Create app.py

app.py

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+import gradio as gr
+from ultralytics import YOLO
+import cv2
+
+# Load model
+model = YOLO("best.pt")  # Ganti dengan path model kamu
+
+def predict_image(img):
+    results = model(img)
+    annotated_frame = results[0].plot()
+    return annotated_frame
+
+def predict_video(video):
+    cap = cv2.VideoCapture(video)
+    frames = []
+    while cap.isOpened():
+        ret, frame = cap.read()
+        if not ret:
+            break
+        results = model(frame)
+        annotated = results[0].plot()
+        frames.append(annotated)
+    cap.release()
+
+    # Simpan video baru
+    out_path = "output.mp4"
+    height, width, _ = frames[0].shape
+    out = cv2.VideoWriter(out_path, cv2.VideoWriter_fourcc(*'mp4v'), 15, (width, height))
+    for f in frames:
+        out.write(f)
+    out.release()
+    return out_path
+
+demo = gr.Interface(
+    fn=predict_image,
+    inputs=gr.Image(type="numpy"),
+    outputs="image",
+    title="YOLOv8 Image Detection",
+    description="Upload an image for detection"
+)
+
+video_demo = gr.Interface(
+    fn=predict_video,
+    inputs=gr.Video(),
+    outputs=gr.Video(),
+    title="YOLOv8 Video Detection",
+    description="Upload a video for detection"
+)
+
+app = gr.TabbedInterface([demo, video_demo], ["Image Detection", "Video Detection"])
+
+app.launch()