Instructions to use siddhantuniyal/exercise-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use siddhantuniyal/exercise-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="siddhantuniyal/exercise-detection") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("siddhantuniyal/exercise-detection") model = AutoModelForImageClassification.from_pretrained("siddhantuniyal/exercise-detection") - Notebooks
- Google Colab
- Kaggle
exercise-detection
Autogenerated by HuggingPics🤗🖼️
Create your own image classifier for anything by running the demo on Google Colab.
Report any issues with the demo at the github repo.
Example Images
bicep curl exercise
push up exercise
shoulder press exercise
squat exercise
- Downloads last month
- 7
Evaluation results
- Accuracyself-reported0.662



