lllyasviel / lllyasviel/ControlNet

NameError: name 'apply_canny' is not defined

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Python
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Description

(control) F:\ControlNet-main>python F:\ControlNet-main\gradio_canny2image.py
logging improved.
Enabled sliced_attention.
logging improved.
Enabled clip hacks.
cuda
cuda
No module 'xformers'. Proceeding without it.
ControlLDM: Running in eps-prediction mode
DiffusionWrapper has 859.52 M params.
making attention of type 'vanilla' with 512 in_channels
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
making attention of type 'vanilla' with 512 in_channels
Loaded model config from [./models/cldm_v15.yaml]
Loaded state_dict from [./models/control_any3_openpose.pth]
Running on local URL: http://0.0.0.0:7861

To create a public link, set share=True in launch().
Traceback (most recent call last):
File "F:\1\envs\control\lib\site-packages\gradio\routes.py", line 337, in run_predict
output = await app.get_blocks().process_api(
File "F:\1\envs\control\lib\site-packages\gradio\blocks.py", line 1015, in process_api
result = await self.call_function(
File "F:\1\envs\control\lib\site-packages\gradio\blocks.py", line 833, in call_function
prediction = await anyio.to_thread.run_sync(
File "F:\1\envs\control\lib\site-packages\anyio\to_thread.py", line 31, in run_sync
return await get_asynclib().run_sync_in_worker_thread(
File "F:\1\envs\control\lib\site-packages\anyio_backends_asyncio.py", line 937, in run_sync_in_worker_thread
return await future
File "F:\1\envs\control\lib\site-packages\anyio_backends_asyncio.py", line 867, in run
result = context.run(func, *args)
File "F:\ControlNet-main\gradio_canny2image.py", line 33, in process
detected_map = apply_canny(img, low_threshold, high_threshold)
NameError: name 'apply_canny' is not defined

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with gradio_canny2image.py, especially process at line 33, and inspect the surrounding imports and related Canny-processing entry points. Reproduce the Gradio action that reaches process, then verify it completes without the reported NameError.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning
Issue type
Bug
Difficulty
2/5
Estimated time
1-3 hours
Activity status
Stale
Clarity
Clearly specified
Newbie friendliness
42/100

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