Upload app.py

app.py

@@ -29,6 +29,7 @@ def get_demo_call(video_name):
     return ump_out
 
 def call_pitch(pitch):
+    start = time.time()
     std = (0.2104, 0.1986, 0.1829)
     mean = (0.3939, 0.3817, 0.3314)
     # Convert the mean and std to tensors
@@ -37,7 +38,7 @@ def call_pitch(pitch):
     ump_out = get_demo_call(pitch)
     pitch_tensor = (read_video(pitch,pts_unit='sec')[0].permute(-1,0,1,2)).unsqueeze(0)/255
     pitch_tensor = (pitch_tensor-mean)/std #normalize the pitch tensor
-    video_length = pitch_tensor.shape[2]/15
+    video_length = pitch_tensor.shape[2] #get video length to wait for the video to finish
     model = MobileNetSmall3D()
     model.load_state_dict(torch.load('weights/MobileNetSmall.pth',map_location=torch.device('cpu')))
     model.eval()
@@ -47,7 +48,9 @@ def call_pitch(pitch):
         output = model(pitch_tensor)
     output = F.softmax(output,dim=1)
     final_call = classify_pitch(output)
-    #time.sleep(video_length) #wait until the video is done to return the call
+    # time.sleep(video_length-1.5) #wait until the video is done to return the call
+    while time.time() - start < (video_length-5)/15: #wait until the video is done to return the call and go 2 frames early to seem speedy
+        time.sleep(0.1)
 
     return final_call,ump_out