Update app.py

app.py

@@ -195,21 +195,23 @@ def infer():
     flow_img = flow_to_image(predicted_flow).to("cpu")
 #     output_folder = "/tmp/"  # Update this to the folder of your choice
     write_jpeg(flow_img, f"predicted_flow.jpg")
-    input_image = flow_to_image(frames[100]).to("cpu")
-    write_jpeg(input_image, f"frame_input.jpg")
+    
+    #input_image = flow_to_image(frames[100]).to("cpu")
+    #write_jpeg(input_image, f"frame_input.jpg")
+    
     flo_file = write_flo(predicted_flow, "flofile.flo")
     #write_jpeg(frames[100], f"input_image.jpg")
     #res = warp_image(img1_batch, predicted_flow)
     
     # define a transform to convert a tensor to PIL image
-    #transform = T.ToPILImage()
+    transform = T.ToPILImage()
     
     # convert the tensor to PIL image using above transform
-    #img = transform(frames[100])
+    img = transform(img1_batch)
     
     # display the PIL image
     #img.show()
-    #img.save('frame_input.jpg')
+    img.save('frame_input.jpg')
     #res = get_warp_res("frame_input.jpg", predicted_flow, fname_output='warped.png')
     #print(res)
     return "done", "predicted_flow.jpg", ["flofile.flo"], 'frame_input.jpg'