Update app.py

app.py

@@ -280,20 +280,20 @@ def infer():
     print(res)
     
     res = Image.fromarray(res)
-    res.save('wraped.jpg')
+    res.save('warped.jpg')
 
     blend2 = Image.open('raw_frame2.jpg')
     blend2 = Image.blend(res,blend2,0.5)
     blend2.save("blended2.jpg")
 
-    pil2diff_blend = Image.open("blended2.jpg")
+    pil2diff_blend = Image.open("warped.jpg")
     canny_image = get_canny_filter(pil2diff_blend)
     diffused_blend = generate_images(prompt, canny_image, pil2diff_blend)
     print(f"DIFFUSED IMG: {diffused_blend[1]}")
     
     diffused_blend[1].save("diffused_blended_2.jpg")
     
-    return "done", "predicted_flow.jpg", ["flofile.flo"], "diffused_input1.jpg", "diffused_blended_2.jpg", 'wraped.jpg', "blended2.jpg"
+    return "done", "predicted_flow.jpg", ["flofile.flo"], "diffused_input1.jpg", "diffused_blended_2.jpg", 'warped.jpg', "blended2.jpg"
 ####################################
 # Bonus: Creating GIFs of predicted flows
 # ---------------------------------------
@@ -322,4 +322,4 @@ def infer():
 # ffmpeg -f image2 -framerate 30 -i predicted_flow_%d.jpg -loop -1 flow.gif
 
       
-gr.Interface(fn=infer, inputs=[], outputs=[gr.Textbox(), gr.Image(label="flow"), gr.Files(), gr.Image(label="diffused input"), gr.Image(), gr.Image(label="wraped flow to img2"), gr.Image(label="blended result to diffuse")]).launch()
+gr.Interface(fn=infer, inputs=[], outputs=[gr.Textbox(), gr.Image(label="flow"), gr.Files(), gr.Image(label="diffused input"), gr.Image(), gr.Image(label="warped flow to img2"), gr.Image(label="blended result to diffuse")]).launch()