delete bbox

app.py

@@ -1185,36 +1185,36 @@ with demo:
                    ddim_steps, guess_mode, strength, scale, seed, eta, condition_mode]
             run_button.click(fn=process_seg, inputs=ips, outputs=[result_gallery])
 
-        with gr.TabItem("Bbox"):
-            with gr.Row():
-                gr.Markdown("## UniControl Stable Diffusion with Object Bounding Boxes (MS-COCO)")
-            with gr.Row():
-                with gr.Column():
-                    input_image = gr.Image(source='upload', type="numpy")
-                    prompt = gr.Textbox(label="Prompt")
-                    run_button = gr.Button(label="Run")
-                    with gr.Accordion("Advanced options", open=False):
-                        num_samples = gr.Slider(label="Images", minimum=1, maximum=12, value=1, step=1)
-                        image_resolution = gr.Slider(label="Image Resolution", minimum=256, maximum=768, value=512,
-                                                     step=64)
-                        strength = gr.Slider(label="Control Strength", minimum=0.0, maximum=2.0, value=1.0, step=0.01)
-                        condition_mode = gr.Checkbox(label='Condition Extraction: RGB -> Bbox', value=True)
-                        guess_mode = gr.Checkbox(label='Guess Mode', value=False)
-                        confidence = gr.Slider(label="Confidence of Detection", minimum=0.1, maximum=1.0, value=0.4,
-                                               step=0.1)
-                        nms_thresh = gr.Slider(label="Nms Threshold", minimum=0.1, maximum=1.0, value=0.5, step=0.1)
-                        ddim_steps = gr.Slider(label="Steps", minimum=1, maximum=100, value=20, step=1)
-                        scale = gr.Slider(label="Guidance Scale", minimum=0.1, maximum=30.0, value=9.0, step=0.1)
-                        seed = gr.Slider(label="Seed", minimum=-1, maximum=2147483647, step=1, randomize=True)
-                        eta = gr.Number(label="eta (DDIM)", value=0.0)
-                        a_prompt = gr.Textbox(label="Added Prompt", value='best quality, extremely detailed, bright')
-                        n_prompt = gr.Textbox(label="Negative Prompt", value='longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality')
-                with gr.Column():
-                    result_gallery = gr.Gallery(label='Output', show_label=False, elem_id="gallery").style(grid=2,
-                                                                                                           height='auto')
-            ips = [input_image, prompt, a_prompt, n_prompt, num_samples, image_resolution, ddim_steps, guess_mode,
-                   strength, scale, seed, eta, confidence, nms_thresh, condition_mode]
-            run_button.click(fn=process_bbox, inputs=ips, outputs=[result_gallery])
+        # with gr.TabItem("Bbox"):
+        #     with gr.Row():
+        #         gr.Markdown("## UniControl Stable Diffusion with Object Bounding Boxes (MS-COCO)")
+        #     with gr.Row():
+        #         with gr.Column():
+        #             input_image = gr.Image(source='upload', type="numpy")
+        #             prompt = gr.Textbox(label="Prompt")
+        #             run_button = gr.Button(label="Run")
+        #             with gr.Accordion("Advanced options", open=False):
+        #                 num_samples = gr.Slider(label="Images", minimum=1, maximum=12, value=1, step=1)
+        #                 image_resolution = gr.Slider(label="Image Resolution", minimum=256, maximum=768, value=512,
+        #                                              step=64)
+        #                 strength = gr.Slider(label="Control Strength", minimum=0.0, maximum=2.0, value=1.0, step=0.01)
+        #                 condition_mode = gr.Checkbox(label='Condition Extraction: RGB -> Bbox', value=True)
+        #                 guess_mode = gr.Checkbox(label='Guess Mode', value=False)
+        #                 confidence = gr.Slider(label="Confidence of Detection", minimum=0.1, maximum=1.0, value=0.4,
+        #                                        step=0.1)
+        #                 nms_thresh = gr.Slider(label="Nms Threshold", minimum=0.1, maximum=1.0, value=0.5, step=0.1)
+        #                 ddim_steps = gr.Slider(label="Steps", minimum=1, maximum=100, value=20, step=1)
+        #                 scale = gr.Slider(label="Guidance Scale", minimum=0.1, maximum=30.0, value=9.0, step=0.1)
+        #                 seed = gr.Slider(label="Seed", minimum=-1, maximum=2147483647, step=1, randomize=True)
+        #                 eta = gr.Number(label="eta (DDIM)", value=0.0)
+        #                 a_prompt = gr.Textbox(label="Added Prompt", value='best quality, extremely detailed, bright')
+        #                 n_prompt = gr.Textbox(label="Negative Prompt", value='longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality')
+        #         with gr.Column():
+        #             result_gallery = gr.Gallery(label='Output', show_label=False, elem_id="gallery").style(grid=2,
+        #                                                                                                    height='auto')
+        #     ips = [input_image, prompt, a_prompt, n_prompt, num_samples, image_resolution, ddim_steps, guess_mode,
+        #            strength, scale, seed, eta, confidence, nms_thresh, condition_mode]
+        #     run_button.click(fn=process_bbox, inputs=ips, outputs=[result_gallery])
 
         with gr.TabItem("Outpainting"):
             with gr.Row():