| import gradio as gr | |
| import os | |
| from transformers import pipeline | |
| image_classifier = pipeline(task="zero-shot-image-classification", model="google/siglip-so400m-patch14-384") | |
| labels = ['street sweeping', 'litter pickup', 'pothole repair', 'parking enforcement'] | |
| def image_mod(image): | |
| outputs = image_classifier(image, candidate_labels=labels) | |
| result = {dic["label"]: dic["score"] for dic in outputs} | |
| return result | |
| app = gr.Interface( | |
| image_mod, | |
| gr.Image(type="pil"), | |
| gr.Label(), | |
| examples=[ | |
| os.path.join(os.path.dirname(__file__), "images/garbage-pickup.jpg"), | |
| os.path.join(os.path.dirname(__file__), "images/litter.jpg"), | |
| os.path.join(os.path.dirname(__file__), "images/wrong-park.jpg"), | |
| os.path.join(os.path.dirname(__file__), "images/pothole.jpg"), | |
| ], | |
| ) | |
| if __name__ == "__main__": | |
| app.launch() | |