lllyasviel / lllyasviel/ControlNet
Details of the random transforms for creating user sketch data
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Description
Hi, really interesting work. I was trying to train the model on a custom dataset, by generating user sketches using the method you mentioned. I couldn't find the implementation details for the `set of strong data augmentations (random thresholds, randomly masking out a random percentage of scribbles, random morphological transformations, and random non-maximum suppression)` you mentioned in the paper. It would be of great help if you could point me toward that code. Thanks.
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Research direction
Start by locating the implementation of the sketch-data augmentations described in the issue and compare it with the paper's list: random thresholds, scribble masking, morphological transformations, and non-maximum suppression. No file, test, or entry point is named, so completion would require identifying the relevant code and documenting or linking the implementation details clearly.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100