Create app.py

app.py

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+import gradio as gr
+import cv2
+import tempfile
+import os
+from ultralytics import YOLO
+
+model = YOLO("yolov8x.pt")
+
+vehicle_classes = {
+    "bicycle": 1,
+    "car": 2,
+    "motorcycle": 3,
+    "bus": 5,
+    "truck": 7
+}
+
+def detect_vehicles_with_logs(video_input):
+    cap = cv2.VideoCapture(video_input)
+    if not cap.isOpened():
+        return None, "", "❌ Error: Could not open video."
+
+    width  = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+    height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+    fps    = cap.get(cv2.CAP_PROP_FPS)
+
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".mp4") as tmpfile:
+        out_path = tmpfile.name
+
+    fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+    out_vid = cv2.VideoWriter(out_path, fourcc, fps, (width, height))
+
+    logs = ""
+    frame_index = 0
+
+    while True:
+        ret, frame = cap.read()
+        if not ret:
+            break
+        frame_index += 1
+
+        results = model(frame, verbose=False)[0]
+        detected = []
+
+        for box in results.boxes:
+            cls_id = int(box.cls.item())
+            if cls_id in vehicle_classes.values():
+                xyxy = box.xyxy[0].cpu().numpy().astype(int)
+                conf = box.conf.item()
+                label = model.names[cls_id]
+                detected.append(f"{label} ({conf:.2f})")
+
+                cv2.rectangle(frame, tuple(xyxy[:2]), tuple(xyxy[2:]), (0, 255, 0), 2)
+                cv2.putText(frame, f"{label} {conf:.2f}", (xyxy[0], xyxy[1] - 5),
+                            cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 1)
+
+        out_vid.write(frame)
+        logs += f"Frame {frame_index}: {', '.join(detected) if detected else 'No vehicles detected'}\n"
+
+    cap.release()
+    out_vid.release()
+
+    if not os.path.exists(out_path):
+        return None, "", "❌ Error: Processed video not found."
+
+    # Return three outputs:
+    # 1) path for video player to display (as video file)
+    # 2) path for download button (same video file)
+    # 3) logs text
+    return out_path, out_path, logs
+
+
+demo = gr.Interface(
+    fn=detect_vehicles_with_logs,
+    inputs=gr.Video(label="Upload a video"),
+    outputs=[
+        gr.Video(label="Processed Video"),  # show inline video
+        gr.File(label="Download Processed Video"),  # download button
+        gr.Textbox(label="Detection Logs", lines=20, interactive=False)
+    ],
+    title="YOLOv8x Vehicle Detection with Inline Video and Download",
+    description="Upload a video, detect vehicles, see the processed video inline, download it, and view logs."
+)
+
+if __name__ == "__main__":
+    demo.launch(share=True)