.

app.py

@@ -180,7 +180,7 @@ def process_rgb(input, mask, indexes):
 
     return rgb
 
-def inference_on_file(target_image, model, custom_test_pipeline, bar_data):
+def inference_on_file(target_image, model, custom_test_pipeline, map_resume):
 
     target_image = target_image.name
     time_taken=-1
@@ -216,10 +216,7 @@ def inference_on_file(target_image, model, custom_test_pipeline, bar_data):
     
     output=apply_color_map(output,map_resume).transpose((1,2,0))
     bar_data = pd.DataFrame(map_resume)
-    print("map_resume", map_resume)
-    print("bar_data", bar_data)
-
-    return rgb1,rgb2,rgb3,output,bar_data
+    return rgb1,rgb2,rgb3,output
 
 def process_test_pipeline(custom_test_pipeline, bands=None):
     
@@ -249,8 +246,10 @@ custom_test_pipeline=process_test_pipeline(model.cfg.data.test.pipeline, None)
 
 
 bar_data = pd.DataFrame(map_resume)
+print("map_resume", map_resume)
+print("bar_data", bar_data)
 
-func = partial(inference_on_file, model=model, custom_test_pipeline=custom_test_pipeline, bar_data=bar_data)
+func = partial(inference_on_file, model=model, custom_test_pipeline=custom_test_pipeline, map_resume=map_resume)
 
 
 with gr.Blocks() as demo:
@@ -288,7 +287,7 @@ with gr.Blocks() as demo:
             out = gr.Image(image_mode='RGB', scale=10, label='Model prediction')
             # gr.Image(value='Legend.png', image_mode='RGB', scale=2, show_label=False)
   
-    btn.click(fn=func, inputs=inp, outputs=[inp1, inp2, inp3, out,bar_data])
+    btn.click(fn=func, inputs=inp, outputs=[inp1, inp2, inp3, out])
     
     with gr.Row():
         gr.Markdown(value='### Model prediction legend')