Update app.py

app.py

@@ -1,8 +1,8 @@
 from ultralytics import YOLO
 from PIL import Image
 import gradio as gr
-from tqdm.auto import tqdm
 from huggingface_hub import snapshot_download
+from tqdm.auto import tqdm
 import os
 import tempfile
 import cv2  # OpenCV for video processing
@@ -12,9 +12,7 @@ model_path = "best_int8_openvino_model"
 
 def load_model(repo_id):
     download_dir = snapshot_download(repo_id)
-    print(download_dir)
-    path = os.path.join(download_dir, "best_int8_openvino_model")
-    print(path)
+    path  = os.path.join(download_dir, "best_int8_openvino_model")
     detection_model = YOLO(path, task='detect')
     return detection_model
 
@@ -26,18 +24,15 @@ def process_image(pilimg):
     out_pilimg = Image.fromarray(img_bgr[..., ::-1])  # RGB-order PIL image
     return out_pilimg
 
-
 def process_video(video):
-    print(video)
     video_reader = cv2.VideoCapture(video)
-    print(video_reader)
     nb_frames = int(video_reader.get(cv2.CAP_PROP_FRAME_COUNT))
     frame_h = int(video_reader.get(cv2.CAP_PROP_FRAME_HEIGHT))
     frame_w = int(video_reader.get(cv2.CAP_PROP_FRAME_WIDTH))
     fps = video_reader.get(cv2.CAP_PROP_FPS)
 
     temp_dir = tempfile.mkdtemp()
-    output_path = os.path.join(temp_dir, "output.mp4")
+    output_path = os.path.join(temp_dir, "annotated_video.mp4")
     video_writer = cv2.VideoWriter(output_path,
                             cv2.VideoWriter_fourcc(*'mp4v'),
                             fps,
@@ -64,11 +59,13 @@ def process_video(video):
     cv2.waitKey(1)
     return output_path
 
-
 REPO_ID = "leryongfeng/iti107_assignment"
 detection_model = load_model(REPO_ID)
+
+# Define a message to display at the top of the app
 message = "Sword and Bow detection model"
 
+
 # Create the interface for image upload
 image_interface = gr.Interface(fn=process_image, 
                                inputs=gr.Image(type="pil"),