Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+from PIL import Image
+
+# Load image classifier (general-purpose)
+classifier = pipeline("image-classification", model="google/vit-base-patch16-224")
+
+# Define recyclable classes (based on common outputs of the model)
+RECYCLABLE_CLASSES = {
+    "plastic bottle", "water bottle", "can", "glass", "cup",
+    "paper", "newspaper", "cardboard", "box", "carton", "tin"
+}
+
+def classify_trash(image):
+    results = classifier(image)
+    top_label = results[0]['label'].lower()
+    confidence = results[0]['score']
+
+    is_recyclable = any(recycle_word in top_label for recycle_word in RECYCLABLE_CLASSES)
+
+    label = "♻️ Recyclable" if is_recyclable else "🗑️ Not Recyclable"
+    return f"{label}\nDetected: {top_label}\nConfidence: {confidence:.2%}"
+
+# Gradio interface
+demo = gr.Interface(
+    fn=classify_trash,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Textbox(label="Classification"),
+    title="♻️ Trash Classifier: Recyclable or Not?",
+    description="Upload an image of an object (like a bottle, banana peel, or can) and find out if it is recyclable.",
+)
+
+if __name__ == "__main__":
+    demo.launch()