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| import gradio as gr | |
| from transformers import pipeline | |
| pipeline =pipeline("image-classification",model="p1atdev/siglip-tagger-test-3",trust_remote_code=True) | |
| def predict(input_img): | |
| predictions = pipeline(input_img , threshold=0.5, #optional parameter defaults to 0 | |
| return_scores = False #optional parameter defaults to False | |
| ) | |
| return predictions | |
| gradio_app = gr.Interface( | |
| predict, | |
| inputs=gr.Image(label="add your image here", sources=['upload', 'webcam'], type="pil"), | |
| outputs=gr.Text(), | |
| title="Image Annotator", | |
| ) | |
| if __name__ == "__main__": | |
| gradio_app.launch() |