 'Override target release branch name (default: release/v<version>)'
|
||||
required: false
|
||||
type: string
|
||||
default: ''
|
||||
tag_name:
|
||||
description: 'Override tag name (default: v<version>)'
|
||||
required: false
|
||||
type: string
|
||||
default: ''
|
||||
dry_run:
|
||||
description: 'Validate only — do not push branch or tag'
|
||||
required: false
|
||||
type: boolean
|
||||
default: false
|
||||
|
||||
jobs:
|
||||
cut-release:
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
# GITHUB_TOKEN write access is unused for the actual push (we use
|
||||
# RELEASE_BOT_TOKEN to bypass branch-protection rules), but kept
|
||||
# write so subsequent automation hooks have it if needed.
|
||||
contents: write
|
||||
env:
|
||||
# All workflow inputs are pulled in via env vars instead of being
|
||||
# interpolated directly into bash, to avoid command injection.
|
||||
INPUT_VERSION: ${{ inputs.version }}
|
||||
INPUT_SOURCE_BRANCH: ${{ inputs.source_branch }}
|
||||
INPUT_RELEASE_BRANCH: ${{ inputs.release_branch }}
|
||||
INPUT_TAG_NAME: ${{ inputs.tag_name }}
|
||||
INPUT_DRY_RUN: ${{ inputs.dry_run }}
|
||||
REPO_FULL: ${{ github.repository }}
|
||||
|
||||
steps:
|
||||
- name: Compute names
|
||||
id: names
|
||||
run: |
|
||||
set -euo pipefail
|
||||
VERSION="${INPUT_VERSION#v}"
|
||||
if ! [[ "$VERSION" =~ ^[0-9]+\.[0-9]+\.[0-9]+$ ]]; then
|
||||
echo "::error::Invalid version '$VERSION' — must match X.Y.Z"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
REL_BRANCH="$INPUT_RELEASE_BRANCH"
|
||||
[ -z "$REL_BRANCH" ] && REL_BRANCH="release/v${VERSION}"
|
||||
|
||||
TAG_NAME="$INPUT_TAG_NAME"
|
||||
[ -z "$TAG_NAME" ] && TAG_NAME="v${VERSION}"
|
||||
|
||||
# Validate the overrides too — they're effectively user-controlled
|
||||
# ref names and end up in shell + git invocations.
|
||||
REF_RE='^[A-Za-z0-9._/-]+$'
|
||||
if ! [[ "$REL_BRANCH" =~ $REF_RE ]]; then
|
||||
echo "::error::Invalid release_branch '$REL_BRANCH' — only [A-Za-z0-9._/-] allowed."
|
||||
exit 1
|
||||
fi
|
||||
if ! [[ "$TAG_NAME" =~ $REF_RE ]]; then
|
||||
echo "::error::Invalid tag_name '$TAG_NAME' — only [A-Za-z0-9._/-] allowed."
|
||||
exit 1
|
||||
fi
|
||||
if ! [[ "$INPUT_SOURCE_BRANCH" =~ $REF_RE ]]; then
|
||||
echo "::error::Invalid source_branch '$INPUT_SOURCE_BRANCH' — only [A-Za-z0-9._/-] allowed."
|
||||
exit 1
|
||||
fi
|
||||
|
||||
{
|
||||
echo "version=$VERSION"
|
||||
echo "release_branch=$REL_BRANCH"
|
||||
echo "tag_name=$TAG_NAME"
|
||||
} >> "$GITHUB_OUTPUT"
|
||||
echo "Computed: version=$VERSION, release_branch=$REL_BRANCH, tag_name=$TAG_NAME"
|
||||
|
||||
- name: Pre-flight remote checks
|
||||
env:
|
||||
REL_BRANCH: ${{ steps.names.outputs.release_branch }}
|
||||
TAG_NAME: ${{ steps.names.outputs.tag_name }}
|
||||
run: |
|
||||
set -euo pipefail
|
||||
REPO_URL="https://github.com/${REPO_FULL}.git"
|
||||
|
||||
# Source branch must exist.
|
||||
if ! git ls-remote --heads --exit-code "$REPO_URL" "$INPUT_SOURCE_BRANCH" >/dev/null; then
|
||||
echo "::error::Source branch '$INPUT_SOURCE_BRANCH' does not exist on origin."
|
||||
exit 1
|
||||
fi
|
||||
|
||||
# Release branch must NOT exist.
|
||||
if git ls-remote --heads --exit-code "$REPO_URL" "$REL_BRANCH" >/dev/null 2>&1; then
|
||||
echo "::error::Release branch '$REL_BRANCH' already exists on origin. Refusing to overwrite."
|
||||
exit 1
|
||||
fi
|
||||
|
||||
# Tag must NOT exist.
|
||||
if git ls-remote --tags --exit-code "$REPO_URL" "$TAG_NAME" >/dev/null 2>&1; then
|
||||
echo "::error::Tag '$TAG_NAME' already exists on origin. Refusing to overwrite."
|
||||
exit 1
|
||||
fi
|
||||
|
||||
- name: Checkout source branch
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
ref: ${{ inputs.source_branch }}
|
||||
fetch-depth: 0
|
||||
# Defense in depth: don't leave a usable git credential on disk
|
||||
# for any code that runs against the checked-out branch.
|
||||
persist-credentials: false
|
||||
|
||||
- name: Verify version files at source HEAD
|
||||
env:
|
||||
EXPECTED: ${{ steps.names.outputs.version }}
|
||||
run: |
|
||||
set -euo pipefail
|
||||
# pyproject.toml is parsed with tomllib (safe — pure data, no code).
|
||||
PYPROJECT_VERSION=$(python3 -c "import tomllib; print(tomllib.load(open('pyproject.toml','rb'))['project']['version'])")
|
||||
if [ "$PYPROJECT_VERSION" != "$EXPECTED" ]; then
|
||||
echo "::error::pyproject.toml version is '$PYPROJECT_VERSION' but expected '$EXPECTED'."
|
||||
exit 1
|
||||
fi
|
||||
# comfyui_version.py contains Python — never `exec()` it. A
|
||||
# malicious candidate branch could replace it with arbitrary code
|
||||
# that would then run in CI with RELEASE_BOT_TOKEN in scope.
|
||||
# Statically parse the AST to extract __version__ instead.
|
||||
MODULE_VERSION=$(python3 - <<'PY'
|
||||
import ast, pathlib, sys
|
||||
tree = ast.parse(pathlib.Path("comfyui_version.py").read_text(encoding="utf-8"))
|
||||
for node in tree.body:
|
||||
if isinstance(node, ast.Assign):
|
||||
for target in node.targets:
|
||||
if isinstance(target, ast.Name) and target.id == "__version__":
|
||||
if isinstance(node.value, ast.Constant) and isinstance(node.value.value, str):
|
||||
print(node.value.value)
|
||||
sys.exit(0)
|
||||
sys.exit("Could not statically read __version__ from comfyui_version.py")
|
||||
PY
|
||||
)
|
||||
if [ "$MODULE_VERSION" != "$EXPECTED" ]; then
|
||||
echo "::error::comfyui_version.py __version__ is '$MODULE_VERSION' but expected '$EXPECTED'."
|
||||
exit 1
|
||||
fi
|
||||
echo "Version files OK: $EXPECTED"
|
||||
|
||||
- name: Identify previous tag and log commit range
|
||||
id: range
|
||||
env:
|
||||
REL_BRANCH: ${{ steps.names.outputs.release_branch }}
|
||||
TAG_NAME: ${{ steps.names.outputs.tag_name }}
|
||||
run: |
|
||||
set -euo pipefail
|
||||
# Find latest tag reachable from this commit (the basis backport
|
||||
# was branched from). Falls back to "" gracefully.
|
||||
PREV_TAG=$(git describe --tags --abbrev=0 2>/dev/null || echo "")
|
||||
SOURCE_SHA=$(git rev-parse HEAD)
|
||||
{
|
||||
echo "prev_tag=$PREV_TAG"
|
||||
echo "source_sha=$SOURCE_SHA"
|
||||
} >> "$GITHUB_OUTPUT"
|
||||
{
|
||||
echo "## Cut Release plan"
|
||||
echo ""
|
||||
echo "| Field | Value |"
|
||||
echo "| --- | --- |"
|
||||
echo "| Source branch | \`$INPUT_SOURCE_BRANCH\` @ \`${SOURCE_SHA:0:12}\` |"
|
||||
echo "| Target release branch | \`$REL_BRANCH\` |"
|
||||
echo "| Tag | \`$TAG_NAME\` |"
|
||||
echo "| Previous reachable tag | \`${PREV_TAG:-none}\` |"
|
||||
echo "| Dry run | \`$INPUT_DRY_RUN\` |"
|
||||
echo ""
|
||||
echo "### Commits to be tagged"
|
||||
echo ""
|
||||
if [ -n "$PREV_TAG" ]; then
|
||||
echo "Range: \`${PREV_TAG}..${SOURCE_SHA}\`"
|
||||
echo ""
|
||||
echo '```'
|
||||
git log --oneline --no-decorate "${PREV_TAG}..${SOURCE_SHA}"
|
||||
echo '```'
|
||||
else
|
||||
echo "(no prior tag found — listing last 30 commits on source)"
|
||||
echo ""
|
||||
echo '```'
|
||||
git log --oneline --no-decorate -30 "$SOURCE_SHA"
|
||||
echo '```'
|
||||
fi
|
||||
} >> "$GITHUB_STEP_SUMMARY"
|
||||
|
||||
- name: Configure git identity
|
||||
if: inputs.dry_run != true && inputs.dry_run != 'true'
|
||||
run: |
|
||||
set -euo pipefail
|
||||
git config --global user.name "github-actions[bot]"
|
||||
git config --global user.email "github-actions[bot]@users.noreply.github.com"
|
||||
|
||||
- name: Push release branch and tag (atomic)
|
||||
if: inputs.dry_run != true && inputs.dry_run != 'true'
|
||||
env:
|
||||
GH_TOKEN: ${{ secrets.RELEASE_BOT_TOKEN }}
|
||||
REL_BRANCH: ${{ steps.names.outputs.release_branch }}
|
||||
TAG_NAME: ${{ steps.names.outputs.tag_name }}
|
||||
VERSION: ${{ steps.names.outputs.version }}
|
||||
SOURCE_SHA: ${{ steps.range.outputs.source_sha }}
|
||||
run: |
|
||||
set -euo pipefail
|
||||
if [ -z "${GH_TOKEN:-}" ]; then
|
||||
echo "::error::secrets.RELEASE_BOT_TOKEN is not set."
|
||||
exit 1
|
||||
fi
|
||||
|
||||
# Create the annotated tag locally first so we can push branch +
|
||||
# tag in a single atomic operation: either both refs are created
|
||||
# on origin, or neither — no half-promoted state.
|
||||
git tag -a "$TAG_NAME" "$SOURCE_SHA" -m "ComfyUI v${VERSION}"
|
||||
|
||||
AUTH_URL="https://x-access-token:${GH_TOKEN}@github.com/${REPO_FULL}.git"
|
||||
git push --atomic "$AUTH_URL" \
|
||||
"${SOURCE_SHA}:refs/heads/${REL_BRANCH}" \
|
||||
"refs/tags/${TAG_NAME}"
|
||||
|
||||
- name: Final summary
|
||||
if: always()
|
||||
env:
|
||||
REL_BRANCH: ${{ steps.names.outputs.release_branch }}
|
||||
TAG_NAME: ${{ steps.names.outputs.tag_name }}
|
||||
JOB_STATUS: ${{ job.status }}
|
||||
run: |
|
||||
set -euo pipefail
|
||||
{
|
||||
echo ""
|
||||
echo "### Result"
|
||||
if [ "$JOB_STATUS" != "success" ]; then
|
||||
echo "❌ Workflow did not complete successfully (job status: \`$JOB_STATUS\`). See the run logs for details. No branch or tag should be assumed to have been created."
|
||||
elif [ "$INPUT_DRY_RUN" = "true" ]; then
|
||||
echo "🔍 **Dry run** — no branch or tag was created."
|
||||
else
|
||||
echo "✅ Created \`$REL_BRANCH\` and tagged \`$TAG_NAME\` from \`$INPUT_SOURCE_BRANCH\`."
|
||||
echo ""
|
||||
echo "- Branch: <https://github.com/${REPO_FULL}/tree/${REL_BRANCH}>"
|
||||
echo "- Tag: <https://github.com/${REPO_FULL}/releases/tag/${TAG_NAME}>"
|
||||
echo ""
|
||||
echo "Next: run [release-stable-all.yml](https://github.com/${REPO_FULL}/actions/workflows/release-stable-all.yml) with \`git_tag=${TAG_NAME}\`."
|
||||
echo ""
|
||||
echo "The candidate branch \`$INPUT_SOURCE_BRANCH\` was left in place; delete it manually once you've verified the release."
|
||||
fi
|
||||
} >> "$GITHUB_STEP_SUMMARY"
|
||||
1412
blueprints/ControlNet (Z-Image-Turbo).json
Normal file
1412
blueprints/ControlNet (Z-Image-Turbo).json
Normal file
File diff suppressed because it is too large
Load Diff
@ -4234,7 +4234,7 @@
|
||||
"workflowRendererVersion": "LG"
|
||||
},
|
||||
"category": "Video generation and editing/Depth to video",
|
||||
"description": "Generates video from depth maps using LTX-2, with optional synchronized audio."
|
||||
"description": "Generates depth-controlled video with LTX-2: motion and structure follow a depth-reference video alongside text prompting, optional first-frame image conditioning, with optional synchronized audio."
|
||||
},
|
||||
{
|
||||
"id": "38b60539-50a7-42f9-a5fe-bdeca26272e2",
|
||||
|
||||
3361
blueprints/First-Last-Frame to Video.json
Normal file
3361
blueprints/First-Last-Frame to Video.json
Normal file
File diff suppressed because it is too large
Load Diff
858
blueprints/Frame Interpolation.json
Normal file
858
blueprints/Frame Interpolation.json
Normal file
@ -0,0 +1,858 @@
|
||||
{
|
||||
"revision": 0,
|
||||
"last_node_id": 16,
|
||||
"last_link_id": 0,
|
||||
"nodes": [
|
||||
{
|
||||
"id": 16,
|
||||
"type": "022693be-2baa-4009-870a-28921508a7ef",
|
||||
"pos": [
|
||||
-2990,
|
||||
-3240
|
||||
],
|
||||
"size": [
|
||||
410,
|
||||
200
|
||||
],
|
||||
"flags": {},
|
||||
"order": 2,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"localized_name": "video",
|
||||
"name": "video",
|
||||
"type": "VIDEO",
|
||||
"link": null
|
||||
},
|
||||
{
|
||||
"label": "multiplier",
|
||||
"name": "value",
|
||||
"type": "INT",
|
||||
"widget": {
|
||||
"name": "value"
|
||||
},
|
||||
"link": null
|
||||
},
|
||||
{
|
||||
"label": "enable_fps_multiplier",
|
||||
"name": "value_1",
|
||||
"type": "BOOLEAN",
|
||||
"widget": {
|
||||
"name": "value_1"
|
||||
},
|
||||
"link": null
|
||||
},
|
||||
{
|
||||
"name": "model_name",
|
||||
"type": "COMBO",
|
||||
"widget": {
|
||||
"name": "model_name"
|
||||
},
|
||||
"link": null
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"label": "VIDEO",
|
||||
"name": "VIDEO_1",
|
||||
"type": "VIDEO",
|
||||
"links": []
|
||||
},
|
||||
{
|
||||
"name": "IMAGE",
|
||||
"type": "IMAGE",
|
||||
"links": null
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"proxyWidgets": [
|
||||
[
|
||||
"9",
|
||||
"value"
|
||||
],
|
||||
[
|
||||
"13",
|
||||
"value"
|
||||
],
|
||||
[
|
||||
"1",
|
||||
"model_name"
|
||||
]
|
||||
],
|
||||
"enableTabs": false,
|
||||
"tabWidth": 65,
|
||||
"tabXOffset": 10,
|
||||
"hasSecondTab": false,
|
||||
"secondTabText": "Send Back",
|
||||
"secondTabOffset": 80,
|
||||
"secondTabWidth": 65,
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.19.3"
|
||||
},
|
||||
"widgets_values": [],
|
||||
"title": "Frame Interpolation"
|
||||
}
|
||||
],
|
||||
"links": [],
|
||||
"version": 0.4,
|
||||
"definitions": {
|
||||
"subgraphs": [
|
||||
{
|
||||
"id": "022693be-2baa-4009-870a-28921508a7ef",
|
||||
"version": 1,
|
||||
"state": {
|
||||
"lastGroupId": 0,
|
||||
"lastNodeId": 17,
|
||||
"lastLinkId": 28,
|
||||
"lastRerouteId": 0
|
||||
},
|
||||
"revision": 0,
|
||||
"config": {},
|
||||
"name": "Frame Interpolation",
|
||||
"inputNode": {
|
||||
"id": -10,
|
||||
"bounding": [
|
||||
-2810,
|
||||
-3070,
|
||||
159.7421875,
|
||||
120
|
||||
]
|
||||
},
|
||||
"outputNode": {
|
||||
"id": -20,
|
||||
"bounding": [
|
||||
-1270,
|
||||
-3075,
|
||||
120,
|
||||
80
|
||||
]
|
||||
},
|
||||
"inputs": [
|
||||
{
|
||||
"id": "05e31c51-dcb6-4a1e-9651-1b9ad4f7a287",
|
||||
"name": "video",
|
||||
"type": "VIDEO",
|
||||
"linkIds": [
|
||||
2
|
||||
],
|
||||
"localized_name": "video",
|
||||
"pos": [
|
||||
-2670.2578125,
|
||||
-3050
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": "feecb409-7d1c-4a99-9c63-50c5fecdd3c9",
|
||||
"name": "value",
|
||||
"type": "INT",
|
||||
"linkIds": [
|
||||
22
|
||||
],
|
||||
"label": "multiplier",
|
||||
"pos": [
|
||||
-2670.2578125,
|
||||
-3030
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": "0b8a861b-b581-4068-9e8c-f8d15daf1ca6",
|
||||
"name": "value_1",
|
||||
"type": "BOOLEAN",
|
||||
"linkIds": [
|
||||
23
|
||||
],
|
||||
"label": "enable_fps_multiplier",
|
||||
"pos": [
|
||||
-2670.2578125,
|
||||
-3010
|
||||
]
|
||||
},
|
||||
{
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
}
|
||||
]
|
||||
},
|
||||
"extra": {}
|
||||
}
|
||||
485
blueprints/Get Any Video Frame.json
Normal file
485
blueprints/Get Any Video Frame.json
Normal file
@ -0,0 +1,485 @@
|
||||
{
|
||||
"revision": 0,
|
||||
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||||
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||||
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||||
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104
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
},
|
||||
{
|
||||
"label": "frame_index",
|
||||
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|
||||
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|
||||
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|
||||
"name": "value"
|
||||
},
|
||||
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||||
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||||
],
|
||||
"outputs": [
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||||
{
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||||
"name": "IMAGE",
|
||||
"type": "IMAGE",
|
||||
"links": []
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||||
}
|
||||
],
|
||||
"title": "Get Any Video Frame",
|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
},
|
||||
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||||
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||||
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||||
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||||
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||||
380,
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||||
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||||
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||||
"outputNode": {
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||||
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||||
1460,
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||||
-57,
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||||
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||||
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|
||||
]
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||||
},
|
||||
"inputs": [
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||||
{
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||||
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||||
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|
||||
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||||
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4
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||||
],
|
||||
"pos": [
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||||
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|
||||
-37
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||||
]
|
||||
},
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{
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"name": "value",
|
||||
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|
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"linkIds": [
|
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||||
],
|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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{
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||||
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||||
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||||
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|
||||
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||||
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"link": 4
|
||||
}
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||||
],
|
||||
"outputs": [
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||||
{
|
||||
"localized_name": "images",
|
||||
"name": "images",
|
||||
"type": "IMAGE",
|
||||
"links": [
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||||
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|
||||
2
|
||||
]
|
||||
},
|
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{
|
||||
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|
||||
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|
||||
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||||
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||||
},
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||||
{
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||||
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|
||||
"name": "fps",
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||||
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|
||||
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||||
}
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||||
],
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}
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},
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{
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||||
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|
||||
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|
||||
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|
||||
50
|
||||
],
|
||||
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|
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||||
120
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||||
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|
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||||
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|
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||||
"link": 1
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}
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||||
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|
||||
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{
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||||
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||||
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|
||||
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|
||||
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|
||||
},
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{
|
||||
"localized_name": "height",
|
||||
"name": "height",
|
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||||
},
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{
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"name": "batch_size",
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||||
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"links": [
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285
|
||||
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}
|
||||
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||||
"properties": {
|
||||
"Node name for S&R": "GetImageSize"
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||||
}
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||||
},
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{
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||||
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|
||||
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|
||||
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|
||||
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|
||||
-150
|
||||
],
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||||
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||||
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{
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||||
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||||
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|
||||
"link": 2
|
||||
},
|
||||
{
|
||||
"localized_name": "batch_index",
|
||||
"name": "batch_index",
|
||||
"type": "INT",
|
||||
"widget": {
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||||
"name": "batch_index"
|
||||
},
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"link": 286
|
||||
},
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||||
{
|
||||
"localized_name": "length",
|
||||
"name": "length",
|
||||
"type": "INT",
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||||
"widget": {
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||||
"name": "length"
|
||||
},
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||||
"link": null
|
||||
}
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||||
],
|
||||
"outputs": [
|
||||
{
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||||
"localized_name": "IMAGE",
|
||||
"name": "IMAGE",
|
||||
"type": "IMAGE",
|
||||
"links": [
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||||
5
|
||||
]
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}
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||||
],
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"properties": {
|
||||
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},
|
||||
"widgets_values": [
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||||
]
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|
||||
{
|
||||
"id": 99,
|
||||
"type": "ComfyMathExpression",
|
||||
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||||
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||||
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|
||||
],
|
||||
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||||
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||||
200
|
||||
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||||
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||||
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||||
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{
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||||
"label": "a",
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||||
"name": "values.a",
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"type": "FLOAT,INT",
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||||
"link": 284
|
||||
},
|
||||
{
|
||||
"label": "b",
|
||||
"localized_name": "values.b",
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||||
"name": "values.b",
|
||||
"shape": 7,
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||||
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"link": 285
|
||||
},
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{
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||||
"label": "c",
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||||
"localized_name": "values.c",
|
||||
"name": "values.c",
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||||
},
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{
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||||
"localized_name": "expression",
|
||||
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|
||||
"type": "STRING",
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||||
"widget": {
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||||
"name": "expression"
|
||||
},
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||||
"link": null
|
||||
}
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||||
],
|
||||
"outputs": [
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||||
{
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||||
"localized_name": "FLOAT",
|
||||
"name": "FLOAT",
|
||||
"type": "FLOAT",
|
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||||
},
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{
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"localized_name": "INT",
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||||
"name": "INT",
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||||
"type": "INT",
|
||||
"links": [
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||||
286
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||||
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||||
}
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||||
],
|
||||
"properties": {
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||||
"Node name for S&R": "ComfyMathExpression"
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||||
},
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||||
"widgets_values": [
|
||||
"min(max(int(a if a >= 0 else b + a), 0), b - 1)"
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||||
]
|
||||
},
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||||
{
|
||||
"id": 100,
|
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"type": "PrimitiveInt",
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||||
"pos": [
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||||
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||||
],
|
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||||
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||||
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||||
],
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|
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||||
"mode": 0,
|
||||
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{
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|
||||
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||||
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}
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{
|
||||
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|
||||
"name": "INT",
|
||||
"type": "INT",
|
||||
"links": [
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||||
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|
||||
]
|
||||
}
|
||||
],
|
||||
"properties": {
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||||
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|
||||
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||||
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|
||||
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||||
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||||
]
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||||
}
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||||
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||||
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|
||||
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{
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|
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|
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|
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|
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||||
{
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|
||||
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||||
{
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||||
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|
||||
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|
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
{
|
||||
"id": 285,
|
||||
"origin_id": 2,
|
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"origin_slot": 2,
|
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|
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|
||||
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|
||||
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|
||||
{
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
}
|
||||
],
|
||||
"extra": {},
|
||||
"category": "Video Tools",
|
||||
"description": "Extracts one image frame from a video at a chosen index, with optional trim and FPS control."
|
||||
}
|
||||
]
|
||||
},
|
||||
"extra": {
|
||||
"ds": {
|
||||
"scale": 1.197015527856339,
|
||||
"offset": [
|
||||
-168.76833554248222,
|
||||
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|
||||
]
|
||||
},
|
||||
"frontendVersion": "1.42.8"
|
||||
}
|
||||
}
|
||||
File diff suppressed because it is too large
Load Diff
2050
blueprints/Image Edit (Flux.2 Dev).json
Normal file
2050
blueprints/Image Edit (Flux.2 Dev).json
Normal file
File diff suppressed because it is too large
Load Diff
1947
blueprints/Image Edit (Qwen 2509).json
Normal file
1947
blueprints/Image Edit (Qwen 2509).json
Normal file
File diff suppressed because it is too large
Load Diff
714
blueprints/Image Segmentation (SAM3).json
Normal file
714
blueprints/Image Segmentation (SAM3).json
Normal file
@ -0,0 +1,714 @@
|
||||
{
|
||||
"revision": 0,
|
||||
"last_node_id": 99,
|
||||
"last_link_id": 0,
|
||||
"nodes": [
|
||||
{
|
||||
"id": 99,
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}
|
||||
],
|
||||
"groups": [],
|
||||
"links": [
|
||||
{
|
||||
"id": 237,
|
||||
"origin_id": 77,
|
||||
"origin_slot": 0,
|
||||
"target_id": 75,
|
||||
"target_slot": 0,
|
||||
"type": "MODEL"
|
||||
},
|
||||
{
|
||||
"id": 200,
|
||||
"origin_id": 78,
|
||||
"origin_slot": 0,
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||||
"target_id": 75,
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||||
"target_slot": 2,
|
||||
"type": "CONDITIONING"
|
||||
},
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||||
{
|
||||
"id": 240,
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||||
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"origin_slot": 1,
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"target_slot": 0,
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||||
"type": "CLIP"
|
||||
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||||
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||||
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||||
},
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{
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||||
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||||
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||||
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||||
"target_id": -20,
|
||||
"target_slot": 1,
|
||||
"type": "BOUNDING_BOX"
|
||||
},
|
||||
{
|
||||
"id": 264,
|
||||
"origin_id": -10,
|
||||
"origin_slot": 0,
|
||||
"target_id": 75,
|
||||
"target_slot": 1,
|
||||
"type": "IMAGE"
|
||||
},
|
||||
{
|
||||
"id": 265,
|
||||
"origin_id": -10,
|
||||
"origin_slot": 1,
|
||||
"target_id": 78,
|
||||
"target_slot": 1,
|
||||
"type": "STRING"
|
||||
},
|
||||
{
|
||||
"id": 266,
|
||||
"origin_id": -10,
|
||||
"origin_slot": 2,
|
||||
"target_id": 75,
|
||||
"target_slot": 3,
|
||||
"type": "BOUNDING_BOX"
|
||||
},
|
||||
{
|
||||
"id": 267,
|
||||
"origin_id": -10,
|
||||
"origin_slot": 3,
|
||||
"target_id": 75,
|
||||
"target_slot": 4,
|
||||
"type": "STRING"
|
||||
},
|
||||
{
|
||||
"id": 268,
|
||||
"origin_id": -10,
|
||||
"origin_slot": 4,
|
||||
"target_id": 75,
|
||||
"target_slot": 5,
|
||||
"type": "STRING"
|
||||
},
|
||||
{
|
||||
"id": 269,
|
||||
"origin_id": -10,
|
||||
"origin_slot": 5,
|
||||
"target_id": 75,
|
||||
"target_slot": 6,
|
||||
"type": "FLOAT"
|
||||
},
|
||||
{
|
||||
"id": 270,
|
||||
"origin_id": -10,
|
||||
"origin_slot": 6,
|
||||
"target_id": 75,
|
||||
"target_slot": 7,
|
||||
"type": "INT"
|
||||
},
|
||||
{
|
||||
"id": 271,
|
||||
"origin_id": -10,
|
||||
"origin_slot": 7,
|
||||
"target_id": 75,
|
||||
"target_slot": 8,
|
||||
"type": "BOOLEAN"
|
||||
},
|
||||
{
|
||||
"id": 272,
|
||||
"origin_id": -10,
|
||||
"origin_slot": 8,
|
||||
"target_id": 77,
|
||||
"target_slot": 0,
|
||||
"type": "COMBO"
|
||||
}
|
||||
],
|
||||
"extra": {},
|
||||
"category": "Image Tools/Image Segmentation",
|
||||
"description": "Segments images into masks using Meta SAM3 from text prompts, points, or boxes."
|
||||
}
|
||||
]
|
||||
},
|
||||
"extra": {
|
||||
"ue_links": []
|
||||
}
|
||||
}
|
||||
@ -2028,7 +2028,7 @@
|
||||
"workflowRendererVersion": "LG"
|
||||
},
|
||||
"category": "Video generation and editing/Image to video",
|
||||
"description": "Generates video from an image and text prompt using Wan 2.2, supporting T2V and I2V."
|
||||
"description": "Image-to-video with Wan 2.2 using a start image plus text prompt to extend motion from the still frame."
|
||||
}
|
||||
]
|
||||
},
|
||||
|
||||
397
blueprints/Remove Background (BiRefNet).json
Normal file
397
blueprints/Remove Background (BiRefNet).json
Normal file
@ -0,0 +1,397 @@
|
||||
{
|
||||
"revision": 0,
|
||||
"last_node_id": 19,
|
||||
"last_link_id": 0,
|
||||
"nodes": [
|
||||
{
|
||||
"id": 19,
|
||||
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|
||||
"pos": [
|
||||
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|
||||
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||||
],
|
||||
"size": [
|
||||
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|
||||
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|
||||
],
|
||||
"flags": {},
|
||||
"order": 2,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"localized_name": "image",
|
||||
"name": "image",
|
||||
"type": "IMAGE",
|
||||
"link": null
|
||||
},
|
||||
{
|
||||
"name": "bg_removal_name",
|
||||
"type": "COMBO",
|
||||
"widget": {
|
||||
"name": "bg_removal_name"
|
||||
},
|
||||
"link": null
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"localized_name": "IMAGE",
|
||||
"name": "IMAGE",
|
||||
"type": "IMAGE",
|
||||
"links": []
|
||||
},
|
||||
{
|
||||
"name": "mask",
|
||||
"type": "MASK",
|
||||
"links": []
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"proxyWidgets": [
|
||||
[
|
||||
"14",
|
||||
"bg_removal_name"
|
||||
]
|
||||
]
|
||||
},
|
||||
"widgets_values": [],
|
||||
"title": "Remove Background (BiRefNet)"
|
||||
}
|
||||
],
|
||||
"links": [],
|
||||
"version": 0.4,
|
||||
"definitions": {
|
||||
"subgraphs": [
|
||||
{
|
||||
"id": "5b40ca21-ba1a-41d5-b403-4d2d7acdc195",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"revision": 0,
|
||||
"config": {},
|
||||
"name": "Remove Background (BiRefNet)",
|
||||
"description": "Removes or replaces image backgrounds using BiRefNet segmentation and alpha compositing.",
|
||||
"inputNode": {
|
||||
"id": -10,
|
||||
"bounding": [
|
||||
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|
||||
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|
||||
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|
||||
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||||
]
|
||||
},
|
||||
"outputNode": {
|
||||
"id": -20,
|
||||
"bounding": [
|
||||
-6169.049695722246,
|
||||
1475.2619799128663,
|
||||
128,
|
||||
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||||
]
|
||||
},
|
||||
"inputs": [
|
||||
{
|
||||
"id": "7bc321cd-df31-4c39-aaf7-7f0d01326189",
|
||||
"name": "image",
|
||||
"type": "IMAGE",
|
||||
"linkIds": [
|
||||
5,
|
||||
7
|
||||
],
|
||||
"localized_name": "image",
|
||||
"pos": [
|
||||
-6601.620008222246,
|
||||
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||||
]
|
||||
},
|
||||
{
|
||||
"id": "e89d2cd8-daa3-4e29-8a69-851db85072cb",
|
||||
"name": "bg_removal_name",
|
||||
"type": "COMBO",
|
||||
"linkIds": [
|
||||
12
|
||||
],
|
||||
"pos": [
|
||||
-6601.620008222246,
|
||||
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|
||||
]
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"id": "16e7863c-4c38-46c2-aa74-e82991fbfe8d",
|
||||
"name": "IMAGE",
|
||||
"type": "IMAGE",
|
||||
"linkIds": [
|
||||
8
|
||||
],
|
||||
"localized_name": "IMAGE",
|
||||
"pos": [
|
||||
-6145.049695722246,
|
||||
1499.2619799128663
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": "f7240c19-5b80-406e-a8e2-9b12440ee2d6",
|
||||
"name": "mask",
|
||||
"type": "MASK",
|
||||
"linkIds": [
|
||||
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||||
],
|
||||
"pos": [
|
||||
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|
||||
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||||
]
|
||||
}
|
||||
],
|
||||
"widgets": [],
|
||||
"nodes": [
|
||||
{
|
||||
"id": 13,
|
||||
"type": "RemoveBackground",
|
||||
"pos": [
|
||||
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|
||||
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||||
],
|
||||
"size": [
|
||||
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|
||||
72
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||||
],
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||||
"flags": {},
|
||||
"order": 0,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"localized_name": "image",
|
||||
"name": "image",
|
||||
"type": "IMAGE",
|
||||
"link": 5
|
||||
},
|
||||
{
|
||||
"localized_name": "bg_removal_model",
|
||||
"name": "bg_removal_model",
|
||||
"type": "BACKGROUND_REMOVAL",
|
||||
"link": 3
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"localized_name": "mask",
|
||||
"name": "mask",
|
||||
"type": "MASK",
|
||||
"links": [
|
||||
4,
|
||||
11
|
||||
]
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "RemoveBackground"
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": 14,
|
||||
"type": "LoadBackgroundRemovalModel",
|
||||
"pos": [
|
||||
-6540.534070722246,
|
||||
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||||
],
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||||
"size": [
|
||||
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|
||||
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||||
],
|
||||
"flags": {},
|
||||
"order": 1,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"localized_name": "bg_removal_name",
|
||||
"name": "bg_removal_name",
|
||||
"type": "COMBO",
|
||||
"widget": {
|
||||
"name": "bg_removal_name"
|
||||
},
|
||||
"link": 12
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"localized_name": "bg_model",
|
||||
"name": "bg_model",
|
||||
"type": "BACKGROUND_REMOVAL",
|
||||
"links": [
|
||||
3
|
||||
]
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "LoadBackgroundRemovalModel",
|
||||
"models": [
|
||||
{
|
||||
"name": "birefnet.safetensors",
|
||||
"url": "https://huggingface.co/Comfy-Org/BiRefNet/resolve/main/background_removal/birefnet.safetensors",
|
||||
"directory": "background_removal"
|
||||
}
|
||||
]
|
||||
},
|
||||
"widgets_values": [
|
||||
"birefnet.safetensors"
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 15,
|
||||
"type": "InvertMask",
|
||||
"pos": [
|
||||
-6532.446160529669,
|
||||
1571.1111286839914
|
||||
],
|
||||
"size": [
|
||||
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|
||||
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|
||||
],
|
||||
"flags": {},
|
||||
"order": 2,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"localized_name": "mask",
|
||||
"name": "mask",
|
||||
"type": "MASK",
|
||||
"link": 4
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"localized_name": "MASK",
|
||||
"name": "MASK",
|
||||
"type": "MASK",
|
||||
"links": [
|
||||
6
|
||||
]
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "InvertMask"
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": 16,
|
||||
"type": "JoinImageWithAlpha",
|
||||
"pos": [
|
||||
-6527.4370171636665,
|
||||
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|
||||
],
|
||||
"size": [
|
||||
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|
||||
72
|
||||
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|
||||
"flags": {},
|
||||
"order": 3,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"localized_name": "image",
|
||||
"name": "image",
|
||||
"type": "IMAGE",
|
||||
"link": 7
|
||||
},
|
||||
{
|
||||
"localized_name": "alpha",
|
||||
"name": "alpha",
|
||||
"type": "MASK",
|
||||
"link": 6
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"localized_name": "IMAGE",
|
||||
"name": "IMAGE",
|
||||
"type": "IMAGE",
|
||||
"links": [
|
||||
8
|
||||
]
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "JoinImageWithAlpha"
|
||||
}
|
||||
}
|
||||
],
|
||||
"groups": [],
|
||||
"links": [
|
||||
{
|
||||
"id": 3,
|
||||
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|
||||
"origin_slot": 0,
|
||||
"target_id": 13,
|
||||
"target_slot": 1,
|
||||
"type": "BACKGROUND_REMOVAL"
|
||||
},
|
||||
{
|
||||
"id": 4,
|
||||
"origin_id": 13,
|
||||
"origin_slot": 0,
|
||||
"target_id": 15,
|
||||
"target_slot": 0,
|
||||
"type": "MASK"
|
||||
},
|
||||
{
|
||||
"id": 6,
|
||||
"origin_id": 15,
|
||||
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|
||||
"target_id": 16,
|
||||
"target_slot": 1,
|
||||
"type": "MASK"
|
||||
},
|
||||
{
|
||||
"id": 5,
|
||||
"origin_id": -10,
|
||||
"origin_slot": 0,
|
||||
"target_id": 13,
|
||||
"target_slot": 0,
|
||||
"type": "IMAGE"
|
||||
},
|
||||
{
|
||||
"id": 7,
|
||||
"origin_id": -10,
|
||||
"origin_slot": 0,
|
||||
"target_id": 16,
|
||||
"target_slot": 0,
|
||||
"type": "IMAGE"
|
||||
},
|
||||
{
|
||||
"id": 8,
|
||||
"origin_id": 16,
|
||||
"origin_slot": 0,
|
||||
"target_id": -20,
|
||||
"target_slot": 0,
|
||||
"type": "IMAGE"
|
||||
},
|
||||
{
|
||||
"id": 11,
|
||||
"origin_id": 13,
|
||||
"origin_slot": 0,
|
||||
"target_id": -20,
|
||||
"target_slot": 1,
|
||||
"type": "MASK"
|
||||
},
|
||||
{
|
||||
"id": 12,
|
||||
"origin_id": -10,
|
||||
"origin_slot": 1,
|
||||
"target_id": 14,
|
||||
"target_slot": 0,
|
||||
"type": "COMBO"
|
||||
}
|
||||
],
|
||||
"extra": {},
|
||||
"category": "Image generation and editing/Background Removal"
|
||||
}
|
||||
]
|
||||
},
|
||||
"extra": {}
|
||||
}
|
||||
2112
blueprints/Text to Image (Ernie Image Turbo).json
Normal file
2112
blueprints/Text to Image (Ernie Image Turbo).json
Normal file
File diff suppressed because it is too large
Load Diff
2190
blueprints/Text to Image (Ernie Image).json
Normal file
2190
blueprints/Text to Image (Ernie Image).json
Normal file
File diff suppressed because it is too large
Load Diff
@ -1030,7 +1030,7 @@
|
||||
"workflowRendererVersion": "LG"
|
||||
},
|
||||
"category": "Image generation and editing/Text to image",
|
||||
"description": "Generates images from text prompts using Flux.1 [dev], Black Forest Labs' 12B diffusion model."
|
||||
"description": "Generates images from prompts using FLUX.1 [dev]: a 12B rectified-flow MMDiT with dual CLIP plus T5-XXL text encoders and guidance-distilled sampling for sharp prompt following versus classic DDPM diffusion."
|
||||
}
|
||||
]
|
||||
},
|
||||
|
||||
@ -1024,7 +1024,7 @@
|
||||
"workflowRendererVersion": "LG"
|
||||
},
|
||||
"category": "Image generation and editing/Text to image",
|
||||
"description": "Generates images from text prompts using Flux.1 Krea Dev, a Black Forest Labs × Krea collaboration variant."
|
||||
"description": "FLUX.1 Krea [dev] (Black Forest Labs × Krea): open-weight 12B rectified-flow text-to-image drop-in alongside FLUX.1 [dev], tuned away from overcooked saturation toward more natural diversity in people, realism, and style while keeping ecosystem compatibility."
|
||||
}
|
||||
]
|
||||
},
|
||||
|
||||
1870
blueprints/Text to Image (Flux.2 Dev).json
Normal file
1870
blueprints/Text to Image (Flux.2 Dev).json
Normal file
File diff suppressed because it is too large
Load Diff
1184
blueprints/Text to Image (Z-Image-Base).json
Normal file
1184
blueprints/Text to Image (Z-Image-Base).json
Normal file
File diff suppressed because it is too large
Load Diff
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@ -361,7 +396,7 @@
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||||
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|
||||
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|
||||
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|
||||
13
|
||||
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|
||||
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|
||||
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||||
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||||
"Node name for S&R": "ModelSamplingAuraFlow",
|
||||
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||||
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|
||||
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||||
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@ -740,7 +831,7 @@
|
||||
"widget": {
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||||
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|
||||
},
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||||
"link": null
|
||||
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|
||||
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||||
{
|
||||
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|
||||
@ -749,7 +840,7 @@
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||||
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||||
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||||
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||||
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||||
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||||
{
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||||
"localized_name": "cfg",
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||||
@ -800,9 +891,9 @@
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||||
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||||
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1132
blueprints/Text to Image.json
Normal file
1132
blueprints/Text to Image.json
Normal file
File diff suppressed because it is too large
Load Diff
827
blueprints/Video Segmentation (SAM3).json
Normal file
827
blueprints/Video Segmentation (SAM3).json
Normal file
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|
||||
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@ -1,21 +1,21 @@
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@ -76,31 +76,26 @@
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|
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|
||||
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|
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|
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|
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@ -109,12 +104,12 @@
|
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|
||||
"id": "8e8aa94a-647e-436d-8440-8ee4691864de",
|
||||
"id": "637913e7-0206-46ba-8ded-70ae3a7c2e19",
|
||||
"version": 1,
|
||||
"state": {
|
||||
"lastGroupId": 1,
|
||||
"lastNodeId": 84,
|
||||
"lastLinkId": 262,
|
||||
"lastNodeId": 97,
|
||||
"lastLinkId": 282,
|
||||
"lastRerouteId": 0
|
||||
},
|
||||
"revision": 0,
|
||||
@ -123,8 +118,8 @@
|
||||
"inputNode": {
|
||||
"id": -10,
|
||||
"bounding": [
|
||||
-6580,
|
||||
2649,
|
||||
-6810,
|
||||
2580,
|
||||
143.55859375,
|
||||
160
|
||||
]
|
||||
@ -132,8 +127,8 @@
|
||||
"outputNode": {
|
||||
"id": -20,
|
||||
"bounding": [
|
||||
-5720,
|
||||
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|
||||
-4770,
|
||||
2600,
|
||||
120,
|
||||
60
|
||||
]
|
||||
@ -149,8 +144,8 @@
|
||||
"localized_name": "video",
|
||||
"label": "Before Video",
|
||||
"pos": [
|
||||
-6456.44140625,
|
||||
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|
||||
-6686.44140625,
|
||||
2600
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -163,8 +158,8 @@
|
||||
"localized_name": "video_1",
|
||||
"label": "After Video",
|
||||
"pos": [
|
||||
-6456.44140625,
|
||||
2689
|
||||
-6686.44140625,
|
||||
2620
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -175,8 +170,8 @@
|
||||
259
|
||||
],
|
||||
"pos": [
|
||||
-6456.44140625,
|
||||
2709
|
||||
-6686.44140625,
|
||||
2640
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -187,8 +182,8 @@
|
||||
260
|
||||
],
|
||||
"pos": [
|
||||
-6456.44140625,
|
||||
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|
||||
-6686.44140625,
|
||||
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|
||||
]
|
||||
},
|
||||
{
|
||||
@ -199,8 +194,8 @@
|
||||
261
|
||||
],
|
||||
"pos": [
|
||||
-6456.44140625,
|
||||
2749
|
||||
-6686.44140625,
|
||||
2680
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -211,8 +206,8 @@
|
||||
262
|
||||
],
|
||||
"pos": [
|
||||
-6456.44140625,
|
||||
2769
|
||||
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|
||||
2700
|
||||
]
|
||||
}
|
||||
],
|
||||
@ -226,8 +221,8 @@
|
||||
],
|
||||
"localized_name": "VIDEO",
|
||||
"pos": [
|
||||
-5700,
|
||||
2679
|
||||
-4750,
|
||||
2620
|
||||
]
|
||||
}
|
||||
],
|
||||
@ -238,11 +233,11 @@
|
||||
"type": "GetVideoComponents",
|
||||
"pos": [
|
||||
-6390,
|
||||
2560
|
||||
2600
|
||||
],
|
||||
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|
||||
193.530859375,
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||||
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|
||||
230,
|
||||
120
|
||||
],
|
||||
"flags": {},
|
||||
"order": 1,
|
||||
@ -278,9 +273,9 @@
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "GetVideoComponents",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.13.0",
|
||||
"Node name for S&R": "GetVideoComponents"
|
||||
"ver": "0.13.0"
|
||||
}
|
||||
},
|
||||
{
|
||||
@ -291,8 +286,8 @@
|
||||
2420
|
||||
],
|
||||
"size": [
|
||||
193.530859375,
|
||||
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|
||||
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|
||||
120
|
||||
],
|
||||
"flags": {},
|
||||
"order": 0,
|
||||
@ -332,21 +327,254 @@
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "GetVideoComponents",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.13.0",
|
||||
"Node name for S&R": "GetVideoComponents"
|
||||
"ver": "0.13.0"
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": 90,
|
||||
"type": "GetImageSize",
|
||||
"pos": [
|
||||
-6390,
|
||||
3030
|
||||
],
|
||||
"size": [
|
||||
230,
|
||||
120
|
||||
],
|
||||
"flags": {},
|
||||
"order": 4,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"localized_name": "image",
|
||||
"name": "image",
|
||||
"type": "IMAGE",
|
||||
"link": 266
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"localized_name": "width",
|
||||
"name": "width",
|
||||
"type": "INT",
|
||||
"links": [
|
||||
274
|
||||
]
|
||||
},
|
||||
{
|
||||
"localized_name": "height",
|
||||
"name": "height",
|
||||
"type": "INT",
|
||||
"links": [
|
||||
276
|
||||
]
|
||||
},
|
||||
{
|
||||
"localized_name": "batch_size",
|
||||
"name": "batch_size",
|
||||
"type": "INT",
|
||||
"links": null
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "GetImageSize"
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": 80,
|
||||
"type": "CreateVideo",
|
||||
"pos": [
|
||||
-5190,
|
||||
2420
|
||||
],
|
||||
"size": [
|
||||
270,
|
||||
130
|
||||
],
|
||||
"flags": {},
|
||||
"order": 3,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"localized_name": "images",
|
||||
"name": "images",
|
||||
"type": "IMAGE",
|
||||
"link": 282
|
||||
},
|
||||
{
|
||||
"localized_name": "audio",
|
||||
"name": "audio",
|
||||
"shape": 7,
|
||||
"type": "AUDIO",
|
||||
"link": 251
|
||||
},
|
||||
{
|
||||
"localized_name": "fps",
|
||||
"name": "fps",
|
||||
"type": "FLOAT",
|
||||
"widget": {
|
||||
"name": "fps"
|
||||
},
|
||||
"link": 252
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"localized_name": "VIDEO",
|
||||
"name": "VIDEO",
|
||||
"type": "VIDEO",
|
||||
"links": [
|
||||
255
|
||||
]
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "CreateVideo",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.13.0"
|
||||
},
|
||||
"widgets_values": [
|
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30
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 95,
|
||||
"type": "ComfyMathExpression",
|
||||
"pos": [
|
||||
-6040,
|
||||
3020
|
||||
],
|
||||
"size": [
|
||||
400,
|
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200
|
||||
],
|
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"flags": {},
|
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"order": 5,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"label": "a",
|
||||
"localized_name": "values.a",
|
||||
"name": "values.a",
|
||||
"type": "FLOAT,INT",
|
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"link": 274
|
||||
},
|
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{
|
||||
"label": "b",
|
||||
"localized_name": "values.b",
|
||||
"name": "values.b",
|
||||
"shape": 7,
|
||||
"type": "FLOAT,INT",
|
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"link": null
|
||||
},
|
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{
|
||||
"localized_name": "expression",
|
||||
"name": "expression",
|
||||
"type": "STRING",
|
||||
"widget": {
|
||||
"name": "expression"
|
||||
},
|
||||
"link": null
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"localized_name": "FLOAT",
|
||||
"name": "FLOAT",
|
||||
"type": "FLOAT",
|
||||
"links": null
|
||||
},
|
||||
{
|
||||
"localized_name": "INT",
|
||||
"name": "INT",
|
||||
"type": "INT",
|
||||
"links": [
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279
|
||||
]
|
||||
}
|
||||
],
|
||||
"properties": {
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||||
"Node name for S&R": "ComfyMathExpression"
|
||||
},
|
||||
"widgets_values": [
|
||||
"a & ~1"
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 96,
|
||||
"type": "ComfyMathExpression",
|
||||
"pos": [
|
||||
-6040,
|
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3290
|
||||
],
|
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"size": [
|
||||
400,
|
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200
|
||||
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|
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"flags": {},
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"order": 6,
|
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"mode": 0,
|
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"inputs": [
|
||||
{
|
||||
"label": "a",
|
||||
"localized_name": "values.a",
|
||||
"name": "values.a",
|
||||
"type": "FLOAT,INT",
|
||||
"link": 276
|
||||
},
|
||||
{
|
||||
"label": "b",
|
||||
"localized_name": "values.b",
|
||||
"name": "values.b",
|
||||
"shape": 7,
|
||||
"type": "FLOAT,INT",
|
||||
"link": null
|
||||
},
|
||||
{
|
||||
"localized_name": "expression",
|
||||
"name": "expression",
|
||||
"type": "STRING",
|
||||
"widget": {
|
||||
"name": "expression"
|
||||
},
|
||||
"link": null
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"localized_name": "FLOAT",
|
||||
"name": "FLOAT",
|
||||
"type": "FLOAT",
|
||||
"links": null
|
||||
},
|
||||
{
|
||||
"localized_name": "INT",
|
||||
"name": "INT",
|
||||
"type": "INT",
|
||||
"links": [
|
||||
280
|
||||
]
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "ComfyMathExpression"
|
||||
},
|
||||
"widgets_values": [
|
||||
"a & ~1"
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 79,
|
||||
"type": "ImageStitch",
|
||||
"pos": [
|
||||
-6390,
|
||||
2700
|
||||
2780
|
||||
],
|
||||
"size": [
|
||||
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|
||||
150
|
||||
160
|
||||
],
|
||||
"flags": {},
|
||||
"order": 2,
|
||||
@ -408,14 +636,15 @@
|
||||
"name": "IMAGE",
|
||||
"type": "IMAGE",
|
||||
"links": [
|
||||
250
|
||||
266,
|
||||
281
|
||||
]
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "ImageStitch",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.13.0",
|
||||
"Node name for S&R": "ImageStitch"
|
||||
"ver": "0.13.0"
|
||||
},
|
||||
"widgets_values": [
|
||||
"right",
|
||||
@ -425,60 +654,91 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 80,
|
||||
"type": "CreateVideo",
|
||||
"id": 97,
|
||||
"type": "ResizeImageMaskNode",
|
||||
"pos": [
|
||||
-6040,
|
||||
2610
|
||||
-5560,
|
||||
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|
||||
],
|
||||
"size": [
|
||||
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|
||||
78
|
||||
160
|
||||
],
|
||||
"flags": {},
|
||||
"order": 3,
|
||||
"order": 7,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"localized_name": "images",
|
||||
"name": "images",
|
||||
"type": "IMAGE",
|
||||
"link": 250
|
||||
"localized_name": "input",
|
||||
"name": "input",
|
||||
"type": "IMAGE,MASK",
|
||||
"link": 281
|
||||
},
|
||||
{
|
||||
"localized_name": "audio",
|
||||
"name": "audio",
|
||||
"shape": 7,
|
||||
"type": "AUDIO",
|
||||
"link": 251
|
||||
},
|
||||
{
|
||||
"localized_name": "fps",
|
||||
"name": "fps",
|
||||
"type": "FLOAT",
|
||||
"localized_name": "resize_type",
|
||||
"name": "resize_type",
|
||||
"type": "COMFY_DYNAMICCOMBO_V3",
|
||||
"widget": {
|
||||
"name": "fps"
|
||||
"name": "resize_type"
|
||||
},
|
||||
"link": 252
|
||||
"link": null
|
||||
},
|
||||
{
|
||||
"localized_name": "width",
|
||||
"name": "resize_type.width",
|
||||
"type": "INT",
|
||||
"widget": {
|
||||
"name": "resize_type.width"
|
||||
},
|
||||
"link": 279
|
||||
},
|
||||
{
|
||||
"localized_name": "height",
|
||||
"name": "resize_type.height",
|
||||
"type": "INT",
|
||||
"widget": {
|
||||
"name": "resize_type.height"
|
||||
},
|
||||
"link": 280
|
||||
},
|
||||
{
|
||||
"localized_name": "crop",
|
||||
"name": "resize_type.crop",
|
||||
"type": "COMBO",
|
||||
"widget": {
|
||||
"name": "resize_type.crop"
|
||||
},
|
||||
"link": null
|
||||
},
|
||||
{
|
||||
"localized_name": "scale_method",
|
||||
"name": "scale_method",
|
||||
"type": "COMBO",
|
||||
"widget": {
|
||||
"name": "scale_method"
|
||||
},
|
||||
"link": null
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"localized_name": "VIDEO",
|
||||
"name": "VIDEO",
|
||||
"type": "VIDEO",
|
||||
"localized_name": "resized",
|
||||
"name": "resized",
|
||||
"type": "*",
|
||||
"links": [
|
||||
255
|
||||
282
|
||||
]
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.13.0",
|
||||
"Node name for S&R": "CreateVideo"
|
||||
"Node name for S&R": "ResizeImageMaskNode"
|
||||
},
|
||||
"widgets_values": [
|
||||
30
|
||||
"scale dimensions",
|
||||
512,
|
||||
512,
|
||||
"center",
|
||||
"area"
|
||||
]
|
||||
}
|
||||
],
|
||||
@ -500,14 +760,6 @@
|
||||
"target_slot": 1,
|
||||
"type": "IMAGE"
|
||||
},
|
||||
{
|
||||
"id": 250,
|
||||
"origin_id": 79,
|
||||
"origin_slot": 0,
|
||||
"target_id": 80,
|
||||
"target_slot": 0,
|
||||
"type": "IMAGE"
|
||||
},
|
||||
{
|
||||
"id": 251,
|
||||
"origin_id": 77,
|
||||
@ -579,6 +831,62 @@
|
||||
"target_id": 79,
|
||||
"target_slot": 5,
|
||||
"type": "COMBO"
|
||||
},
|
||||
{
|
||||
"id": 266,
|
||||
"origin_id": 79,
|
||||
"origin_slot": 0,
|
||||
"target_id": 90,
|
||||
"target_slot": 0,
|
||||
"type": "IMAGE"
|
||||
},
|
||||
{
|
||||
"id": 274,
|
||||
"origin_id": 90,
|
||||
"origin_slot": 0,
|
||||
"target_id": 95,
|
||||
"target_slot": 0,
|
||||
"type": "INT"
|
||||
},
|
||||
{
|
||||
"id": 276,
|
||||
"origin_id": 90,
|
||||
"origin_slot": 1,
|
||||
"target_id": 96,
|
||||
"target_slot": 0,
|
||||
"type": "INT"
|
||||
},
|
||||
{
|
||||
"id": 279,
|
||||
"origin_id": 95,
|
||||
"origin_slot": 1,
|
||||
"target_id": 97,
|
||||
"target_slot": 2,
|
||||
"type": "INT"
|
||||
},
|
||||
{
|
||||
"id": 280,
|
||||
"origin_id": 96,
|
||||
"origin_slot": 1,
|
||||
"target_id": 97,
|
||||
"target_slot": 3,
|
||||
"type": "INT"
|
||||
},
|
||||
{
|
||||
"id": 281,
|
||||
"origin_id": 79,
|
||||
"origin_slot": 0,
|
||||
"target_id": 97,
|
||||
"target_slot": 0,
|
||||
"type": "IMAGE"
|
||||
},
|
||||
{
|
||||
"id": 282,
|
||||
"origin_id": 97,
|
||||
"origin_slot": 0,
|
||||
"target_id": 80,
|
||||
"target_slot": 0,
|
||||
"type": "IMAGE"
|
||||
}
|
||||
],
|
||||
"extra": {
|
||||
@ -588,5 +896,6 @@
|
||||
"description": "Stitches multiple video clips into a single sequential video file."
|
||||
}
|
||||
]
|
||||
}
|
||||
},
|
||||
"extra": {}
|
||||
}
|
||||
@ -1196,7 +1196,7 @@ def model_trange(*args, **kwargs):
|
||||
pbar.i1_time = time.time()
|
||||
pbar.set_postfix_str(" Model Initialization complete! ")
|
||||
elif pbar._i == 2:
|
||||
#bring forward the effective start time based the the diff between first and second iteration
|
||||
#bring forward the effective start time based the diff between first and second iteration
|
||||
#to attempt to remove load overhead from the final step rate estimate.
|
||||
pbar.start_t = pbar.i1_time - (time.time() - pbar.i1_time)
|
||||
pbar.set_postfix_str("")
|
||||
|
||||
@ -23,7 +23,7 @@ class BriaEditImageRequest(BaseModel):
|
||||
None,
|
||||
description="Mask image (black and white). Black areas will be preserved, white areas will be edited. "
|
||||
"If omitted, the edit applies to the entire image. "
|
||||
"The input image and the the input mask must be of the same size.",
|
||||
"The input image and the input mask must be of the same size.",
|
||||
)
|
||||
negative_prompt: str | None = Field(None)
|
||||
guidance_scale: float = Field(...)
|
||||
|
||||
@ -198,6 +198,62 @@ RECOMMENDED_PRESETS_SEEDREAM_4 = [
|
||||
("Custom", None, None),
|
||||
]
|
||||
|
||||
_PRESETS_SEEDREAM_1K = [
|
||||
("(1K) 1024x1024 (1:1)", 1024, 1024),
|
||||
("(1K) 864x1152 (3:4)", 864, 1152),
|
||||
("(1K) 1152x864 (4:3)", 1152, 864),
|
||||
("(1K) 1312x736 (16:9)", 1312, 736),
|
||||
("(1K) 736x1312 (9:16)", 736, 1312),
|
||||
("(1K) 832x1248 (2:3)", 832, 1248),
|
||||
("(1K) 1248x832 (3:2)", 1248, 832),
|
||||
("(1K) 1568x672 (21:9)", 1568, 672),
|
||||
]
|
||||
|
||||
_PRESETS_SEEDREAM_2K = [
|
||||
("(2K) 2048x2048 (1:1)", 2048, 2048),
|
||||
("(2K) 1728x2304 (3:4)", 1728, 2304),
|
||||
("(2K) 2304x1728 (4:3)", 2304, 1728),
|
||||
("(2K) 2848x1600 (16:9)", 2848, 1600),
|
||||
("(2K) 1600x2848 (9:16)", 1600, 2848),
|
||||
("(2K) 1664x2496 (2:3)", 1664, 2496),
|
||||
("(2K) 2496x1664 (3:2)", 2496, 1664),
|
||||
("(2K) 3136x1344 (21:9)", 3136, 1344),
|
||||
]
|
||||
|
||||
_PRESETS_SEEDREAM_3K = [
|
||||
("(3K) 3072x3072 (1:1)", 3072, 3072),
|
||||
("(3K) 2592x3456 (3:4)", 2592, 3456),
|
||||
("(3K) 3456x2592 (4:3)", 3456, 2592),
|
||||
("(3K) 4096x2304 (16:9)", 4096, 2304),
|
||||
("(3K) 2304x4096 (9:16)", 2304, 4096),
|
||||
("(3K) 2496x3744 (2:3)", 2496, 3744),
|
||||
("(3K) 3744x2496 (3:2)", 3744, 2496),
|
||||
("(3K) 4704x2016 (21:9)", 4704, 2016),
|
||||
]
|
||||
|
||||
_PRESETS_SEEDREAM_4K = [
|
||||
("(4K) 4096x4096 (1:1)", 4096, 4096),
|
||||
("(4K) 3520x4704 (3:4)", 3520, 4704),
|
||||
("(4K) 4704x3520 (4:3)", 4704, 3520),
|
||||
("(4K) 5504x3040 (16:9)", 5504, 3040),
|
||||
("(4K) 3040x5504 (9:16)", 3040, 5504),
|
||||
("(4K) 3328x4992 (2:3)", 3328, 4992),
|
||||
("(4K) 4992x3328 (3:2)", 4992, 3328),
|
||||
("(4K) 6240x2656 (21:9)", 6240, 2656),
|
||||
]
|
||||
|
||||
_CUSTOM_PRESET = [("Custom", None, None)]
|
||||
|
||||
RECOMMENDED_PRESETS_SEEDREAM_5_LITE = (
|
||||
_PRESETS_SEEDREAM_2K + _PRESETS_SEEDREAM_3K + _PRESETS_SEEDREAM_4K + _CUSTOM_PRESET
|
||||
)
|
||||
RECOMMENDED_PRESETS_SEEDREAM_4_5 = (
|
||||
_PRESETS_SEEDREAM_2K + _PRESETS_SEEDREAM_4K + _CUSTOM_PRESET
|
||||
)
|
||||
RECOMMENDED_PRESETS_SEEDREAM_4_0 = (
|
||||
_PRESETS_SEEDREAM_1K + _PRESETS_SEEDREAM_2K + _PRESETS_SEEDREAM_4K + _CUSTOM_PRESET
|
||||
)
|
||||
|
||||
# Seedance 2.0 reference video pixel count limits per model and output resolution.
|
||||
SEEDANCE2_REF_VIDEO_PIXEL_LIMITS = {
|
||||
"dreamina-seedance-2-0-260128": {
|
||||
|
||||
@ -596,6 +596,7 @@ class Flux2ProImageNode(IO.ComfyNode):
|
||||
depends_on=IO.PriceBadgeDepends(widgets=["width", "height"], inputs=["images"]),
|
||||
expr=cls.PRICE_BADGE_EXPR,
|
||||
),
|
||||
is_deprecated=True,
|
||||
)
|
||||
|
||||
@classmethod
|
||||
@ -674,6 +675,175 @@ class Flux2MaxImageNode(Flux2ProImageNode):
|
||||
"""
|
||||
|
||||
|
||||
_FLUX2_MODEL_ENDPOINTS = {
|
||||
"Flux.2 [pro]": "/proxy/bfl/flux-2-pro/generate",
|
||||
"Flux.2 [max]": "/proxy/bfl/flux-2-max/generate",
|
||||
}
|
||||
|
||||
|
||||
def _flux2_model_inputs():
|
||||
return [
|
||||
IO.Int.Input(
|
||||
"width",
|
||||
default=1024,
|
||||
min=256,
|
||||
max=2048,
|
||||
step=32,
|
||||
),
|
||||
IO.Int.Input(
|
||||
"height",
|
||||
default=768,
|
||||
min=256,
|
||||
max=2048,
|
||||
step=32,
|
||||
),
|
||||
IO.Autogrow.Input(
|
||||
"images",
|
||||
template=IO.Autogrow.TemplateNames(
|
||||
IO.Image.Input("image"),
|
||||
names=[f"image_{i}" for i in range(1, 9)],
|
||||
min=0,
|
||||
),
|
||||
tooltip="Optional reference image(s) for image-to-image generation. Up to 8 images.",
|
||||
),
|
||||
]
|
||||
|
||||
|
||||
class Flux2ImageNode(IO.ComfyNode):
|
||||
|
||||
@classmethod
|
||||
def define_schema(cls) -> IO.Schema:
|
||||
return IO.Schema(
|
||||
node_id="Flux2ImageNode",
|
||||
display_name="Flux.2 Image",
|
||||
category="api node/image/BFL",
|
||||
description="Generate images via Flux.2 [pro] or Flux.2 [max] from a prompt and optional reference images.",
|
||||
inputs=[
|
||||
IO.String.Input(
|
||||
"prompt",
|
||||
multiline=True,
|
||||
default="",
|
||||
tooltip="Prompt for the image generation or edit",
|
||||
),
|
||||
IO.DynamicCombo.Input(
|
||||
"model",
|
||||
options=[
|
||||
IO.DynamicCombo.Option("Flux.2 [pro]", _flux2_model_inputs()),
|
||||
IO.DynamicCombo.Option("Flux.2 [max]", _flux2_model_inputs()),
|
||||
],
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=0,
|
||||
min=0,
|
||||
max=0xFFFFFFFFFFFFFFFF,
|
||||
control_after_generate=True,
|
||||
tooltip="The random seed used for creating the noise.",
|
||||
),
|
||||
],
|
||||
outputs=[IO.Image.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(
|
||||
depends_on=IO.PriceBadgeDepends(
|
||||
widgets=["model", "model.width", "model.height"],
|
||||
input_groups=["model.images"],
|
||||
),
|
||||
expr="""
|
||||
(
|
||||
$isMax := widgets.model = "flux.2 [max]";
|
||||
$MP := 1024 * 1024;
|
||||
$w := $lookup(widgets, "model.width");
|
||||
$h := $lookup(widgets, "model.height");
|
||||
$outMP := $max([1, $floor((($w * $h) + $MP - 1) / $MP)]);
|
||||
$outputCost := $isMax
|
||||
? (0.07 + 0.03 * ($outMP - 1))
|
||||
: (0.03 + 0.015 * ($outMP - 1));
|
||||
$refMin := $isMax ? 0.03 : 0.015;
|
||||
$refMax := $isMax ? 0.24 : 0.12;
|
||||
$hasRefs := $lookup(inputGroups, "model.images") > 0;
|
||||
$hasRefs
|
||||
? {
|
||||
"type": "range_usd",
|
||||
"min_usd": $outputCost + $refMin,
|
||||
"max_usd": $outputCost + $refMax,
|
||||
"format": { "approximate": true }
|
||||
}
|
||||
: {"type": "usd", "usd": $outputCost}
|
||||
)
|
||||
""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
prompt: str,
|
||||
model: dict,
|
||||
seed: int,
|
||||
) -> IO.NodeOutput:
|
||||
model_choice = model["model"]
|
||||
endpoint = _FLUX2_MODEL_ENDPOINTS[model_choice]
|
||||
width = model["width"]
|
||||
height = model["height"]
|
||||
images_dict = model.get("images") or {}
|
||||
|
||||
image_tensors: list[Input.Image] = [t for t in images_dict.values() if t is not None]
|
||||
n_images = sum(get_number_of_images(t) for t in image_tensors)
|
||||
if n_images > 8:
|
||||
raise ValueError("The current maximum number of supported images is 8.")
|
||||
|
||||
flat_tensors: list[torch.Tensor] = []
|
||||
for tensor in image_tensors:
|
||||
if len(tensor.shape) == 4:
|
||||
flat_tensors.extend(tensor[i] for i in range(tensor.shape[0]))
|
||||
else:
|
||||
flat_tensors.append(tensor)
|
||||
|
||||
reference_images: dict[str, str] = {}
|
||||
for idx, tensor in enumerate(flat_tensors):
|
||||
key_name = f"input_image_{idx + 1}" if idx else "input_image"
|
||||
reference_images[key_name] = tensor_to_base64_string(tensor, total_pixels=2048 * 2048)
|
||||
|
||||
initial_response = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(path=endpoint, method="POST"),
|
||||
response_model=BFLFluxProGenerateResponse,
|
||||
data=Flux2ProGenerateRequest(
|
||||
prompt=prompt,
|
||||
width=width,
|
||||
height=height,
|
||||
seed=seed,
|
||||
**reference_images,
|
||||
),
|
||||
)
|
||||
|
||||
def price_extractor(_r: BaseModel) -> float | None:
|
||||
return None if initial_response.cost is None else initial_response.cost / 100
|
||||
|
||||
response = await poll_op(
|
||||
cls,
|
||||
ApiEndpoint(initial_response.polling_url),
|
||||
response_model=BFLFluxStatusResponse,
|
||||
status_extractor=lambda r: r.status,
|
||||
progress_extractor=lambda r: r.progress,
|
||||
price_extractor=price_extractor,
|
||||
completed_statuses=[BFLStatus.ready],
|
||||
failed_statuses=[
|
||||
BFLStatus.request_moderated,
|
||||
BFLStatus.content_moderated,
|
||||
BFLStatus.error,
|
||||
BFLStatus.task_not_found,
|
||||
],
|
||||
queued_statuses=[],
|
||||
)
|
||||
return IO.NodeOutput(await download_url_to_image_tensor(response.result["sample"]))
|
||||
|
||||
|
||||
class BFLExtension(ComfyExtension):
|
||||
@override
|
||||
async def get_node_list(self) -> list[type[IO.ComfyNode]]:
|
||||
@ -685,6 +855,7 @@ class BFLExtension(ComfyExtension):
|
||||
FluxProFillNode,
|
||||
Flux2ProImageNode,
|
||||
Flux2MaxImageNode,
|
||||
Flux2ImageNode,
|
||||
]
|
||||
|
||||
|
||||
|
||||
@ -10,6 +10,9 @@ from comfy_api.latest import IO, ComfyExtension, Input
|
||||
from comfy_api_nodes.apis.bytedance import (
|
||||
RECOMMENDED_PRESETS,
|
||||
RECOMMENDED_PRESETS_SEEDREAM_4,
|
||||
RECOMMENDED_PRESETS_SEEDREAM_4_0,
|
||||
RECOMMENDED_PRESETS_SEEDREAM_4_5,
|
||||
RECOMMENDED_PRESETS_SEEDREAM_5_LITE,
|
||||
SEEDANCE2_PRICE_PER_1K_TOKENS,
|
||||
SEEDANCE2_REF_VIDEO_PIXEL_LIMITS,
|
||||
VIDEO_TASKS_EXECUTION_TIME,
|
||||
@ -68,6 +71,12 @@ SEEDREAM_MODELS = {
|
||||
"seedream-4-0-250828": "seedream-4-0-250828",
|
||||
}
|
||||
|
||||
SEEDREAM_PRESETS = {
|
||||
"seedream-5-0-260128": RECOMMENDED_PRESETS_SEEDREAM_5_LITE,
|
||||
"seedream-4-5-251128": RECOMMENDED_PRESETS_SEEDREAM_4_5,
|
||||
"seedream-4-0-250828": RECOMMENDED_PRESETS_SEEDREAM_4_0,
|
||||
}
|
||||
|
||||
# Long-running tasks endpoints(e.g., video)
|
||||
BYTEPLUS_TASK_ENDPOINT = "/proxy/byteplus/api/v3/contents/generations/tasks"
|
||||
BYTEPLUS_TASK_STATUS_ENDPOINT = "/proxy/byteplus/api/v3/contents/generations/tasks" # + /{task_id}
|
||||
@ -562,6 +571,7 @@ class ByteDanceSeedreamNode(IO.ComfyNode):
|
||||
)
|
||||
""",
|
||||
),
|
||||
is_deprecated=True,
|
||||
)
|
||||
|
||||
@classmethod
|
||||
@ -651,6 +661,226 @@ class ByteDanceSeedreamNode(IO.ComfyNode):
|
||||
return IO.NodeOutput(torch.cat([await download_url_to_image_tensor(i) for i in urls]))
|
||||
|
||||
|
||||
def _seedream_model_inputs(*, max_ref_images: int, presets: list):
|
||||
return [
|
||||
IO.Combo.Input(
|
||||
"size_preset",
|
||||
options=[label for label, _, _ in presets],
|
||||
tooltip="Pick a recommended size. Select Custom to use the width and height below.",
|
||||
),
|
||||
IO.Int.Input(
|
||||
"width",
|
||||
default=2048,
|
||||
min=1024,
|
||||
max=6240,
|
||||
step=2,
|
||||
tooltip="Custom width for image. Value is working only if `size_preset` is set to `Custom`",
|
||||
),
|
||||
IO.Int.Input(
|
||||
"height",
|
||||
default=2048,
|
||||
min=1024,
|
||||
max=4992,
|
||||
step=2,
|
||||
tooltip="Custom height for image. Value is working only if `size_preset` is set to `Custom`",
|
||||
),
|
||||
IO.Int.Input(
|
||||
"max_images",
|
||||
default=1,
|
||||
min=1,
|
||||
max=max_ref_images,
|
||||
step=1,
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
tooltip="Maximum number of images to generate. With 1, exactly one image is produced. "
|
||||
"With >1, the model generates between 1 and max_images related images "
|
||||
"(e.g., story scenes, character variations). "
|
||||
"Total images (input + generated) cannot exceed 15.",
|
||||
),
|
||||
IO.Autogrow.Input(
|
||||
"images",
|
||||
template=IO.Autogrow.TemplateNames(
|
||||
IO.Image.Input("image"),
|
||||
names=[f"image_{i}" for i in range(1, max_ref_images + 1)],
|
||||
min=0,
|
||||
),
|
||||
tooltip=f"Optional reference image(s) for image-to-image or multi-reference generation. "
|
||||
f"Up to {max_ref_images} images.",
|
||||
),
|
||||
IO.Boolean.Input(
|
||||
"fail_on_partial",
|
||||
default=False,
|
||||
tooltip="If enabled, abort execution if any requested images are missing or return an error.",
|
||||
advanced=True,
|
||||
),
|
||||
]
|
||||
|
||||
|
||||
class ByteDanceSeedreamNodeV2(IO.ComfyNode):
|
||||
|
||||
@classmethod
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="ByteDanceSeedreamNodeV2",
|
||||
display_name="ByteDance Seedream 4.5 & 5.0",
|
||||
category="api node/image/ByteDance",
|
||||
description="Unified text-to-image generation and precise single-sentence editing at up to 4K resolution.",
|
||||
inputs=[
|
||||
IO.String.Input(
|
||||
"prompt",
|
||||
multiline=True,
|
||||
default="",
|
||||
tooltip="Text prompt for creating or editing an image.",
|
||||
),
|
||||
IO.DynamicCombo.Input(
|
||||
"model",
|
||||
options=[
|
||||
IO.DynamicCombo.Option(
|
||||
"seedream 5.0 lite",
|
||||
_seedream_model_inputs(max_ref_images=14, presets=RECOMMENDED_PRESETS_SEEDREAM_5_LITE),
|
||||
),
|
||||
IO.DynamicCombo.Option(
|
||||
"seedream-4-5-251128",
|
||||
_seedream_model_inputs(max_ref_images=10, presets=RECOMMENDED_PRESETS_SEEDREAM_4_5),
|
||||
),
|
||||
IO.DynamicCombo.Option(
|
||||
"seedream-4-0-250828",
|
||||
_seedream_model_inputs(max_ref_images=10, presets=RECOMMENDED_PRESETS_SEEDREAM_4_0),
|
||||
),
|
||||
],
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=0,
|
||||
min=0,
|
||||
max=2147483647,
|
||||
step=1,
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
control_after_generate=True,
|
||||
tooltip="Seed to use for generation.",
|
||||
),
|
||||
IO.Boolean.Input(
|
||||
"watermark",
|
||||
default=False,
|
||||
tooltip='Whether to add an "AI generated" watermark to the image.',
|
||||
advanced=True,
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.Image.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(
|
||||
depends_on=IO.PriceBadgeDepends(widgets=["model"]),
|
||||
expr="""
|
||||
(
|
||||
$price := $contains(widgets.model, "5.0 lite") ? 0.035 :
|
||||
$contains(widgets.model, "4-5") ? 0.04 : 0.03;
|
||||
{
|
||||
"type":"usd",
|
||||
"usd": $price,
|
||||
"format": { "suffix":" x images/Run", "approximate": true }
|
||||
}
|
||||
)
|
||||
""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
prompt: str,
|
||||
model: dict,
|
||||
seed: int = 0,
|
||||
watermark: bool = False,
|
||||
) -> IO.NodeOutput:
|
||||
validate_string(prompt, strip_whitespace=True, min_length=1)
|
||||
model_id = SEEDREAM_MODELS[model["model"]]
|
||||
presets = SEEDREAM_PRESETS[model_id]
|
||||
|
||||
size_preset = model.get("size_preset", presets[0][0])
|
||||
width = model.get("width", 2048)
|
||||
height = model.get("height", 2048)
|
||||
max_images = model.get("max_images", 1)
|
||||
sequential_image_generation = "disabled" if max_images == 1 else "auto"
|
||||
images_dict = model.get("images") or {}
|
||||
fail_on_partial = model.get("fail_on_partial", False)
|
||||
|
||||
w = h = None
|
||||
for label, tw, th in presets:
|
||||
if label == size_preset:
|
||||
w, h = tw, th
|
||||
break
|
||||
if w is None or h is None:
|
||||
w, h = width, height
|
||||
|
||||
out_num_pixels = w * h
|
||||
mp_provided = out_num_pixels / 1_000_000.0
|
||||
if ("seedream-4-5" in model_id or "seedream-5-0" in model_id) and out_num_pixels < 3686400:
|
||||
raise ValueError(
|
||||
f"Minimum image resolution for the selected model is 3.68MP, but {mp_provided:.2f}MP provided."
|
||||
)
|
||||
if "seedream-4-0" in model_id and out_num_pixels < 921600:
|
||||
raise ValueError(
|
||||
f"Minimum image resolution that the selected model can generate is 0.92MP, "
|
||||
f"but {mp_provided:.2f}MP provided."
|
||||
)
|
||||
if out_num_pixels > 16_777_216:
|
||||
raise ValueError(
|
||||
f"Maximum image resolution for the selected model is 16.78MP, but {mp_provided:.2f}MP provided."
|
||||
)
|
||||
|
||||
image_tensors: list[Input.Image] = [t for t in images_dict.values() if t is not None]
|
||||
n_input_images = sum(get_number_of_images(t) for t in image_tensors)
|
||||
max_num_of_images = 14 if model_id == "seedream-5-0-260128" else 10
|
||||
if n_input_images > max_num_of_images:
|
||||
raise ValueError(
|
||||
f"Maximum of {max_num_of_images} reference images are supported, but {n_input_images} received."
|
||||
)
|
||||
if sequential_image_generation == "auto" and n_input_images + max_images > 15:
|
||||
raise ValueError(
|
||||
"The maximum number of generated images plus the number of reference images cannot exceed 15."
|
||||
)
|
||||
|
||||
reference_images_urls: list[str] = []
|
||||
if image_tensors:
|
||||
for tensor in image_tensors:
|
||||
validate_image_aspect_ratio(tensor, (1, 3), (3, 1))
|
||||
reference_images_urls = await upload_images_to_comfyapi(
|
||||
cls,
|
||||
image_tensors,
|
||||
max_images=n_input_images,
|
||||
mime_type="image/png",
|
||||
wait_label="Uploading reference images",
|
||||
)
|
||||
|
||||
response = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(path=BYTEPLUS_IMAGE_ENDPOINT, method="POST"),
|
||||
response_model=ImageTaskCreationResponse,
|
||||
data=Seedream4TaskCreationRequest(
|
||||
model=model_id,
|
||||
prompt=prompt,
|
||||
image=reference_images_urls,
|
||||
size=f"{w}x{h}",
|
||||
seed=seed,
|
||||
sequential_image_generation=sequential_image_generation,
|
||||
sequential_image_generation_options=Seedream4Options(max_images=max_images),
|
||||
watermark=watermark,
|
||||
),
|
||||
)
|
||||
if len(response.data) == 1:
|
||||
return IO.NodeOutput(await download_url_to_image_tensor(get_image_url_from_response(response)))
|
||||
urls = [str(d["url"]) for d in response.data if isinstance(d, dict) and "url" in d]
|
||||
if fail_on_partial and len(urls) < len(response.data):
|
||||
raise RuntimeError(f"Only {len(urls)} of {len(response.data)} images were generated before error.")
|
||||
return IO.NodeOutput(torch.cat([await download_url_to_image_tensor(i) for i in urls]))
|
||||
|
||||
|
||||
class ByteDanceTextToVideoNode(IO.ComfyNode):
|
||||
|
||||
@classmethod
|
||||
@ -2105,6 +2335,7 @@ class ByteDanceExtension(ComfyExtension):
|
||||
return [
|
||||
ByteDanceImageNode,
|
||||
ByteDanceSeedreamNode,
|
||||
ByteDanceSeedreamNodeV2,
|
||||
ByteDanceTextToVideoNode,
|
||||
ByteDanceImageToVideoNode,
|
||||
ByteDanceFirstLastFrameNode,
|
||||
|
||||
@ -162,6 +162,61 @@ class GrokImageNode(IO.ComfyNode):
|
||||
)
|
||||
|
||||
|
||||
_GROK_IMAGE_EDIT_ASPECT_RATIO_OPTIONS = [
|
||||
"auto",
|
||||
"1:1",
|
||||
"2:3",
|
||||
"3:2",
|
||||
"3:4",
|
||||
"4:3",
|
||||
"9:16",
|
||||
"16:9",
|
||||
"9:19.5",
|
||||
"19.5:9",
|
||||
"9:20",
|
||||
"20:9",
|
||||
"1:2",
|
||||
"2:1",
|
||||
]
|
||||
|
||||
|
||||
def _grok_image_edit_model_inputs(*, max_ref_images: int, with_aspect_ratio: bool):
|
||||
inputs = [
|
||||
IO.Autogrow.Input(
|
||||
"images",
|
||||
template=IO.Autogrow.TemplateNames(
|
||||
IO.Image.Input("image"),
|
||||
names=[f"image_{i}" for i in range(1, max_ref_images + 1)],
|
||||
min=1,
|
||||
),
|
||||
tooltip=(
|
||||
"Reference image to edit."
|
||||
if max_ref_images == 1
|
||||
else f"Reference image(s) to edit. Up to {max_ref_images} images."
|
||||
),
|
||||
),
|
||||
IO.Combo.Input("resolution", options=["1K", "2K"]),
|
||||
IO.Int.Input(
|
||||
"number_of_images",
|
||||
default=1,
|
||||
min=1,
|
||||
max=10,
|
||||
step=1,
|
||||
tooltip="Number of edited images to generate",
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
),
|
||||
]
|
||||
if with_aspect_ratio:
|
||||
inputs.append(
|
||||
IO.Combo.Input(
|
||||
"aspect_ratio",
|
||||
options=_GROK_IMAGE_EDIT_ASPECT_RATIO_OPTIONS,
|
||||
tooltip="Only allowed when multiple images are connected.",
|
||||
)
|
||||
)
|
||||
return inputs
|
||||
|
||||
|
||||
class GrokImageEditNode(IO.ComfyNode):
|
||||
|
||||
@classmethod
|
||||
@ -256,6 +311,7 @@ class GrokImageEditNode(IO.ComfyNode):
|
||||
)
|
||||
""",
|
||||
),
|
||||
is_deprecated=True,
|
||||
)
|
||||
|
||||
@classmethod
|
||||
@ -303,6 +359,143 @@ class GrokImageEditNode(IO.ComfyNode):
|
||||
)
|
||||
|
||||
|
||||
class GrokImageEditNodeV2(IO.ComfyNode):
|
||||
|
||||
@classmethod
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="GrokImageEditNodeV2",
|
||||
display_name="Grok Image Edit",
|
||||
category="api node/image/Grok",
|
||||
description="Modify an existing image based on a text prompt",
|
||||
inputs=[
|
||||
IO.String.Input(
|
||||
"prompt",
|
||||
multiline=True,
|
||||
default="",
|
||||
tooltip="The text prompt used to generate the image",
|
||||
),
|
||||
IO.DynamicCombo.Input(
|
||||
"model",
|
||||
options=[
|
||||
IO.DynamicCombo.Option(
|
||||
"grok-imagine-image-quality",
|
||||
_grok_image_edit_model_inputs(max_ref_images=3, with_aspect_ratio=True),
|
||||
),
|
||||
IO.DynamicCombo.Option(
|
||||
"grok-imagine-image-pro",
|
||||
_grok_image_edit_model_inputs(max_ref_images=1, with_aspect_ratio=False),
|
||||
),
|
||||
IO.DynamicCombo.Option(
|
||||
"grok-imagine-image",
|
||||
_grok_image_edit_model_inputs(max_ref_images=3, with_aspect_ratio=True),
|
||||
),
|
||||
],
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=0,
|
||||
min=0,
|
||||
max=2147483647,
|
||||
step=1,
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
control_after_generate=True,
|
||||
tooltip="Seed to determine if node should re-run; "
|
||||
"actual results are nondeterministic regardless of seed.",
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.Image.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(
|
||||
depends_on=IO.PriceBadgeDepends(
|
||||
widgets=["model", "model.resolution", "model.number_of_images"],
|
||||
),
|
||||
expr="""
|
||||
(
|
||||
$isQualityModel := widgets.model = "grok-imagine-image-quality";
|
||||
$isPro := $contains(widgets.model, "pro");
|
||||
$res := $lookup(widgets, "model.resolution");
|
||||
$n := $lookup(widgets, "model.number_of_images");
|
||||
$rate := $isQualityModel
|
||||
? ($res = "1k" ? 0.05 : 0.07)
|
||||
: ($isPro ? 0.07 : 0.02);
|
||||
$base := $isQualityModel ? 0.01 : 0.002;
|
||||
$output := $rate * $n;
|
||||
$isPro
|
||||
? {"type":"usd","usd": $base + $output}
|
||||
: {"type":"range_usd","min_usd": $base + $output, "max_usd": 3 * $base + $output}
|
||||
)
|
||||
""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
prompt: str,
|
||||
model: dict,
|
||||
seed: int,
|
||||
) -> IO.NodeOutput:
|
||||
validate_string(prompt, strip_whitespace=True, min_length=1)
|
||||
model_id = model["model"]
|
||||
resolution = model["resolution"]
|
||||
number_of_images = model["number_of_images"]
|
||||
images_dict = model.get("images") or {}
|
||||
aspect_ratio = model.get("aspect_ratio", "auto")
|
||||
|
||||
image_tensors: list[Input.Image] = [t for t in images_dict.values() if t is not None]
|
||||
n_images = sum(get_number_of_images(t) for t in image_tensors)
|
||||
if n_images < 1:
|
||||
raise ValueError("At least one image is required for editing.")
|
||||
if model_id == "grok-imagine-image-pro" and n_images > 1:
|
||||
raise ValueError("The pro model supports only 1 input image.")
|
||||
if model_id != "grok-imagine-image-pro" and n_images > 3:
|
||||
raise ValueError("A maximum of 3 input images is supported.")
|
||||
if aspect_ratio != "auto" and n_images == 1:
|
||||
raise ValueError(
|
||||
"Custom aspect ratio is only allowed when multiple images are connected to the image input."
|
||||
)
|
||||
|
||||
flat_tensors: list[torch.Tensor] = []
|
||||
for tensor in image_tensors:
|
||||
if len(tensor.shape) == 4:
|
||||
flat_tensors.extend(tensor[i] for i in range(tensor.shape[0]))
|
||||
else:
|
||||
flat_tensors.append(tensor)
|
||||
|
||||
response = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(path="/proxy/xai/v1/images/edits", method="POST"),
|
||||
data=ImageEditRequest(
|
||||
model=model_id,
|
||||
images=[
|
||||
InputUrlObject(url=f"data:image/png;base64,{tensor_to_base64_string(i)}") for i in flat_tensors
|
||||
],
|
||||
prompt=prompt,
|
||||
resolution=resolution.lower(),
|
||||
n=number_of_images,
|
||||
seed=seed,
|
||||
aspect_ratio=None if aspect_ratio == "auto" else aspect_ratio,
|
||||
),
|
||||
response_model=ImageGenerationResponse,
|
||||
price_extractor=_extract_grok_price,
|
||||
)
|
||||
if len(response.data) == 1:
|
||||
return IO.NodeOutput(await download_url_to_image_tensor(response.data[0].url))
|
||||
return IO.NodeOutput(
|
||||
torch.cat(
|
||||
[await download_url_to_image_tensor(i) for i in [str(d.url) for d in response.data if d.url]],
|
||||
)
|
||||
)
|
||||
|
||||
|
||||
class GrokVideoNode(IO.ComfyNode):
|
||||
|
||||
@classmethod
|
||||
@ -737,6 +930,7 @@ class GrokExtension(ComfyExtension):
|
||||
return [
|
||||
GrokImageNode,
|
||||
GrokImageEditNode,
|
||||
GrokImageEditNodeV2,
|
||||
GrokVideoNode,
|
||||
GrokVideoReferenceNode,
|
||||
GrokVideoEditNode,
|
||||
|
||||
@ -27,6 +27,7 @@ from comfy_api_nodes.util import (
|
||||
ApiEndpoint,
|
||||
download_url_to_bytesio,
|
||||
downscale_image_tensor,
|
||||
get_number_of_images,
|
||||
poll_op,
|
||||
sync_op,
|
||||
tensor_to_base64_string,
|
||||
@ -372,6 +373,7 @@ class OpenAIGPTImage1(IO.ComfyNode):
|
||||
display_name="OpenAI GPT Image 2",
|
||||
category="api node/image/OpenAI",
|
||||
description="Generates images synchronously via OpenAI's GPT Image endpoint.",
|
||||
is_deprecated=True,
|
||||
inputs=[
|
||||
IO.String.Input(
|
||||
"prompt",
|
||||
@ -640,6 +642,316 @@ class OpenAIGPTImage1(IO.ComfyNode):
|
||||
return IO.NodeOutput(await validate_and_cast_response(response))
|
||||
|
||||
|
||||
def _gpt_image_shared_inputs():
|
||||
"""Inputs shared by all GPT Image models (quality + reference images + mask)."""
|
||||
return [
|
||||
IO.Combo.Input(
|
||||
"quality",
|
||||
default="low",
|
||||
options=["low", "medium", "high"],
|
||||
tooltip="Image quality, affects cost and generation time.",
|
||||
),
|
||||
IO.Autogrow.Input(
|
||||
"images",
|
||||
template=IO.Autogrow.TemplateNames(
|
||||
IO.Image.Input("image"),
|
||||
names=[f"image_{i}" for i in range(1, 17)],
|
||||
min=0,
|
||||
),
|
||||
tooltip="Optional reference image(s) for image editing. Up to 16 images.",
|
||||
),
|
||||
IO.Mask.Input(
|
||||
"mask",
|
||||
optional=True,
|
||||
tooltip="Optional mask for inpainting (white areas will be replaced). "
|
||||
"Requires exactly one reference image.",
|
||||
),
|
||||
]
|
||||
|
||||
|
||||
def _gpt_image_legacy_model_inputs():
|
||||
"""Per-model widget set for legacy gpt-image-1 / gpt-image-1.5 (4 base sizes, transparent bg allowed)."""
|
||||
return [
|
||||
IO.Combo.Input(
|
||||
"size",
|
||||
default="auto",
|
||||
options=["auto", "1024x1024", "1024x1536", "1536x1024"],
|
||||
tooltip="Image size.",
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"background",
|
||||
default="auto",
|
||||
options=["auto", "opaque", "transparent"],
|
||||
tooltip="Return image with or without background.",
|
||||
),
|
||||
*_gpt_image_shared_inputs(),
|
||||
]
|
||||
|
||||
|
||||
class OpenAIGPTImageNodeV2(IO.ComfyNode):
|
||||
|
||||
@classmethod
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="OpenAIGPTImageNodeV2",
|
||||
display_name="OpenAI GPT Image 2",
|
||||
category="api node/image/OpenAI",
|
||||
description="Generates images via OpenAI's GPT Image endpoint.",
|
||||
inputs=[
|
||||
IO.String.Input(
|
||||
"prompt",
|
||||
default="",
|
||||
multiline=True,
|
||||
tooltip="Text prompt for GPT Image",
|
||||
),
|
||||
IO.DynamicCombo.Input(
|
||||
"model",
|
||||
options=[
|
||||
IO.DynamicCombo.Option(
|
||||
"gpt-image-2",
|
||||
[
|
||||
IO.Combo.Input(
|
||||
"size",
|
||||
default="auto",
|
||||
options=[
|
||||
"auto",
|
||||
"1024x1024",
|
||||
"1024x1536",
|
||||
"1536x1024",
|
||||
"2048x2048",
|
||||
"2048x1152",
|
||||
"1152x2048",
|
||||
"3840x2160",
|
||||
"2160x3840",
|
||||
"Custom",
|
||||
],
|
||||
tooltip="Image size. Select 'Custom' to use the custom width and height.",
|
||||
),
|
||||
IO.Int.Input(
|
||||
"custom_width",
|
||||
default=1024,
|
||||
min=1024,
|
||||
max=3840,
|
||||
step=16,
|
||||
tooltip="Used only when `size` is 'Custom'. Must be a multiple of 16.",
|
||||
),
|
||||
IO.Int.Input(
|
||||
"custom_height",
|
||||
default=1024,
|
||||
min=1024,
|
||||
max=3840,
|
||||
step=16,
|
||||
tooltip="Used only when `size` is 'Custom'. Must be a multiple of 16.",
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"background",
|
||||
default="auto",
|
||||
options=["auto", "opaque"],
|
||||
tooltip="Return image with or without background.",
|
||||
),
|
||||
*_gpt_image_shared_inputs(),
|
||||
],
|
||||
),
|
||||
IO.DynamicCombo.Option("gpt-image-1.5", _gpt_image_legacy_model_inputs()),
|
||||
IO.DynamicCombo.Option("gpt-image-1", _gpt_image_legacy_model_inputs()),
|
||||
],
|
||||
),
|
||||
IO.Int.Input(
|
||||
"n",
|
||||
default=1,
|
||||
min=1,
|
||||
max=8,
|
||||
step=1,
|
||||
tooltip="How many images to generate",
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=0,
|
||||
min=0,
|
||||
max=2147483647,
|
||||
step=1,
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
control_after_generate=True,
|
||||
tooltip="not implemented yet in backend",
|
||||
),
|
||||
],
|
||||
outputs=[IO.Image.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(
|
||||
depends_on=IO.PriceBadgeDepends(widgets=["model", "model.quality", "n"]),
|
||||
expr="""
|
||||
(
|
||||
$ranges := {
|
||||
"gpt-image-1": {
|
||||
"low": [0.011, 0.02],
|
||||
"medium": [0.042, 0.07],
|
||||
"high": [0.167, 0.25]
|
||||
},
|
||||
"gpt-image-1.5": {
|
||||
"low": [0.009, 0.02],
|
||||
"medium": [0.034, 0.062],
|
||||
"high": [0.133, 0.22]
|
||||
},
|
||||
"gpt-image-2": {
|
||||
"low": [0.0048, 0.019],
|
||||
"medium": [0.041, 0.168],
|
||||
"high": [0.165, 0.67]
|
||||
}
|
||||
};
|
||||
$range := $lookup($lookup($ranges, widgets.model), $lookup(widgets, "model.quality"));
|
||||
$nRaw := widgets.n;
|
||||
$n := ($nRaw != null and $nRaw != 0) ? $nRaw : 1;
|
||||
($n = 1)
|
||||
? {"type":"range_usd","min_usd": $range[0], "max_usd": $range[1], "format": {"approximate": true}}
|
||||
: {
|
||||
"type":"range_usd",
|
||||
"min_usd": $range[0] * $n,
|
||||
"max_usd": $range[1] * $n,
|
||||
"format": { "suffix": "/Run", "approximate": true }
|
||||
}
|
||||
)
|
||||
""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
prompt: str,
|
||||
model: dict,
|
||||
n: int,
|
||||
seed: int,
|
||||
) -> IO.NodeOutput:
|
||||
validate_string(prompt, strip_whitespace=False)
|
||||
|
||||
model_id = model["model"]
|
||||
size = model["size"]
|
||||
background = model["background"]
|
||||
quality = model["quality"]
|
||||
custom_width = model.get("custom_width", 1024)
|
||||
custom_height = model.get("custom_height", 1024)
|
||||
|
||||
images_dict = model.get("images") or {}
|
||||
image_tensors: list[Input.Image] = [t for t in images_dict.values() if t is not None]
|
||||
n_images = sum(get_number_of_images(t) for t in image_tensors)
|
||||
mask = model.get("mask")
|
||||
|
||||
if mask is not None and n_images == 0:
|
||||
raise ValueError("Cannot use a mask without an input image")
|
||||
|
||||
if size == "Custom":
|
||||
if custom_width % 16 != 0 or custom_height % 16 != 0:
|
||||
raise ValueError(
|
||||
f"Custom width and height must be multiples of 16, got {custom_width}x{custom_height}"
|
||||
)
|
||||
if max(custom_width, custom_height) > 3840:
|
||||
raise ValueError(
|
||||
f"Custom resolution max edge must be <= 3840, got {custom_width}x{custom_height}"
|
||||
)
|
||||
ratio = max(custom_width, custom_height) / min(custom_width, custom_height)
|
||||
if ratio > 3:
|
||||
raise ValueError(
|
||||
f"Custom resolution aspect ratio must not exceed 3:1, got {custom_width}x{custom_height}"
|
||||
)
|
||||
total_pixels = custom_width * custom_height
|
||||
if not 655_360 <= total_pixels <= 8_294_400:
|
||||
raise ValueError(
|
||||
f"Custom resolution total pixels must be between 655,360 and 8,294,400, got {total_pixels}"
|
||||
)
|
||||
size = f"{custom_width}x{custom_height}"
|
||||
|
||||
if model_id == "gpt-image-1":
|
||||
price_extractor = calculate_tokens_price_image_1
|
||||
elif model_id == "gpt-image-1.5":
|
||||
price_extractor = calculate_tokens_price_image_1_5
|
||||
elif model_id == "gpt-image-2":
|
||||
price_extractor = calculate_tokens_price_image_2_0
|
||||
else:
|
||||
raise ValueError(f"Unknown model: {model_id}")
|
||||
|
||||
if image_tensors:
|
||||
flat: list[torch.Tensor] = []
|
||||
for tensor in image_tensors:
|
||||
if len(tensor.shape) == 4:
|
||||
flat.extend(tensor[i : i + 1] for i in range(tensor.shape[0]))
|
||||
else:
|
||||
flat.append(tensor.unsqueeze(0))
|
||||
|
||||
files = []
|
||||
for i, single_image in enumerate(flat):
|
||||
scaled_image = downscale_image_tensor(single_image, total_pixels=2048 * 2048).squeeze()
|
||||
image_np = (scaled_image.numpy() * 255).astype(np.uint8)
|
||||
img = Image.fromarray(image_np)
|
||||
img_byte_arr = BytesIO()
|
||||
img.save(img_byte_arr, format="PNG")
|
||||
img_byte_arr.seek(0)
|
||||
|
||||
if len(flat) == 1:
|
||||
files.append(("image", (f"image_{i}.png", img_byte_arr, "image/png")))
|
||||
else:
|
||||
files.append(("image[]", (f"image_{i}.png", img_byte_arr, "image/png")))
|
||||
|
||||
if mask is not None:
|
||||
if len(flat) != 1:
|
||||
raise Exception("Cannot use a mask with multiple image")
|
||||
ref_image = flat[0]
|
||||
if mask.shape[1:] != ref_image.shape[1:-1]:
|
||||
raise Exception("Mask and Image must be the same size")
|
||||
_, height, width = mask.shape
|
||||
rgba_mask = torch.zeros(height, width, 4, device="cpu")
|
||||
rgba_mask[:, :, 3] = 1 - mask.squeeze().cpu()
|
||||
scaled_mask = downscale_image_tensor(
|
||||
rgba_mask.unsqueeze(0), total_pixels=2048 * 2048
|
||||
).squeeze()
|
||||
mask_np = (scaled_mask.numpy() * 255).astype(np.uint8)
|
||||
mask_img = Image.fromarray(mask_np)
|
||||
mask_img_byte_arr = BytesIO()
|
||||
mask_img.save(mask_img_byte_arr, format="PNG")
|
||||
mask_img_byte_arr.seek(0)
|
||||
files.append(("mask", ("mask.png", mask_img_byte_arr, "image/png")))
|
||||
|
||||
response = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(path="/proxy/openai/images/edits", method="POST"),
|
||||
response_model=OpenAIImageGenerationResponse,
|
||||
data=OpenAIImageEditRequest(
|
||||
model=model_id,
|
||||
prompt=prompt,
|
||||
quality=quality,
|
||||
background=background,
|
||||
n=n,
|
||||
size=size,
|
||||
moderation="low",
|
||||
),
|
||||
content_type="multipart/form-data",
|
||||
files=files,
|
||||
price_extractor=price_extractor,
|
||||
)
|
||||
else:
|
||||
response = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(path="/proxy/openai/images/generations", method="POST"),
|
||||
response_model=OpenAIImageGenerationResponse,
|
||||
data=OpenAIImageGenerationRequest(
|
||||
model=model_id,
|
||||
prompt=prompt,
|
||||
quality=quality,
|
||||
background=background,
|
||||
n=n,
|
||||
size=size,
|
||||
moderation="low",
|
||||
),
|
||||
price_extractor=price_extractor,
|
||||
)
|
||||
return IO.NodeOutput(await validate_and_cast_response(response))
|
||||
|
||||
|
||||
class OpenAIChatNode(IO.ComfyNode):
|
||||
"""
|
||||
Node to generate text responses from an OpenAI model.
|
||||
@ -999,6 +1311,7 @@ class OpenAIExtension(ComfyExtension):
|
||||
OpenAIDalle2,
|
||||
OpenAIDalle3,
|
||||
OpenAIGPTImage1,
|
||||
OpenAIGPTImageNodeV2,
|
||||
OpenAIChatNode,
|
||||
OpenAIInputFiles,
|
||||
OpenAIChatConfig,
|
||||
|
||||
@ -63,7 +63,7 @@ class MathExpressionNode(io.ComfyNode):
|
||||
@classmethod
|
||||
def define_schema(cls) -> io.Schema:
|
||||
autogrow = io.Autogrow.TemplateNames(
|
||||
input=io.MultiType.Input("value", [io.Float, io.Int]),
|
||||
input=io.MultiType.Input("value", [io.Float, io.Int, io.Boolean]),
|
||||
names=list(string.ascii_lowercase),
|
||||
min=1,
|
||||
)
|
||||
@ -82,6 +82,7 @@ class MathExpressionNode(io.ComfyNode):
|
||||
outputs=[
|
||||
io.Float.Output(display_name="FLOAT"),
|
||||
io.Int.Output(display_name="INT"),
|
||||
io.Boolean.Output(display_name="BOOL"),
|
||||
],
|
||||
)
|
||||
|
||||
@ -97,7 +98,7 @@ class MathExpressionNode(io.ComfyNode):
|
||||
|
||||
result = simple_eval(expression, names=context, functions=MATH_FUNCTIONS)
|
||||
# bool check must come first because bool is a subclass of int in Python
|
||||
if isinstance(result, bool) or not isinstance(result, (int, float)):
|
||||
if not isinstance(result, (int, float)):
|
||||
raise ValueError(
|
||||
f"Math Expression '{expression}' must evaluate to a numeric result, "
|
||||
f"got {type(result).__name__}: {result!r}"
|
||||
@ -106,7 +107,7 @@ class MathExpressionNode(io.ComfyNode):
|
||||
raise ValueError(
|
||||
f"Math Expression '{expression}' produced a non-finite result: {result}"
|
||||
)
|
||||
return io.NodeOutput(float(result), int(result))
|
||||
return io.NodeOutput(float(result), int(result), bool(result))
|
||||
|
||||
|
||||
class MathExtension(ComfyExtension):
|
||||
|
||||
@ -116,7 +116,7 @@ class EmptyQwenImageLayeredLatentImage(io.ComfyNode):
|
||||
inputs=[
|
||||
io.Int.Input("width", default=640, min=16, max=nodes.MAX_RESOLUTION, step=16),
|
||||
io.Int.Input("height", default=640, min=16, max=nodes.MAX_RESOLUTION, step=16),
|
||||
io.Int.Input("layers", default=3, min=0, max=nodes.MAX_RESOLUTION, step=1, advanced=True),
|
||||
io.Int.Input("layers", default=3, min=0, max=nodes.MAX_RESOLUTION, step=1),
|
||||
io.Int.Input("batch_size", default=1, min=1, max=4096),
|
||||
],
|
||||
outputs=[
|
||||
|
||||
@ -1,3 +1,3 @@
|
||||
# This file is automatically generated by the build process when version is
|
||||
# updated in pyproject.toml.
|
||||
__version__ = "0.20.1"
|
||||
__version__ = "0.21.0"
|
||||
|
||||
35
openapi.yaml
35
openapi.yaml
@ -2071,7 +2071,6 @@ paths:
|
||||
type: integer
|
||||
description: Number of assets marked as missing
|
||||
|
||||
|
||||
# ===========================================================================
|
||||
# Cloud-runtime FE-facing operations
|
||||
#
|
||||
@ -2122,7 +2121,11 @@ paths:
|
||||
operationId: getCloudJobStatus
|
||||
tags: [queue]
|
||||
summary: Get status of a cloud job
|
||||
description: "[cloud-only] Returns the current execution status of a cloud job."
|
||||
deprecated: true
|
||||
description: |
|
||||
**Deprecated.** This endpoint is superseded by `GET /api/jobs/{job_id}`.
|
||||
Clients should migrate; the endpoint is retained for backward
|
||||
compatibility but will be removed in a future release.
|
||||
x-runtime: [cloud]
|
||||
parameters:
|
||||
- name: job_id
|
||||
@ -2192,7 +2195,11 @@ paths:
|
||||
operationId: getHistoryV2
|
||||
tags: [history]
|
||||
summary: Get paginated execution history (v2)
|
||||
description: "[cloud-only] Returns a paginated list of execution history entries in the v2 format, with richer metadata than the legacy history endpoint."
|
||||
deprecated: true
|
||||
description: |
|
||||
**Deprecated.** This endpoint is superseded by `GET /api/jobs`.
|
||||
Clients should migrate; the endpoint is retained for backward
|
||||
compatibility but will be removed in a future release.
|
||||
x-runtime: [cloud]
|
||||
parameters:
|
||||
- name: limit
|
||||
@ -2231,7 +2238,11 @@ paths:
|
||||
operationId: getHistoryV2ByPromptId
|
||||
tags: [history]
|
||||
summary: Get v2 history for a specific prompt
|
||||
description: "[cloud-only] Returns the v2 history entry for a specific prompt execution."
|
||||
deprecated: true
|
||||
description: |
|
||||
**Deprecated.** This endpoint is superseded by `GET /api/jobs/{prompt_id}`.
|
||||
Clients should migrate; the endpoint is retained for backward
|
||||
compatibility but will be removed in a future release.
|
||||
x-runtime: [cloud]
|
||||
parameters:
|
||||
- name: prompt_id
|
||||
@ -2266,7 +2277,12 @@ paths:
|
||||
operationId: getCloudLogs
|
||||
tags: [system]
|
||||
summary: Get cloud execution logs
|
||||
description: "[cloud-only] Returns execution logs for the authenticated user's cloud jobs."
|
||||
deprecated: true
|
||||
description: |
|
||||
**Deprecated.** This endpoint returns a static placeholder response and
|
||||
provides no real log data. It is retained only to avoid breaking clients
|
||||
that still call it. Clients should remove their dependency; the endpoint
|
||||
will be removed in a future release.
|
||||
x-runtime: [cloud]
|
||||
parameters:
|
||||
- name: job_id
|
||||
@ -5370,7 +5386,12 @@ paths:
|
||||
operationId: viewVideo
|
||||
tags: [view]
|
||||
summary: View or download a video file
|
||||
description: "[cloud-only] Serves a video file from the output directory. Used by the frontend video player."
|
||||
deprecated: true
|
||||
description: |
|
||||
**Deprecated.** This endpoint is an alias of `GET /api/view` added for
|
||||
legacy history-queue video playback. Callers should use `/api/view`
|
||||
directly; the endpoint is retained for backward compatibility but will
|
||||
be removed in a future release.
|
||||
x-runtime: [cloud]
|
||||
parameters:
|
||||
- name: filename
|
||||
@ -5523,7 +5544,6 @@ paths:
|
||||
schema:
|
||||
$ref: "#/components/schemas/CloudError"
|
||||
|
||||
|
||||
components:
|
||||
parameters:
|
||||
ComfyUserHeader:
|
||||
@ -6875,7 +6895,6 @@ components:
|
||||
error:
|
||||
type: string
|
||||
|
||||
|
||||
# -------------------------------------------------------------------
|
||||
# Cloud-runtime schemas
|
||||
#
|
||||
|
||||
@ -1,6 +1,6 @@
|
||||
[project]
|
||||
name = "ComfyUI"
|
||||
version = "0.20.1"
|
||||
version = "0.21.0"
|
||||
readme = "README.md"
|
||||
license = { file = "LICENSE" }
|
||||
requires-python = ">=3.10"
|
||||
|
||||
@ -1,5 +1,5 @@
|
||||
comfyui-frontend-package==1.43.18
|
||||
comfyui-workflow-templates==0.9.72
|
||||
comfyui-workflow-templates==0.9.73
|
||||
comfyui-embedded-docs==0.4.4
|
||||
torch
|
||||
torchsde
|
||||
|
||||
@ -124,9 +124,11 @@ class TestMathExpressionExecute:
|
||||
with pytest.raises(Exception, match="not defined"):
|
||||
self._exec("str(a)", a=42)
|
||||
|
||||
def test_boolean_result_raises(self):
|
||||
with pytest.raises(ValueError, match="got bool"):
|
||||
self._exec("a > b", a=5, b=3)
|
||||
def test_boolean_result(self):
|
||||
result = self._exec("a > b", a=5, b=3)
|
||||
assert result[2] is True
|
||||
result = self._exec("a > b", a=3, b=5)
|
||||
assert result[2] is False
|
||||
|
||||
def test_empty_expression_raises(self):
|
||||
with pytest.raises(ValueError, match="Expression cannot be empty"):
|
||||
|
||||
Reference in New Issue
Block a user