fix code

app.py

@@ -25,22 +25,9 @@ model, transform = depth_pro.create_model_and_transforms()
 model = model.to(device)
 model.eval()
 
-def resize_image(image_path, max_size=1536):
-    with Image.open(image_path) as img:
-        # Calculate the new size while maintaining aspect ratio
-        ratio = max_size / max(img.size)
-        new_size = tuple([int(x * ratio) for x in img.size])
-        
-        # Resize the image
-        img = img.resize(new_size, Image.LANCZOS)
-        
-        # Create a temporary file
-        with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as temp_file:
-            img.save(temp_file, format="PNG")
-            return temp_file.name
 
 @spaces.GPU(duration=20)
-def predict(frame): 
+def predict(frame):
     image = transform(frame)
     image = image.to(device)
     prediction = model.infer(image)
@@ -61,12 +48,10 @@ def run_rerun(path_to_video):
                 ),
                 rrb.Spatial2DView(origin="/world/camera/image"),
             ),
-        )
+        ),
         collapse_panels=True,
     )
 
-    
-
     rr.send_blueprint(blueprint)
     yield stream.read()
 
@@ -78,13 +63,11 @@ def run_rerun(path_to_video):
         if not read:
             break
 
-        
         frame = cv2.resize(frame, (320, 240))
         frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
 
-        
         rr.set_time_sequence("frame", frame_idx)
-        rr.log("world/camera/image", rr.Image(frame))    
+        rr.log("world/camera/image", rr.Image(frame))
         yield stream.read()
 
         image = transform(frame)
@@ -95,7 +78,7 @@ def run_rerun(path_to_video):
             rr.Pinhole(
                 width=frame.shape[1],
                 height=frame.shape[0],
-                focal_length=,
+                focal_length=focal_length,
                 principal_point=(frame.shape[1] / 2, frame.shape[0] / 2),
                 image_plane_distance=depth.max(),
             ),
@@ -111,7 +94,6 @@ def run_rerun(path_to_video):
         yield stream.read()
 
 
-
 @spaces.GPU(duration=20)
 def estimate_depth(image):
     prediction = model.infer(image)
@@ -119,26 +101,12 @@ def estimate_depth(image):
     focal_length = prediction["focallength_px"].item()
 
     return depth, focal_length
-    
 
 
-video_path = Path("hd-cat.mp4")
-
-# Load video
-frames = []
-video = cv2.VideoCapture("hd-cat2.mp4")
-while True:
-    read, frame = video.read()
-    if not read:
-        break
-    frame = cv2.resize(frame, (320, 240))
-    frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
-    frames.append(frame)
-
 with gr.Blocks() as demo:
     video = gr.Video(interactive=True, label="Video")
     visualize = gr.Button("Visualize ML Depth Pro")
-            
+
     with gr.Row():
         viewer = Rerun(
             streaming=True,