| import gradio as gr | |
| from transformers import pipeline | |
| # Load the model | |
| pipe = pipeline("image-classification", model="prithivMLmods/Gym-Workout-Classifier-SigLIP2") | |
| # Inference function | |
| def classify_image(image): | |
| return pipe(image) | |
| # Gradio UI | |
| demo = gr.Interface( | |
| fn=classify_image, | |
| inputs=gr.Image(type="pil"), | |
| outputs="label", | |
| title="Gym Workout Classifier" | |
| ) | |
| demo.launch() | |