fofr / cog-become-image Goto Github PK
View Code? Open in Web Editor NEWTurn anyone into another image
Home Page: https://replicate.com/fofr/become-image
License: Other
Turn anyone into another image
Home Page: https://replicate.com/fofr/become-image
License: Other
How to fix this error?
'SDXLClipModel' object has no attribute 'set_clip_options'
File "/home/ComfyUI/execution.py", line 152, in recursive_execute
output_data, output_ui = get_output_data(obj, input_data_all)
File "/home/ComfyUI/execution.py", line 82, in get_output_data
return_values = map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True)
File "/home/ComfyUI/execution.py", line 75, in map_node_over_list
results.append(getattr(obj, func)(**slice_dict(input_data_all, i)))
File "/home/ComfyUI/custom_nodes/efficiency-nodes-comfyui/efficiency_nodes.py", line 172, in efficientloader
encode_prompts(positive, negative, token_normalization, weight_interpretation, clip, clip_skip,
File "/home/ComfyUI/custom_nodes/efficiency-nodes-comfyui/efficiency_nodes.py", line 73, in encode_prompts
positive_encoded = bnk_adv_encode.AdvancedCLIPTextEncode().encode(clip, positive_prompt, token_normalization, weight_interpretation)[0]
File "/home/ComfyUI/custom_nodes/efficiency-nodes-comfyui/py/bnk_adv_encode.py", line 312, in encode
embeddings_final, pooled = advanced_encode(clip, text, token_normalization, weight_interpretation, w_max=1.0,
File "/home/ComfyUI/custom_nodes/efficiency-nodes-comfyui/py/bnk_adv_encode.py", line 246, in advanced_encode
embs_l, _ = advanced_encode_from_tokens(tokenized['l'],
File "/home/ComfyUI/custom_nodes/efficiency-nodes-comfyui/py/bnk_adv_encode.py", line 183, in advanced_encode_from_tokens
weighted_emb, pooled_base = encode_func(weighted_tokens)
File "/home/ComfyUI/custom_nodes/efficiency-nodes-comfyui/py/bnk_adv_encode.py", line 249, in
lambda x: encode_token_weights(clip, x, encode_token_weights_l),
File "/home/ComfyUI/custom_nodes/efficiency-nodes-comfyui/py/bnk_adv_encode.py", line 226, in encode_token_weights
model.cond_stage_model.set_clip_options({"layer": model.layer_idx})
File "/home/miniconda3/envs/comfy/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1688, in __getattr__
raise AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'")
In the ComfyUI workflow, I keep getting this error and cannot run this workflow completely: AttributeError: 'SDXLClipModel' object has no attribute 'clip_layer'
model_path is /home/xxx/code/github.com/comfyanonymous/ComfyUI/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators/ZoeD_M12_N.pt
!!! Exception during processing !!!
Traceback (most recent call last):
File "/home/xxx/code/github.com/comfyanonymous/ComfyUI/execution.py", line 151, in recursive_execute
output_data, output_ui = get_output_data(obj, input_data_all)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/xxx/code/github.com/comfyanonymous/ComfyUI/execution.py", line 81, in get_output_data
return_values = map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/xxx/code/github.com/comfyanonymous/ComfyUI/execution.py", line 74, in map_node_over_list
results.append(getattr(obj, func)(**slice_dict(input_data_all, i)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/xxx/code/github.com/comfyanonymous/ComfyUI/custom_nodes/efficiency-nodes-comfyui/efficiency_nodes.py", line 172, in efficientloader
encode_prompts(positive, negative, token_normalization, weight_interpretation, clip, clip_skip,
File "/home/xxx/code/github.com/comfyanonymous/ComfyUI/custom_nodes/efficiency-nodes-comfyui/efficiency_nodes.py", line 73, in encode_prompts
positive_encoded = bnk_adv_encode.AdvancedCLIPTextEncode().encode(clip, positive_prompt, token_normalization, weight_interpretation)[0]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/xxx/code/github.com/comfyanonymous/ComfyUI/custom_nodes/efficiency-nodes-comfyui/py/bnk_adv_encode.py", line 288, in encode
embeddings_final, pooled = advanced_encode(clip, text, token_normalization, weight_interpretation, w_max=1.0,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/xxx/code/github.com/comfyanonymous/ComfyUI/custom_nodes/efficiency-nodes-comfyui/py/bnk_adv_encode.py", line 246, in advanced_encode
embs_l, _ = advanced_encode_from_tokens(tokenized['l'],
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/xxx/code/github.com/comfyanonymous/ComfyUI/custom_nodes/efficiency-nodes-comfyui/py/bnk_adv_encode.py", line 183, in advanced_encode_from_tokens
weighted_emb, pooled_base = encode_func(weighted_tokens)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/xxx/code/github.com/comfyanonymous/ComfyUI/custom_nodes/efficiency-nodes-comfyui/py/bnk_adv_encode.py", line 249, in <lambda>
lambda x: encode_token_weights(clip, x, encode_token_weights_l),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/xxx/code/github.com/comfyanonymous/ComfyUI/custom_nodes/efficiency-nodes-comfyui/py/bnk_adv_encode.py", line 226, in encode_token_weights
model.cond_stage_model.clip_layer(model.layer_idx)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/comfyui/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1688, in __getattr__
raise AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'")
AttributeError: 'SDXLClipModel' object has no attribute 'clip_layer'
⏳ Downloading antelopev2 to ComfyUI/models/insightface
⌛️ Completed in 9.45s but file not found.
Great workflow
I has a question about the comfyui workflow. When I run the workflow that you provide, I found the depth-controlnet seems not control the body of person, while replicate can control. I want to know how should I do?
This is my result of comyfui workflow(All params with default settings):
Dear developer,
How to debug this project?
I can't find the forward function. I want to know how the model performs cross-attention in UNet.
Best wishes.
I've developed a Cloudflare function that uploads an image and then runs your machine learning throught replicate. I've created a route to fetch the uploaded image. However, this route is not available in the development environment, so instead of a public image URL, I'll be sending a buffer of the image content.
When we set a blob/buffer/file in replicate, the input is transformed into base64 here:
totalBytes += buffer.byteLength;
if (totalBytes > MAX_DATA_URI_SIZE) {
throw new Error(
`Combined filesize of prediction ${totalBytes} bytes exceeds the 10MB limit for inline encoding. Please provide URLs instead.`
);
}
const data = bytesToBase64(buffer);
mime = mime ?? "application/octet-stream";
return `data:${mime};base64,${data}`;
However, when a base64 image is sent, I encounter the following error in the replicate logs:
Traceback (most recent call last):
File "/root/.pyenv/versions/3.10.6/lib/python3.10/site-packages/cog/server/worker.py", line 217, in _predict
result = predict(**payload)
File "/src/predict.py", line 186, in predict
filename = self.handle_input_file(image, "image_of_face")
File "/src/predict.py", line 61, in handle_input_file
raise ValueError(f"Unsupported file type: {file_extension}")
ValueError: Unsupported file type: .bin
Upon inspecting your repository, it appears that the file extension is being determined based on the file content here:
file_extension = os.path.splitext(input_file)[1].lower()
if file_extension in [".jpg", ".jpeg"]:
final_filename = f"{filename}.png"
image = Image.open(input_file)
try:
for orientation in ExifTags.TAGS.keys():
if ExifTags.TAGS[orientation] == "Orientation":
break
exif = dict(image._getexif().items())
if exif[orientation] == 3:
image = image.rotate(180, expand=True)
elif exif[orientation] == 6:
image = image.rotate(270, expand=True)
elif exif[orientation] == 8:
image = image.rotate(90, expand=True)
except (KeyError, AttributeError):
# EXIF data does not have orientation
# Do not rotate
pass
image.save(os.path.join(INPUT_DIR, final_filename))
elif file_extension in [".png", ".webp"]:
final_filename = filename + file_extension
shutil.copy(input_file, os.path.join(INPUT_DIR, final_filename))
else:
raise ValueError(f"Unsupported file type: {file_extension}")
return final_filename
.bin
when processing base64 images.handle_input_file
function in predict.py
to handle base64 images (or .bin
files) appropriately.I've only tested this with webp images (the base64 URL can be opened in my browser). I haven't managed to try base64 with jpeg and png images yet.
Adds more controlnet options
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