| import gradio as gr | |
| from transformers import pipeline | |
| def image_classifier(image): | |
| pipe = pipeline("image-classification", "bhargob11/vit-base-patch16-224-in21k-finetuned-housplants") | |
| output = pipe(image) | |
| best_prediction = max(output, key=lambda x: x['score']) | |
| best_label = best_prediction['label'] | |
| return best_label | |
| gr.close_all() | |
| demo = gr.Interface(fn=image_classifier, | |
| inputs=[gr.Image(label="Upload image", type="pil")], | |
| outputs=[gr.Textbox(label="Category")], | |
| title="Image Classification with Fine-Tuned ViT Model", | |
| description="Classify any houseplant images", | |
| allow_flagging="never") | |
| # examples=["christmas_dog.jpeg", "bird_flight.jpeg", "cow.jpeg"]) | |
| demo.launch(share=True) # server_port=int(os.environ['PORT1']) | |