Update app.py

app.py

@@ -173,18 +173,30 @@ def infer(frameA, frameB):
     
     return "predicted_flow.jpg", ["flofile.flo"]
 
+title="RAFT Optical Flow"
 description="<p style='text-align:center'>PyTorch way to Generate optical flow image & .flo file from 2 consecutive frames with RAFT model</p>" 
 
-gr.Interface(fn=infer, 
-             inputs=[
-                 gr.Image(source="upload", type="filepath", label="frame 1"), 
-                 gr.Image(source="upload", type="filepath", label="frame 2")], 
-             outputs=[
-                 gr.Image(label="flow image"), 
-                 gr.Files(label="flow file")], 
-             title="RAFT Optical Flow",
-             description=description,
-             examples=[
-                 ["examples/basket1.JPG", "examples/basket2.JPG"]
-             ]
-            ).launch()
+with gr.Blocks() as block:
+    with gr.Column(elem_id="col-container"):
+        gr.HTML(title)
+        gr.HTML(description)
+
+        frame1_inp = gr.Image(source="upload", type="filepath", label="frame 1")
+        frame2_inp = gr.Image(source="upload", type="filepath", label="frame 2")]
+        
+        submit_btn = gr.Button("Submit")
+        
+        flow_img_out = gr.Image(label="flow image") 
+        flow_file_out = gr.Files(label="flow file")]
+        
+        
+        examples=[['basket1.jpg'], ['basket2.jpg']]
+        ex = gr.Examples(examples=examples, fn=infer, inputs=[frame1_inp, frame2_inp], outputs=[flow_img_out, flow_file_out], cache_examples=True, run_on_click=True)
+        ex.dataset.headers = [""]
+        
+        
+
+    submit_btn.click(fn=infer, inputs=[frame1_inp, frame2_inp], outputs=[flow_img_out, flow_file_out])
+    
+
+block.launch()