Instructions to use MRiabov/WireSegHR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MRiabov/WireSegHR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="MRiabov/WireSegHR")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MRiabov/WireSegHR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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(debug) import yaml
Verified signatureb7ea8a4 -
Update model card
Verified signaturee3db6f5 -
Git lfs changed to accept png and jpg
4bdc4a4 -
(minor) push paper files for easier LLM usage
1a0b138 -
Add final pt to git
b4ec92c -
Safetensors model export
96ac66c -
Safetensors export and infer.
dae69c0 -
Add images to README
befda65 -
fix strip checkpoint saving
5571883 -
README and cleanup
e05cc17 -
Metrics computation in infer.py
d79c41b -
(minor util) strip checkpoint util
a0ad699 -
(minor refactor) os.path to pathlib and tdqm to infer.py
8223f36
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Attempting export to onnx and tensorRT
2991754 -
(test) test ResNet backbone
6e8ad0e -
Add export to onnx and tensorRT
c2fb738 -
Add benchmark to infer.py
8943a48 -
(debug) fix eval loop not selecting randomly
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Save test visuals during final eval
ba1bfde -
Add ResNet-50 as a backbone option
a2999cc -
(cleanup) removing timm from the codebase.
e3ab023 -
Merge branch 'main' of https://github.com/MRiabov/wire-seg-hr-impl
8cd5198 -
(debug) to torch operations in bfloat conversions.
854831b -
Add final checkpoint save and test set val
feec877 -
(untested test) fixing some test errors
ae754fb -
Eval to infer.py
500cad9 -
(optim) benchmark=True and higher eval batch size
d2db539 -
Speeding up eval by reducing iters
8b1ceda -
Added precision training option
8743e1d -
(optim) prefetch and speed up eval.
efdb6a6 -
(debug) 6 chan instead of 7. (warn: conflicting git changes)
a527623 -
to mit_b2 as per paper
d46d294
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(debug) eval fixes
e160020 -
(devops) automatic pull and preprocess of datasets
953508f -
(config) reducing training iters and eval, checkpoint intervals
e8ba7db -
(test) test dataset
1d66790 -
Pull ttpla script
f2f9fec -
Running training
61275b8 -
(format) format
6928e82 -
Training loop and around the codebase
8e73ec9 -
Dataset pull script
ebeb96c -
Project skeleton generated
8ea2eff -
Unpack `.tex` source.
5cab910
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Repo init (paper add)
b03a07c