Upload app.py

app.py

@@ -96,10 +96,18 @@ with gr.Blocks(title=title,
     #
     # gr.HTML("""<h4 style="color:navy;">1-b. Or upload an image by clicking on the canvas.</h4>""")
 
-    with gr.Row():
-        input_url = gr.Textbox(label="Image URL", placeholder="")
-        input_image = gr.Image(type="filepath", image_mode="RGB", source="upload", optional=False, label="Input Image")
-        output_image = gr.Image(type="pil", label="Output")
+    # with gr.Row():
+    #     input_url = gr.Textbox(label="Image URL", placeholder="")
+    #     input_image = gr.Image(type="filepath", image_mode="RGB", source="upload", optional=False, label="Input Image")
+    #     output_image = gr.Image(type="pil", label="Output")
+
+    # gr.Interface(
+    #     inference,
+    #     [gr.inputs.Textbox(label="Image URL", placeholder=""),
+    #      gr.inputs.Image(type="filepath", image_mode="RGB", source="upload", optional=False, label="Input Image"),
+    #      gr.Slider(minimum=0.0, maximum=1.0, value=0.4, label="Minimum score"),
+    #     ],
+
 
     gr.Examples(['./d1.jpeg', './d2.jpeg', './d3.jpeg','./d4.jpeg','./d5.jpeg','./d6.jpeg'], inputs=input_image)
 
@@ -107,7 +115,7 @@ with gr.Blocks(title=title,
     # gr.HTML("""<h4 style="color:navy;">2. Then, click "Infer" button to predict object instances. It will take about 15-20 seconds (on cpu)</h4>""")
 
     send_btn = gr.Button("Submit")
-    send_btn.click(fn=inference, inputs=[[input_url],[input_image]], outputs=[output_image])
+    send_btn.click(fn=inference, inputs=[input_url,input_image], outputs=[output_image])
 
     # gr.HTML("""<br/>""")
     # gr.HTML("""<h4 style="color:navy;">Reference</h4>""")