ComfyUI version 0.3.30

saves users having to explicitly discard the channel

comfy/clip_vision.py

@@ -18,6 +18,7 @@ class Output:
         setattr(self, key, item)
 
 def clip_preprocess(image, size=224, mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711], crop=True):
+    image = image[:, :, :, :3] if image.shape[3] > 3 else image
     mean = torch.tensor(mean, device=image.device, dtype=image.dtype)
     std = torch.tensor(std, device=image.device, dtype=image.dtype)
     image = image.movedim(-1, 1)

comfy_api_nodes/nodes_api.py

@@ -31,35 +31,43 @@ def downscale_input(image):
     s = s.movedim(1,-1)
     return s
 
-def validate_and_cast_response (response):
+def validate_and_cast_response(response):
     # validate raw JSON response
     data = response.data
     if not data or len(data) == 0:
         raise Exception("No images returned from API endpoint")
 
-    # Get base64 image data
-    image_url = data[0].url
-    b64_data = data[0].b64_json
-    if not image_url and not b64_data:
-        raise Exception("No image was generated in the response")
+    # Initialize list to store image tensors
+    image_tensors = []
 
-    if b64_data:
-        img_data = base64.b64decode(b64_data)
-        img = Image.open(io.BytesIO(img_data))
+    # Process each image in the data array
+    for image_data in data:
+        image_url = image_data.url
+        b64_data = image_data.b64_json
 
-    elif image_url:
-        img_response = requests.get(image_url)
-        if img_response.status_code != 200:
-            raise Exception("Failed to download the image")
-        img = Image.open(io.BytesIO(img_response.content))
+        if not image_url and not b64_data:
+            raise Exception("No image was generated in the response")
 
-    img = img.convert("RGBA")
+        if b64_data:
+            img_data = base64.b64decode(b64_data)
+            img = Image.open(io.BytesIO(img_data))
 
-    # Convert to numpy array, normalize to float32 between 0 and 1
-    img_array = np.array(img).astype(np.float32) / 255.0
+        elif image_url:
+            img_response = requests.get(image_url)
+            if img_response.status_code != 200:
+                raise Exception("Failed to download the image")
+            img = Image.open(io.BytesIO(img_response.content))
 
-    # Convert to torch tensor and add batch dimension
-    return torch.from_numpy(img_array)[None,]
+        img = img.convert("RGBA")
+
+        # Convert to numpy array, normalize to float32 between 0 and 1
+        img_array = np.array(img).astype(np.float32) / 255.0
+        img_tensor = torch.from_numpy(img_array)
+
+        # Add to list of tensors
+        image_tensors.append(img_tensor)
+
+    return torch.stack(image_tensors, dim=0)
 
 class OpenAIDalle2(ComfyNodeABC):
     """

comfy_extras/nodes_lt.py

@@ -385,7 +385,7 @@ def encode_single_frame(output_file, image_array: np.ndarray, crf):
     container = av.open(output_file, "w", format="mp4")
     try:
         stream = container.add_stream(
-            "h264", rate=1, options={"crf": str(crf), "preset": "veryfast"}
+            "libx264", rate=1, options={"crf": str(crf), "preset": "veryfast"}
         )
         stream.height = image_array.shape[0]
         stream.width = image_array.shape[1]

comfyui_version.py

@@ -1,3 +1,3 @@
 # This file is automatically generated by the build process when version is
 # updated in pyproject.toml.
-__version__ = "0.3.29"
+__version__ = "0.3.30"

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "ComfyUI"
-version = "0.3.29"
+version = "0.3.30"
 readme = "README.md"
 license = { file = "LICENSE" }
 requires-python = ">=3.9"

requirements.txt

@@ -1,4 +1,4 @@
-comfyui-frontend-package==1.17.10
+comfyui-frontend-package==1.17.11
 comfyui-workflow-templates==0.1.3
 torch
 torchsde