Update app.py

app.py

@@ -22,6 +22,27 @@ model.overrides['agnostic_nms'] = False  # NMS class-agnostic
 model.overrides['max_det'] = 1000  # Maksimum deteksi per frame
 logger.info("Model berhasil dimuat")
 
+def convert_video_to_mp4(input_path):
+    """Konversi video input ke MP4 jika format tidak didukung."""
+    temp_mp4_path = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False).name
+    ffmpeg_command = [
+        "ffmpeg",
+        "-y",  # Overwrite jika ada
+        "-i", input_path,
+        "-c:v", "libx264",
+        "-preset", "veryfast",
+        "-pix_fmt", "yuv420p",
+        temp_mp4_path
+    ]
+    result = subprocess.run(ffmpeg_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
+    if result.returncode == 0 and os.path.exists(temp_mp4_path) and os.path.getsize(temp_mp4_path) > 0:
+        logger.info("Video dikonversi ke MP4: %s", temp_mp4_path)
+        os.remove(input_path)  # Hapus file asli setelah konversi
+        return temp_mp4_path
+    else:
+        logger.error("Konversi video gagal: %s", result.stderr)
+        raise Exception("Konversi video ke MP4 gagal.")
+
 def process_video(video_path):
     try:
         logger.info("Memulai pemrosesan video: %s", video_path)
@@ -29,8 +50,12 @@ def process_video(video_path):
         # Buka video
         cap = cv2.VideoCapture(video_path)
         if not cap.isOpened():
-            logger.error("Gagal membuka video")
-            return None, "Error: Tidak dapat membuka video."
+            logger.warning("Format video tidak didukung, mencoba konversi ke MP4...")
+            video_path = convert_video_to_mp4(video_path)
+            cap = cv2.VideoCapture(video_path)
+            if not cap.isOpened():
+                logger.error("Gagal membuka video setelah konversi")
+                return None, "Error: Video tidak dapat dibuka setelah konversi."
         
         # Dapatkan FPS
         fps = cap.get(cv2.CAP_PROP_FPS)
@@ -122,13 +147,23 @@ def process_video(video_path):
             out.release()
 
 # Setup antarmuka Gradio
-iface = gr.Interface(
-    fn=process_video,
-    inputs=gr.Video(label="Unggah Video (maks. 30 detik)"),
-    outputs=[gr.Video(label="Hasil Deteksi Helm Keselamatan"), gr.Textbox(label="Status")],
-    title="Deteksi Helm Keselamatan",
-    description="Unggah video pendek (maks. 30 detik, resolusi rendah) untuk mendeteksi helm keselamatan menggunakan YOLOv8 (keremberke/yolov8m-hard-hat-detection)."
-)
+with gr.Blocks() as iface:
+    gr.Markdown("## Deteksi Helm Keselamatan")
+    with gr.Row():
+        with gr.Column(scale=1):
+            video_input = gr.Video(label="Unggah Video (maks. 30 detik)", interactive=True)
+            detect_vid_btn = gr.Button("Detect Objects")
+            video_examples = gr.Examples(
+                examples=[["./examples/video.mp4"]],  # Sesuaikan path dengan file contoh di repositori
+                inputs=[video_input],
+                label="Contoh Video",
+            )
+        with gr.Column(scale=1):
+            video_output = gr.Video(label="Hasil Deteksi Helm Keselamatan")
+    status_text = gr.Textbox(label="Status", interactive=False)
+    detect_vid_btn.click(fn=process_video, inputs=video_input, outputs=[video_output, status_text])
+
+    iface.launch()
 
 # Luncurkan aplikasi
 if __name__ == "__main__":