Delete app_depth.py

app_depth.py

@@ -1,88 +0,0 @@
-# This file is adapted from https://github.com/lllyasviel/ControlNet/blob/f4748e3630d8141d7765e2bd9b1e348f47847707/gradio_depth2image.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('### Use a photo of your room and reimagine it with different styles')
-        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):
-                    is_depth_image = gr.Checkbox(label='Is depth image',
-                                                 value=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='Depth Resolution',
-                                                  minimum=128,
-                                                  maximum=512,
-                                                  value=384,
-                                                  step=1)
-                    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, photo from Pinterest, interior, cinematic photo, ultra-detailed, ultra-realistic, award-winning')
-                    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,
-            is_depth_image,
-        ]
-        prompt.submit(fn=process, inputs=inputs, outputs=result)
-        run_button.click(fn=process,
-                         inputs=inputs,
-                         outputs=result,
-                         api_name='depth')
-        examples = gr.Examples(examples=[["room.jpg","a room for gaming with gaming computers, gaming consoles, and gaming chairs"]],inputs = inputs, outputs = [result], cache_examples = True, fn = process)
-        
-    return demo
-
-
-if __name__ == '__main__':
-    from model import Model
-    model = Model()
-    demo = create_demo(model.process_depth)
-    demo.queue().launch()