Front-squat vs Back-squat classification web app.
See notebooks for model demo.
This Deeplearning application was trained on a small curated dataset of images crawled off of google using a pretrained Resnet34 as the base. Click here or here to see an example implementation of Resnet models.
See setup.md to get started!
To train models run the following:
python training/run_experiment.py --save '{"dataset": "FvbsDataset", "model": "CnnClassificationModel", "network": "resnet34"}'
or
python ./tasks/train_simple_cnn_classification_model_on_fvbs.sh
python ./tasks/train_world_class_cnn_classification_model_on_fvbs.sh
see setup.md
test/tests.py
👤 m0sys
- Github: @m0sys
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