Upload app (1).py

app (1).py

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+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()