feat(plugin): add external image batch

comfy-nodes/external_image_batch.py

@@ -0,0 +1,85 @@
+import folder_paths
+from PIL import Image, ImageOps
+import numpy as np
+import torch
+import json
+import comfy
+
+class ComfyUIDeployExternalImageBatch:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "input_id": (
+                    "STRING",
+                    {"multiline": False, "default": "input_images"},
+                ),
+                "images": (
+                    "STRING",
+                    {"multiline": False, "default": "[]"},
+                ),
+            },
+            "optional": {
+                "default_value": ("IMAGE",),
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("image",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "image"
+    
+    def run(self, input_id, images=None, default_value=None):
+        processed_images = []
+        try:
+            images_list = json.loads(images)  # Assuming images is a JSON array string
+            print(images_list)
+            for img_input in images_list:
+                if img_input.startswith('http'):
+                    import requests
+                    from io import BytesIO
+                    print("Fetching image from url: ", img_input)
+                    response = requests.get(img_input)
+                    image = Image.open(BytesIO(response.content))
+                elif img_input.startswith('data:image/png;base64,') or img_input.startswith('data:image/jpeg;base64,') or img_input.startswith('data:image/jpg;base64,'):
+                    import base64
+                    from io import BytesIO
+                    print("Decoding base64 image")
+                    base64_image = img_input[img_input.find(",")+1:]
+                    decoded_image = base64.b64decode(base64_image)
+                    image = Image.open(BytesIO(decoded_image))
+                else:
+                    raise ValueError("Invalid image url or base64 data provided.")
+
+                image = ImageOps.exif_transpose(image)
+                image = image.convert("RGB")
+                image = np.array(image).astype(np.float32) / 255.0
+                image_tensor = torch.from_numpy(image)[None,]
+                processed_images.append(image_tensor)
+        except Exception as e:
+            print(f"Error processing images: {e}")
+            pass
+            
+        if default_value is not None and len(images_list) == 0:
+            processed_images.append(default_value)  # Assuming default_value is a pre-processed image tensor
+
+        # Resize images if necessary and concatenate from MakeImageBatch in ImpactPack
+        if processed_images:
+            base_shape = processed_images[0].shape[1:]  # Get the shape of the first image for comparison
+            batch_tensor = processed_images[0]
+            for i in range(1, len(processed_images)):
+                if processed_images[i].shape[1:] != base_shape:
+                    # Resize to match the first image's dimensions
+                    processed_images[i] = comfy.utils.common_upscale(processed_images[i].movedim(-1, 1), base_shape[1], base_shape[0], "lanczos", "center").movedim(1, -1)
+
+                batch_tensor = torch.cat((batch_tensor, processed_images[i]), dim=0)
+            # Concatenate using torch.cat
+        else:
+            batch_tensor = None  # or handle the empty case as needed
+        return (batch_tensor, )
+
+
+NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalImageBatch": ComfyUIDeployExternalImageBatch}
+NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalImageBatch": "External Image Batch (ComfyUI Deploy)"}

custom_routes.py

@@ -105,6 +105,38 @@ def apply_random_seed_to_workflow(workflow_api):
                 workflow_api[key]['inputs']['seed'] = randomSeed(8);
                 continue
             workflow_api[key]['inputs']['seed'] = randomSeed();
+            
+def apply_inputs_to_workflow(workflow_api: Any, inputs: Any, sid: str = None):
+    # Loop through each of the inputs and replace them
+    for key, value in workflow_api.items():
+        if 'inputs' in value:
+            
+            # Support websocket
+            if sid is not None:
+                if (value["class_type"] == "ComfyDeployWebscoketImageOutput"):
+                    value['inputs']["client_id"] = sid
+                if (value["class_type"] == "ComfyDeployWebscoketImageInput"):
+                    value['inputs']["client_id"] = sid
+                    
+            if "input_id" in value['inputs'] and value['inputs']['input_id'] in inputs:
+                new_value = inputs[value['inputs']['input_id']]
+                
+                # Lets skip it if its an image
+                if isinstance(new_value, Image.Image):
+                    continue
+                
+                # Backward compactibility
+                value['inputs']["input_id"] = new_value
+            
+                # Fix for external text default value
+                if (value["class_type"] == "ComfyUIDeployExternalText"):
+                    value['inputs']["default_value"] = new_value
+                    
+                if (value["class_type"] == "ComfyUIDeployExternalCheckpoint"):
+                    value['inputs']["default_value"] = new_value
+                    
+                if (value["class_type"] == "ComfyUIDeployExternalImageBatch"):
+                    value['inputs']["images"] = new_value
 
 def send_prompt(sid: str, inputs: StreamingPrompt):
     # workflow_api = inputs.workflow_api
@@ -114,31 +146,8 @@ def send_prompt(sid: str, inputs: StreamingPrompt):
     apply_random_seed_to_workflow(workflow_api)
             
     print("getting inputs" , inputs.inputs)
-            
+    
-    # Loop through each of the inputs and replace them
+    apply_inputs_to_workflow(workflow_api, inputs.inputs, sid=sid)
-    for key, value in workflow_api.items():
-        if 'inputs' in value:
-            if (value["class_type"] == "ComfyDeployWebscoketImageOutput"):
-                value['inputs']["client_id"] = sid
-            if (value["class_type"] == "ComfyDeployWebscoketImageInput"):
-                value['inputs']["client_id"] = sid
-                
-            if "input_id" in value['inputs'] and value['inputs']['input_id'] in inputs.inputs:
-                new_value = inputs.inputs[value['inputs']['input_id']]
-                
-                # Lets skip it if its an image
-                if isinstance(new_value, Image.Image):
-                    continue
-                
-                value['inputs']["input_id"] = new_value
-            
-                # Fix for external text default value
-                if (value["class_type"] == "ComfyUIDeployExternalText"):
-                    value['inputs']["default_value"] = new_value
-                    
-                if (value["class_type"] == "ComfyUIDeployExternalCheckpoint"):
-                    value['inputs']["default_value"] = new_value
-
                 
     print(workflow_api)
                 
@@ -171,15 +180,15 @@ async def comfy_deploy_run(request):
     prompt_server = server.PromptServer.instance
     data = await request.json()
 
-    workflow_api = data.get("workflow_api")
+    # In older version, we use workflow_api, but this has inputs already swapped in nextjs frontend, which is tricky
-
+    workflow_api = data.get("workflow_api_raw")
     # The prompt id generated from comfy deploy, can be None
     prompt_id = data.get("prompt_id")
+    inputs = data.get("inputs")
 
+    # Now it handles directly in here
     apply_random_seed_to_workflow(workflow_api)
-    # for key in workflow_api:
+    apply_inputs_to_workflow(workflow_api, inputs)
-    #     if 'inputs' in workflow_api[key] and 'seed' in workflow_api[key]['inputs']:
-    #         workflow_api[key]['inputs']['seed'] = randomSeed()
 
     prompt = {
         "prompt": workflow_api,