Create app_hough.py

app_hough.py

@@ -0,0 +1,97 @@
+# This file is adapted from https://github.com/lllyasviel/ControlNet/blob/f4748e3630d8141d7765e2bd9b1e348f47847707/gradio_hough2image.py
+# The original license file is LICENSE.ControlNet in this repo.
+import gradio as gr
+
+
+def create_demo(process, max_images=12, default_num_images=3):
+    with gr.Blocks() as demo:
+        with gr.Row():
+            gr.Markdown('## Control Stable Diffusion with Hough Line Maps')
+        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=max_images,
+                                            value=default_num_images,
+                                            step=1)
+                    image_resolution = gr.Slider(label='Image Resolution',
+                                                 minimum=256,
+                                                 maximum=512,
+                                                 value=512,
+                                                 step=256)
+                    detect_resolution = gr.Slider(label='Hough Resolution',
+                                                  minimum=128,
+                                                  maximum=512,
+                                                  value=512,
+                                                  step=1)
+                    mlsd_value_threshold = gr.Slider(
+                        label='Hough value threshold (MLSD)',
+                        minimum=0.01,
+                        maximum=2.0,
+                        value=0.1,
+                        step=0.01)
+                    mlsd_distance_threshold = gr.Slider(
+                        label='Hough distance threshold (MLSD)',
+                        minimum=0.01,
+                        maximum=20.0,
+                        value=0.1,
+                        step=0.01)
+                    num_steps = gr.Slider(label='Steps',
+                                          minimum=1,
+                                          maximum=100,
+                                          value=20,
+                                          step=1)
+                    guidance_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)
+                    a_prompt = gr.Textbox(
+                        label='Added Prompt',
+                        value='best quality, extremely detailed')
+                    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 = gr.Gallery(label='Output',
+                                    show_label=False,
+                                    elem_id='gallery').style(grid=2,
+                                                             height='auto')
+        inputs = [
+            input_image,
+            prompt,
+            a_prompt,
+            n_prompt,
+            num_samples,
+            image_resolution,
+            detect_resolution,
+            num_steps,
+            guidance_scale,
+            seed,
+            mlsd_value_threshold,
+            mlsd_distance_threshold,
+        ]
+        prompt.submit(fn=process, inputs=inputs, outputs=result)
+        run_button.click(fn=process,
+                         inputs=inputs,
+                         outputs=result,
+                         api_name='hough')
+    return demo
+
+
+if __name__ == '__main__':
+    from model import Model
+    model = Model()
+    demo = create_demo(model.process_hough)
+    demo.queue().launch()