Update app.py

app.py

@@ -103,7 +103,8 @@ def warpImage(im, vx, vy, cast_uint8=True):
 
 def get_warp_res(fname_image, fname_flow, fname_output='warped.png'):
     print(f"FNAME IMAGE: {fname_image}")
-    im2 = imread(fname_image)
+    #im2 = imread(fname_image)
+    im2 = fname_image
     print(f"FNAME IMAGE READED: {im2}")
     flow = fname_flow.cpu().detach().numpy()
     im_warped, _ = warpImage(im2, flow[:, :, 0], flow[:, :, 1])
@@ -203,18 +204,18 @@ def infer():
     flo_file = write_flo(predicted_flow, "flofile.flo")
     #write_jpeg(frames[100], f"input_image.jpg")
     #res = warp_image(img1_batch, predicted_flow)
-    my_frame = transforms(F.resize(frames[100], size=[520, 960]))
+    
     
     # define a transform to convert a tensor to PIL image
     transform = T.ToPILImage()
     
     # convert the tensor to PIL image using above transform
-    img = transform(my_frame)
+    img = transform(frame[100])
     
     # display the PIL image
     #img.show()
     img.save('frame_input.jpg')
-    res = get_warp_res("frame_input.jpg", predicted_flow, fname_output='warped.png')
+    res = get_warp_res(frame[100], predicted_flow, fname_output='warped.png')
     #print(res)
     return "done", "predicted_flow.jpg", ["flofile.flo"], 'frame_input.jpg'
 ####################################