Merge branch 'master' into feat/load3d-camera-info

Signed-off-by: bigcat88 <bigcat88@icloud.com>

.github/workflows/detect-unreviewed-merge.yml

@@ -0,0 +1,24 @@
+name: Detect Unreviewed Merge
+
+# SOC 2 compliance — reusable workflow lives in Comfy-Org/github-workflows,
+# tracking issues are filed in Comfy-Org/unreviewed-merges.
+
+on:
+  push:
+    branches: [master]
+
+concurrency:
+  group: detect-unreviewed-merge-${{ github.sha }}
+  cancel-in-progress: false
+
+permissions:
+  contents: read
+  pull-requests: read
+
+jobs:
+  detect:
+    uses: Comfy-Org/github-workflows/.github/workflows/detect-unreviewed-merge.yml@4d9cb6b87f953bb7cd69954280e1465fb9bd2040 # v1
+    with:
+      approval-mode: latest-per-reviewer
+    secrets:
+      UNREVIEWED_MERGES_TOKEN: ${{ secrets.UNREVIEWED_MERGES_TOKEN }}

comfy_api/latest/_io.py

@@ -762,17 +762,17 @@ class Accumulation(ComfyTypeIO):
 @comfytype(io_type="LOAD3D_CAMERA")
 class Load3DCamera(ComfyTypeIO):
     class CameraInfo(TypedDict):
-        position: dict[str, float | int]
-        target: dict[str, float | int]
-        zoom: int
-        cameraType: str
-        quaternion: NotRequired[dict[str, float | int]]
-        rotation: NotRequired[dict[str, float | int | str]]
-        fov: NotRequired[float | int]
-        aspect: NotRequired[float | int]
-        near: NotRequired[float | int]
-        far: NotRequired[float | int]
-        frustum: NotRequired[dict[str, float | int]]
+        # Coordinate system: right-handed, Y-up, camera looks down -Z
+        position: dict[str, float | int]  # scene units
+        target: dict[str, float | int]  # scene units; OrbitControls focus point
+        zoom: float | int  # dimensionless, 1 = 100%
+        cameraType: str  # 'perspective' | 'orthographic'
+        quaternion: NotRequired[dict[str, float | int]]  # normalized, dimensionless; camera world rotation
+        fov: NotRequired[float | int]  # degrees, vertical FOV (perspective only)
+        aspect: NotRequired[float | int]  # width / height (perspective only)
+        near: NotRequired[float | int]  # scene units
+        far: NotRequired[float | int]  # scene units
+        frustum: NotRequired[dict[str, float | int]]  # orthographic only: {left, right, top, bottom} in scene units
 
     Type = CameraInfo
 

comfy_api_nodes/nodes_beeble.py

@@ -206,7 +206,7 @@ class BeebleSwitchXVideoEdit(IO.ComfyNode):
         return IO.Schema(
             node_id="BeebleSwitchXVideoEdit",
             display_name="Beeble SwitchX Video Edit",
-            category="api node/video/Beeble",
+            category="video/partner/Beeble",
             description=(
                 "Edit a video with Beeble SwitchX. Switches anything in the scene (background, "
                 "lighting, costume) while preserving the original subject's pixels and motion. "
@@ -302,7 +302,7 @@ class BeebleSwitchXImageEdit(IO.ComfyNode):
         return IO.Schema(
             node_id="BeebleSwitchXImageEdit",
             display_name="Beeble SwitchX Image Edit",
-            category="api node/image/Beeble",
+            category="image/partner/Beeble",
             description=(
                 "Edit a single image with Beeble SwitchX. Switches anything in the scene "
                 "(background, lighting, costume) while preserving the original subject's pixels. "

comfy_api_nodes/nodes_bytedance.py

@@ -44,6 +44,7 @@ from comfy_api_nodes.util import (
     ApiEndpoint,
     download_url_to_image_tensor,
     download_url_to_video_output,
+    downscale_image_tensor_by_max_side,
     downscale_video_to_max_pixels,
     get_number_of_images,
     image_tensor_pair_to_batch,
@@ -122,6 +123,14 @@ def _validate_ref_video_pixels(video: Input.Video, model_id: str, resolution: st
         )
 
 
+def _prepare_seedance_image(image: Input.Image) -> Input.Image:
+    """Auto-downscale a Seedance image input to the per-side limits, then validate it."""
+    validate_image_aspect_ratio(image, (2, 5), (5, 2), strict=False)  # 0.4 to 2.5
+    image = downscale_image_tensor_by_max_side(image, max_side=6000)
+    validate_image_dimensions(image, min_width=300, min_height=300, max_width=6000, max_height=6000)
+    return image
+
+
 async def _resolve_reference_assets(
     cls: type[IO.ComfyNode],
     asset_ids: list[str],
@@ -1781,6 +1790,11 @@ class ByteDance2FirstLastFrameNode(IO.ComfyNode):
         if last_frame is not None and last_frame_asset_id:
             raise ValueError("Provide only one of last_frame or last_frame_asset_id, not both.")
 
+        if first_frame is not None:
+            first_frame = _prepare_seedance_image(first_frame)
+        if last_frame is not None:
+            last_frame = _prepare_seedance_image(last_frame)
+
         asset_ids_to_resolve = [a for a in (first_frame_asset_id, last_frame_asset_id) if a]
         image_assets: dict[str, str] = {}
         if asset_ids_to_resolve:
@@ -1887,7 +1901,7 @@ def _seedance2_reference_inputs(resolutions: list[str], default_ratio: str = "16
         ),
         IO.Boolean.Input(
             "auto_downscale",
-            default=False,
+            default=True,
             optional=True,
             tooltip="Automatically downscale reference videos that exceed the model's pixel budget "
             "for the selected resolution. Aspect ratio is preserved; videos already within limits are untouched.",
@@ -2055,6 +2069,9 @@ class ByteDance2ReferenceNode(IO.ComfyNode):
                 f"(audios={len(reference_audios)}, audio assets={len(reference_audio_assets)}). Maximum is 3."
             )
 
+        for key in reference_images:
+            reference_images[key] = _prepare_seedance_image(reference_images[key])
+
         model_id = SEEDANCE_MODELS[model["model"]]
         has_video_input = total_videos > 0
 

comfy_extras/nodes_dataset.py

@@ -157,7 +157,7 @@ class LoadImageTextDataSetFromFolderNode(io.ComfyNode):
         return io.NodeOutput(output_tensor, captions)
 
 
-def save_images_to_folder(image_list, output_dir, prefix="image"):
+def save_images_to_folder(image_list, output_dir, prefix="image", overwrite=True):
     """Utility function to save a list of image tensors to disk.
 
     Args:
@@ -197,7 +197,11 @@ def save_images_to_folder(image_list, output_dir, prefix="image"):
             raise ValueError(f"Expected torch.Tensor, got {type(img_tensor)}")
 
         # Save image
-        filename = f"{prefix}_{idx:05d}.png"
+        if overwrite:
+            filename = f"{prefix}_{idx:05d}.png"
+        else:
+            _, _, counter, _, resolved_prefix = folder_paths.get_save_image_path(prefix, output_dir)
+            filename = f"{resolved_prefix}_{counter:05}_{idx:05d}.png"
         filepath = os.path.join(output_dir, filename)
         img.save(filepath)
         saved_files.append(filename)
@@ -230,19 +234,26 @@ class SaveImageDataSetToFolderNode(io.ComfyNode):
                     tooltip="Prefix for saved image filenames.",
                     advanced=True,
                 ),
+                io.Combo.Input(
+                    "mode",
+                    default="overwrite",
+                    options=["overwrite", "increment"],
+                    tooltip="Whether to overwrite existing files or increment filenames to avoid overwriting."
+                ),
             ],
             outputs=[],
             is_deprecated=True,  # This node is redundant and superseded by existing Save Image nodes where the target folder can be specified in the filename_prefix
         )
 
     @classmethod
-    def execute(cls, images, folder_name, filename_prefix):
+    def execute(cls, images, folder_name, filename_prefix, mode):
         # Extract scalar values
         folder_name = folder_name[0]
         filename_prefix = filename_prefix[0]
+        mode = mode[0]
 
         output_dir = os.path.join(folder_paths.get_output_directory(), folder_name)
-        saved_files = save_images_to_folder(images, output_dir, filename_prefix)
+        saved_files = save_images_to_folder(images, output_dir, filename_prefix, mode=='overwrite')
 
         logging.info(f"Saved {len(saved_files)} images to {output_dir}.")
         return io.NodeOutput()
@@ -278,18 +289,25 @@ class SaveImageTextDataSetToFolderNode(io.ComfyNode):
                     tooltip="Prefix for saved image filenames.",
                     advanced=True,
                 ),
+                io.Combo.Input(
+                    "mode",
+                    default="overwrite",
+                    options=["overwrite", "increment"],
+                    tooltip="Whether to overwrite existing files or increment filenames to avoid overwriting."
+                ),
             ],
             outputs=[],
         )
 
     @classmethod
-    def execute(cls, images, folder_name, filename_prefix, texts=None):
+    def execute(cls, images, folder_name, filename_prefix, mode, texts=None):
         # Extract scalar values
         folder_name = folder_name[0]
         filename_prefix = filename_prefix[0]
+        mode = mode[0]
 
         output_dir = os.path.join(folder_paths.get_output_directory(), folder_name)
-        saved_files = save_images_to_folder(images, output_dir, filename_prefix)
+        saved_files = save_images_to_folder(images, output_dir, filename_prefix, mode=='overwrite')
 
         # Save captions
         if texts:

comfy_extras/nodes_load_3d.py

@@ -34,7 +34,7 @@ class Load3D(IO.ComfyNode):
             essentials_category="Basics",
             is_experimental=True,
             inputs=[
-                IO.Combo.Input("model_file", options=sorted(files), upload=IO.UploadType.model),
+                IO.Combo.Input("model_file", options=["none"] + sorted(files), upload=IO.UploadType.model),
                 IO.Load3D.Input("image"),
                 IO.Int.Input("width", default=1024, min=1, max=4096, step=1),
                 IO.Int.Input("height", default=1024, min=1, max=4096, step=1),
@@ -68,8 +68,12 @@ class Load3D(IO.ComfyNode):
 
             video = InputImpl.VideoFromFile(recording_video_path)
 
-        file_3d = Types.File3D(folder_paths.get_annotated_filepath(model_file))
-        return IO.NodeOutput(output_image, output_mask, model_file, normal_image, image['camera_info'], video, file_3d)
+        file_3d = None
+        mesh_path = ""
+        if model_file and model_file != "none":
+            file_3d = Types.File3D(folder_paths.get_annotated_filepath(model_file))
+            mesh_path = model_file
+        return IO.NodeOutput(output_image, output_mask, mesh_path, normal_image, image['camera_info'], video, file_3d)
 
     process = execute  # TODO: remove
 

requirements.txt

@@ -21,7 +21,7 @@ psutil
 alembic
 SQLAlchemy>=2.0.0
 filelock
-av>=14.2.0
+av>=16.0.0
 comfy-kitchen>=0.2.8
 comfy-aimdo==0.4.5
 requests