clean up video files

app.py

@@ -13,7 +13,7 @@ from gradio_rerun import Rerun
 import spaces
 
 # Run the script to get pretrained models
-if not os.path.exists("checkpoints/depth_pro.pt"):
+if not os.path.exists("./checkpoints/depth_pro.pt"):
     print("downloading pretrained model")
     subprocess.run(["bash", "get_pretrained_models.sh"])
 
@@ -64,10 +64,11 @@ def run_rerun(path_to_video):
             break
 
         frame_idx += 1
-        if frame_idx % 10 != 0:
+        if frame_idx % 3 != 0:
             continue
 
-        frame = cv2.resize(frame, (320, 240))
+        # resize to avoid excessive time spent processing
+        frame = cv2.resize(frame, (640, 480))
         frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
 
         rr.set_time_sequence("frame", frame_idx)
@@ -91,13 +92,15 @@ def run_rerun(path_to_video):
 
         rr.log(
             "world/camera/depth",
-            # need 0.19 stable for this
-            # rr.DepthImage(depth, meter=1, depth_range=(depth.min(), depth.max())),
             rr.DepthImage(depth, meter=1),
         )
 
         yield stream.read()
 
+    # clean up
+    if os.exists(path_to_video):
+        os.remove(path_to_video)
+
 
 @spaces.GPU(duration=40)
 def estimate_depth(frame):