Update app.py

app.py

@@ -295,111 +295,111 @@ def run_demo_server(pipe_depth, pipe_normal, pipe_dis):
                     cache_examples=False,
                 )
             
-            # with gr.Tab("Normal"):
-            #     with gr.Row():
-            #         with gr.Column():
-            #             normal_image_input = gr.Image(
-            #                 label="Input Image",
-            #                 type="filepath",
-            #             )
-            #             with gr.Row():
-            #                 normal_image_submit_btn = gr.Button(
-            #                     value="Estimate Normal", variant="primary"
-            #                 )
-            #                 normal_image_reset_btn = gr.Button(value="Reset")
-            #             with gr.Accordion("Advanced options", open=False):
-            #                 image_processing_res = gr.Radio(
-            #                     [
-            #                         ("Native", 0),
-            #                         ("Recommended", 768),
-            #                     ],
-            #                     label="Processing resolution",
-            #                     value=default_image_processing_res,
-            #                 )
-            #         with gr.Column():
-            #             normal_image_output_slider = ImageSlider(
-            #                 label="Predicted surface normal",
-            #                 type="filepath",
-            #                 show_download_button=True,
-            #                 show_share_button=True,
-            #                 interactive=False,
-            #                 elem_classes="slider",
-            #                 position=0.25,
-            #             )
-            #             normal_image_output_files = gr.Files(
-            #                 label="Normal outputs",
-            #                 elem_id="download",
-            #                 interactive=False,
-            #             )
-
-            #     filenames = []
-            #     filenames.extend(["normal_%d.jpg" %(i+1) for i in range(10)])
-            #     example_folder = os.path.join(os.path.dirname(__file__), "./images")
-            #     Examples(
-            #         fn=process_pipe_normal,
-            #         examples=[
-            #             os.path.join(example_folder, name)
-            #             for name in filenames
-            #         ],
-            #         inputs=[normal_image_input],
-            #         outputs=[normal_image_output_slider, normal_image_output_files],
-            #         # cache_examples=True,
-            #         # directory_name="examples_normal",
-            #         cache_examples=False,
-            #     )
+            with gr.Tab("Normal"):
+                with gr.Row():
+                    with gr.Column():
+                        normal_image_input = gr.Image(
+                            label="Input Image",
+                            type="filepath",
+                        )
+                        with gr.Row():
+                            normal_image_submit_btn = gr.Button(
+                                value="Estimate Normal", variant="primary"
+                            )
+                            normal_image_reset_btn = gr.Button(value="Reset")
+                        with gr.Accordion("Advanced options", open=False):
+                            image_processing_res = gr.Radio(
+                                [
+                                    ("Native", 0),
+                                    ("Recommended", 768),
+                                ],
+                                label="Processing resolution",
+                                value=default_image_processing_res,
+                            )
+                    with gr.Column():
+                        normal_image_output_slider = ImageSlider(
+                            label="Predicted surface normal",
+                            type="filepath",
+                            show_download_button=True,
+                            show_share_button=True,
+                            interactive=False,
+                            elem_classes="slider",
+                            position=0.25,
+                        )
+                        normal_image_output_files = gr.Files(
+                            label="Normal outputs",
+                            elem_id="download",
+                            interactive=False,
+                        )
+
+                filenames = []
+                filenames.extend(["normal_%d.jpg" %(i+1) for i in range(10)])
+                example_folder = os.path.join(os.path.dirname(__file__), "./images")
+                Examples(
+                    fn=process_pipe_normal,
+                    examples=[
+                        os.path.join(example_folder, 'depth', name)
+                        for name in filenames
+                    ],
+                    inputs=[normal_image_input],
+                    outputs=[normal_image_output_slider, normal_image_output_files],
+                    # cache_examples=True,
+                    # directory_name="examples_normal",
+                    cache_examples=False,
+                )
                 
-            # with gr.Tab("Dichotomous Segmentation"):
-            #     with gr.Row():
-            #         with gr.Column():
-            #             dis_image_input = gr.Image(
-            #                 label="Input Image",
-            #                 type="filepath",
-            #             )
-            #             with gr.Row():
-            #                 dis_image_submit_btn = gr.Button(
-            #                     value="Estimate Dichotomous Segmentation.", variant="primary"
-            #                 )
-            #                 dis_image_reset_btn = gr.Button(value="Reset")
-            #             with gr.Accordion("Advanced options", open=False):
-            #                 image_processing_res = gr.Radio(
-            #                     [
-            #                         ("Native", 0),
-            #                         ("Recommended", 768),
-            #                     ],
-            #                     label="Processing resolution",
-            #                     value=default_image_processing_res,
-            #                 )
-            #         with gr.Column():
-            #             dis_image_output_slider = ImageSlider(
-            #                 label="Predicted dichotomous image segmentation",
-            #                 type="filepath",
-            #                 show_download_button=True,
-            #                 show_share_button=True,
-            #                 interactive=False,
-            #                 elem_classes="slider",
-            #                 position=0.25,
-            #             )
-            #             dis_image_output_files = gr.Files(
-            #                 label="DIS outputs",
-            #                 elem_id="download",
-            #                 interactive=False,
-            #             )
-
-            #     filenames = []
-            #     filenames.extend(["dis_%d.jpg" %(i+1) for i in range(10)])
-            #     example_folder = os.path.join(os.path.dirname(__file__), "./images")
-            #     Examples(
-            #         fn=process_pipe_dis,
-            #         examples=[
-            #             os.path.join(example_folder, name)
-            #             for name in filenames
-            #         ],
-            #         inputs=[dis_image_input],
-            #         outputs=[dis_image_output_slider, dis_image_output_files],
-            #         # cache_examples=True,
-            #         # directory_name="examples_dis",
-            #         cache_examples=False,
-            #     )
+            with gr.Tab("Dichotomous Segmentation"):
+                with gr.Row():
+                    with gr.Column():
+                        dis_image_input = gr.Image(
+                            label="Input Image",
+                            type="filepath",
+                        )
+                        with gr.Row():
+                            dis_image_submit_btn = gr.Button(
+                                value="Estimate Dichotomous Segmentation.", variant="primary"
+                            )
+                            dis_image_reset_btn = gr.Button(value="Reset")
+                        with gr.Accordion("Advanced options", open=False):
+                            image_processing_res = gr.Radio(
+                                [
+                                    ("Native", 0),
+                                    ("Recommended", 768),
+                                ],
+                                label="Processing resolution",
+                                value=default_image_processing_res,
+                            )
+                    with gr.Column():
+                        dis_image_output_slider = ImageSlider(
+                            label="Predicted dichotomous image segmentation",
+                            type="filepath",
+                            show_download_button=True,
+                            show_share_button=True,
+                            interactive=False,
+                            elem_classes="slider",
+                            position=0.25,
+                        )
+                        dis_image_output_files = gr.Files(
+                            label="DIS outputs",
+                            elem_id="download",
+                            interactive=False,
+                        )
+
+                filenames = []
+                filenames.extend(["dis_%d.jpg" %(i+1) for i in range(10)])
+                example_folder = os.path.join(os.path.dirname(__file__), "./images")
+                Examples(
+                    fn=process_pipe_dis,
+                    examples=[
+                        os.path.join(example_folder, 'depth', name)
+                        for name in filenames
+                    ],
+                    inputs=[dis_image_input],
+                    outputs=[dis_image_output_slider, dis_image_output_files],
+                    # cache_examples=True,
+                    # directory_name="examples_dis",
+                    cache_examples=False,
+                )
 
 
         ### Image tab
@@ -436,71 +436,71 @@ def run_demo_server(pipe_depth, pipe_normal, pipe_dis):
             queue=False,
         )
         
-        # normal_image_submit_btn.click(
-        #     fn=process_image_check,
-        #     inputs=normal_image_input,
-        #     outputs=None,
-        #     preprocess=False,
-        #     queue=False,
-        # ).success(
-        #     fn=process_pipe_normal,
-        #     inputs=[
-        #         normal_image_input,
-        #         image_processing_res,
-        #     ],
-        #     outputs=[normal_image_output_slider, normal_image_output_files],
-        #     concurrency_limit=1,
-        # )
-
-        # normal_image_reset_btn.click(
-        #     fn=lambda: (
-        #         None,
-        #         None,
-        #         None,
-        #         default_image_processing_res,
-        #     ),
-        #     inputs=[],
-        #     outputs=[
-        #         normal_image_input,
-        #         normal_image_output_slider,
-        #         normal_image_output_files,
-        #         image_processing_res,
-        #     ],
-        #     queue=False,
-        # )
+        normal_image_submit_btn.click(
+            fn=process_image_check,
+            inputs=normal_image_input,
+            outputs=None,
+            preprocess=False,
+            queue=False,
+        ).success(
+            fn=process_pipe_normal,
+            inputs=[
+                normal_image_input,
+                image_processing_res,
+            ],
+            outputs=[normal_image_output_slider, normal_image_output_files],
+            concurrency_limit=1,
+        )
+
+        normal_image_reset_btn.click(
+            fn=lambda: (
+                None,
+                None,
+                None,
+                default_image_processing_res,
+            ),
+            inputs=[],
+            outputs=[
+                normal_image_input,
+                normal_image_output_slider,
+                normal_image_output_files,
+                image_processing_res,
+            ],
+            queue=False,
+        )
         
-        # dis_image_submit_btn.click(
-        #     fn=process_image_check,
-        #     inputs=dis_image_input,
-        #     outputs=None,
-        #     preprocess=False,
-        #     queue=False,
-        # ).success(
-        #     fn=process_pipe_dis,
-        #     inputs=[
-        #         dis_image_input,
-        #         image_processing_res,
-        #     ],
-        #     outputs=[dis_image_output_slider, dis_image_output_files],
-        #     concurrency_limit=1,
-        # )
-
-        # dis_image_reset_btn.click(
-        #     fn=lambda: (
-        #         None,
-        #         None,
-        #         None,
-        #         default_image_processing_res,
-        #     ),
-        #     inputs=[],
-        #     outputs=[
-        #         dis_image_input,
-        #         dis_image_output_slider,
-        #         dis_image_output_files,
-        #         image_processing_res,
-        #     ],
-        #     queue=False,
-        # )
+        dis_image_submit_btn.click(
+            fn=process_image_check,
+            inputs=dis_image_input,
+            outputs=None,
+            preprocess=False,
+            queue=False,
+        ).success(
+            fn=process_pipe_dis,
+            inputs=[
+                dis_image_input,
+                image_processing_res,
+            ],
+            outputs=[dis_image_output_slider, dis_image_output_files],
+            concurrency_limit=1,
+        )
+
+        dis_image_reset_btn.click(
+            fn=lambda: (
+                None,
+                None,
+                None,
+                default_image_processing_res,
+            ),
+            inputs=[],
+            outputs=[
+                dis_image_input,
+                dis_image_output_slider,
+                dis_image_output_files,
+                image_processing_res,
+            ],
+            queue=False,
+        )
 
         ### Server launch