🚀 Added Gradio YOLOv8 app

app.py

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+
+import gradio as gr
+from ultralytics import YOLO
+from huggingface_hub import hf_hub_download
+import cv2, tempfile
+
+# Load YOLO model from HF Hub
+model_path = hf_hub_download(repo_id="utkarsh-23/yolov8m-garbage-pothole-detector", filename="best.pt")
+model = YOLO(model_path)
+
+# Image detection
+def detect_image(image):
+    results = model(image)
+    return results[0].plot()
+
+# Video detection
+def detect_video(video_path):
+    cap = cv2.VideoCapture(video_path)
+    fourcc = cv2.VideoWriter_fourcc(*"mp4v")
+    out_path = tempfile.mktemp(suffix=".mp4")
+    out = cv2.VideoWriter(
+        out_path, fourcc, cap.get(cv2.CAP_PROP_FPS),
+        (int(cap.get(3)), int(cap.get(4)))
+    )
+
+    while cap.isOpened():
+        ret, frame = cap.read()
+        if not ret:
+            break
+        results = model(frame)
+        annotated_frame = results[0].plot()
+        out.write(annotated_frame)
+
+    cap.release()
+    out.release()
+    return out_path
+
+# Interfaces
+image_interface = gr.Interface(
+    fn=detect_image,
+    inputs=gr.Image(type="numpy"),
+    outputs=gr.Image(type="numpy"),
+    title="Garbage & Pothole Detector (Image)"
+)
+
+video_interface = gr.Interface(
+    fn=detect_video,
+    inputs=gr.Video(),
+    outputs=gr.Video(),
+    title="Garbage & Pothole Detector (Video)"
+)
+
+demo = gr.TabbedInterface(
+    [image_interface, video_interface],
+    ["Image Detection", "Video Detection"]
+)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+ultralytics==8.3.202
+gradio==5.46.0
+huggingface_hub==0.35.0
+opencv-python==4.12.0.88

runtime.txt

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+python-3.10