Delete app.py

app.py

@@ -1,184 +0,0 @@
-# this code is largely inspired by https://huggingface.co/spaces/hysts/ControlNet-with-Anything-v4/blob/main/app_scribble_interactive.py
-# Thank you, hysts!
-
-import sys
-sys.path.append('./src/ControlNetInpaint/')
-# functionality based on https://github.com/mikonvergence/ControlNetInpaint
-
-import gradio as gr
-#import torch
-#from torch import autocast // only for GPU
-
-from PIL import Image
-import numpy as np
-from io import BytesIO
-import os
-
-# Usage
-# 1. Upload image or fill with white
-# 2. Sketch the mask (image->[image,mask]
-# 3. Sketch the content of the mask
-
-# Global Storage
-CURRENT_IMAGE={'image' : None,
-               'mask' : None,
-               'guide' : None
-            }
-
-HEIGHT,WIDTH=512,512
-
-## SETUP PIPE
-
-from diffusers import StableDiffusionInpaintPipeline, ControlNetModel, UniPCMultistepScheduler
-from src.pipeline_stable_diffusion_controlnet_inpaint import *
-from diffusers.utils import load_image
-from controlnet_aux import HEDdetector
-
-hed = HEDdetector.from_pretrained('lllyasviel/ControlNet')
-
-controlnet = ControlNetModel.from_pretrained(
-    "fusing/stable-diffusion-v1-5-controlnet-scribble", torch_dtype=torch.float16
-)
-pipe = StableDiffusionControlNetInpaintPipeline.from_pretrained(
-     "runwayml/stable-diffusion-inpainting", controlnet=controlnet, torch_dtype=torch.float16
- )
-
-pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
-
-if torch.cuda.is_available():
-    # Remove if you do not have xformers installed
-    # see https://huggingface.co/docs/diffusers/v0.13.0/en/optimization/xformers#installing-xformers
-    # for installation instructions
-    pipe.enable_xformers_memory_efficient_attention()
-
-    pipe.to('cuda')
-
-# Functions
-
-def get_guide(image):  
-    return hed(image,scribble=True)
-
-def set_mask(image):
-    img=image['image'][...,:3]
-    mask=1*(image['mask'][...,:3]>0)
-    # save vars
-    CURRENT_IMAGE['image']=img
-    CURRENT_IMAGE['mask']=mask
-
-    guide=get_guide(img)
-    CURRENT_IMAGE['guide']=np.array(guide)
-    guide=255-np.asarray(guide)  
-
-    seg_img = guide*(1-mask) + mask*192
-    preview = img * (seg_img==255)
-
-    vis_image=(preview/2).astype(seg_img.dtype) + seg_img * (seg_img!=255)
-
-    return vis_image
-
-def generate(image,
-             prompt,
-             num_steps,
-             text_scale,
-             sketch_scale,
-             seed):
-
-    sketch=(255*(image['mask'][...,:3]>0)).astype(CURRENT_IMAGE['image'].dtype)
-    mask=CURRENT_IMAGE['mask']
-
-    CURRENT_IMAGE['guide']=(CURRENT_IMAGE['guide']*(mask==0) + sketch*(mask!=0)).astype(CURRENT_IMAGE['image'].dtype)
-
-    mask_img=255*CURRENT_IMAGE['mask'].astype(CURRENT_IMAGE['image'].dtype)
-
-    new_image = pipe(
-      prompt,
-      num_inference_steps=num_steps,
-      guidance_scale=text_scale,
-      generator=torch.manual_seed(seed),
-      image=Image.fromarray(CURRENT_IMAGE['image']),
-      control_image=Image.fromarray(CURRENT_IMAGE['guide']),
-      controlnet_conditioning_scale=sketch_scale,
-      mask_image=Image.fromarray(mask_img)
-    ).images
-
-    return new_image
-
-def create_demo(max_images=12, default_num_images=3):
-  
-    with gr.Blocks(theme=gr.themes.Default(font=[gr.themes.GoogleFont("IBM Plex Mono"), "ui-monospace","monospace"]),
-                   css=".gradio-container {background-color: #f2faf2}"
-                  ) as demo:
-        gr.Markdown('## Cut and Sketch ✂️▶️✏️')
-        gr.Markdown('**Usage**')
-        gr.Markdown('1. Upload your image to the left window')
-        gr.Markdown('2. Draw the mask in the left window (Cut ✂️)')
-        gr.Markdown('3. Click `Set Mask`')
-        gr.Markdown('4. In the right window, sketch a replacement object! (Sketch ✏️)')
-        gr.Markdown('5. (You can also provide a text prompt if you want)')
-        gr.Markdown('6. 🔮 Click Generate! ')
-        
-        prompt = gr.Textbox(label='Prompt')
-
-        with gr.Row():
-            with gr.Column():
-                with gr.Row():
-                    input_image = gr.Image(source='upload',
-                                            shape=[HEIGHT,WIDTH],
-                                            type='numpy',
-                                          label='Mask Draw',
-                                            tool='sketch',
-                                            brush_radius=70)
-                    sketch_image = gr.Image(source='upload',
-                                            shape=[HEIGHT,WIDTH],
-                                            type='numpy',
-                                          label='Fill Draw',
-                                            tool='sketch',
-                                            brush_radius=15)
-                with gr.Row():
-                    mask_button = gr.Button(label='Set Mask', value='Set Mask')
-                    run_button = gr.Button(label='Generate', value='Generate')
-            output_image = gr.Gallery(
-                        label="Generated images",
-                        show_label=False,
-                        elem_id="gallery",
-                    )
-
-        with gr.Accordion('Advanced options', open=False):
-            num_steps = gr.Slider(label='Steps',
-                                minimum=1,
-                                maximum=100,
-                                value=20,
-                                step=1)
-            text_scale = gr.Slider(label='Text Guidance Scale',
-                                      minimum=0.1,
-                                      maximum=30.0,
-                                      value=7.5,
-                                      step=0.1)
-            seed = gr.Slider(label='Seed',
-                            minimum=-1,
-                            maximum=2147483647,
-                            step=1,
-                            randomize=True)  
-
-            sketch_scale = gr.Slider(label='Sketch Guidance Scale',
-                                      minimum=0.0,
-                                      maximum=1.0,
-                                      value=1.0,
-                                      step=0.05)                  
-
-        inputs = [
-          sketch_image,
-          prompt,
-          num_steps,
-          text_scale,
-          sketch_scale,
-          seed
-        ]
-
-        mask_button.click(fn=set_mask, inputs=input_image, outputs=sketch_image)     
-        run_button.click(fn=generate, inputs=inputs, outputs=output_image)
-        return demo
-
-if __name__ == '__main__':
-    demo = create_demo()
-    demo.queue().launch()