lllyasviel / lllyasviel/ControlNet
Custom resolution dataset, ex 1024 x 768?
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Description
Is it possible to train with a custom resolution dataset, ex 1024 x 768?
I tried something like this, but didn't work:
accelerate launch train_controlnet.py
--pretrained_model_name_or_path=$MODEL_DIR
--output_dir=$OUTPUT_DIR
--dataset_name=fusing/fill50k
*--resolution=1024x768 *
--learning_rate=1e-5
--validation_image "./conditioning_image_1.png" "./conditioning_image_2.png"
--validation_prompt "red circle with blue background" "cyan circle with brown floral background"
--train_batch_size=4
thanks!
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Research direction
Start with train_controlnet.py and inspect how the --resolution argument is parsed and applied to the fusing/fill50k dataset and validation images. Determine whether non-square dimensions such as 1024x768 are supported throughout training, and consider the work complete when that command accepts the custom resolution and training proceeds successfully.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100