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feat(plugin): add external image batch

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This commit is contained in:
bennykok 2024-04-24 21:48:42 +08:00
parent d00ca375a2
commit 797180b5c7
2 changed files with 124 additions and 30 deletions
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85
comfy-nodes/external_image_batch.py Normal file
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@ -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)"}

41
custom_routes.py
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@ -106,30 +106,26 @@ def apply_random_seed_to_workflow(workflow_api):
continue
workflow_api[key]['inputs']['seed'] = randomSeed();
def send_prompt(sid: str, inputs: StreamingPrompt):
# workflow_api = inputs.workflow_api
workflow_api = copy.deepcopy(inputs.workflow_api)
# Random seed
apply_random_seed_to_workflow(workflow_api)
print("getting inputs" , inputs.inputs)
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.inputs:
new_value = inputs.inputs[value['inputs']['input_id']]
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
@ -139,6 +135,19 @@ def send_prompt(sid: str, inputs: StreamingPrompt):
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
workflow_api = copy.deepcopy(inputs.workflow_api)
# Random seed
apply_random_seed_to_workflow(workflow_api)
print("getting inputs" , inputs.inputs)
apply_inputs_to_workflow(workflow_api, inputs.inputs, sid=sid)
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:
# if 'inputs' in workflow_api[key] and 'seed' in workflow_api[key]['inputs']:
# workflow_api[key]['inputs']['seed'] = randomSeed()
apply_inputs_to_workflow(workflow_api, inputs)
prompt = {
"prompt": workflow_api,