| import gradio as gr | |
| from transformers import pipeline | |
| def predict(image): | |
| model_id = "google/vit-base-patch16-224" | |
| classifier = pipeline("image-classification", model=model_id) | |
| predictions = classifier(image) | |
| return {prediction['label']: prediction['score'] for prediction in predictions} | |
| title = "Image Classifier" | |
| description = "A demo that recognizes and classifies images using the model from Hugging Face's 'google/vit-base-patch16-224'." | |
| input_component = gr.Image(type="pil", label="Upload an image here") | |
| output_component = gr.Label(num_top_classes=3) | |
| gr.Interface(fn=predict, inputs=input_component, outputs=output_component, title=title, description=description).launch() | |