Delete app.py

app.py

@@ -1,158 +0,0 @@
-import gradio as gr
-import numpy as np
-from PIL import Image
-from transformers import pipeline
-from diffusers import StableDiffusionDepth2ImgPipeline, StableDiffusionPipeline, StableDiffusionControlNetPipeline, StableDiffusionUpscalePipeline,  StableDiffusionImg2ImgPipeline, AutoPipelineForImage2Image
-from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler, DPMSolverMultistepScheduler
-
-import torch
-from controlnet_aux import HEDdetector
-from diffusers.utils import load_image
-from huggingface_hub import notebook_login, login
-import concurrent.futures
-from threading import Thread
-
-hidden_booster_text = "beautiful face, beautiful hand, small boobs, a cup"
-hidden_negative = "big boobs, huge boobs, sexy, dirty, d cup, e cup, g cup, slutty, badhandv4, ng_deepnegative_v1_75t, worst quality, low quality, extra digits, text, signature, bad anatomy, mutated hand, error, missing finger, cropped, worse quality, bad quality, lowres, floating limbs, bad hands, anatomical nonsense"
-
-hed = HEDdetector.from_pretrained('lllyasviel/ControlNet')
-
-controlnet_scribble = ControlNetModel.from_pretrained(
-    "lllyasviel/sd-controlnet-scribble", torch_dtype=torch.float16
-)
-
-pipe_scribble = StableDiffusionControlNetPipeline.from_single_file(
-    "https://huggingface.co/shellypeng/anime-god/blob/main/animeGod_v10.safetensors", controlnet=controlnet_scribble,
-    torch_dtype=torch.float16,
-)
-
-pipe_scribble.load_textual_inversion("shellypeng/bad-prompt")
-pipe_scribble.load_textual_inversion("shellypeng/badhandv4")
-# pipe.load_textual_inversion("shellypeng/easynegative")
-pipe_scribble.load_textual_inversion("shellypeng/deepnegative")
-pipe_scribble.load_textual_inversion("shellypeng/verybadimagenegative")
-pipe_scribble.scheduler = DPMSolverMultistepScheduler.from_config(pipe_scribble.scheduler.config, use_karras_sigmas=True)
-# pipe.enable_model_cpu_offload()
-def dummy(images, **kwargs):
-    return images, False
-pipe_scribble.safety_checker = lambda images, **kwargs: (images, [False] * len(images))
-pipe_scribble.to("cuda")
-
-def scribble_to_image(text, input_img):
-    """
-    pass the sd model and do scribble to image
-    include Adetailer, detail tweaker lora, prompt backend include: beautiful eyes, beautiful face, beautiful hand, (maybe infer from user's prompt for gesture and facial
-    expression to improve hand)
-    """
-    # change param "bag" below to text, image param below to input_img
-    input_img = Image.fromarray(input_img)
-    input_img = hed(input_img, scribble=True)
-    input_img = load_image(input_img)
-    # global prompt
-    prompt = text + hidden_booster_text
-    res_image0 = pipe_scribble(prompt, input_img, negative_prompt=hidden_negative, num_inference_steps=40).images[0]
-    res_image1 = pipe_scribble(prompt, input_img, negative_prompt=hidden_negative, num_inference_steps=40).images[0]
-    res_image2 = pipe_scribble(prompt, input_img, negative_prompt=hidden_negative, num_inference_steps=40).images[0]
-    res_image3 = pipe_scribble(prompt, input_img, negative_prompt=hidden_negative, num_inference_steps=40).images[0]
-
-    return res_image0, res_image1, res_image2, res_image3
-
-theme = gr.themes.Soft(
-    primary_hue="orange",
-    secondary_hue="orange",
-).set(
-    block_background_fill='*primary_50'
-)
-
-pipe_img2img = StableDiffusionImg2ImgPipeline.from_single_file("https://huggingface.co/shellypeng/anime-god/blob/main/animeGod_v10.safetensors",
-                                                               torch_dtype=torch.float16)
-pipe_img2img.load_lora_weights("shellypeng/detail-tweaker")
-pipe_img2img.fuse_lora(lora_scale=0.1)
-pipe_img2img.load_textual_inversion("shellypeng/bad-prompt")
-pipe_img2img.load_textual_inversion("shellypeng/badhandv4")
-# pipe.load_textual_inversion("shellypeng/easynegative")
-pipe_img2img.load_textual_inversion("shellypeng/deepnegative")
-pipe_img2img.load_textual_inversion("shellypeng/verybadimagenegative")
-pipe_img2img.scheduler = DPMSolverMultistepScheduler.from_config(pipe_img2img.scheduler.config, use_karras_sigmas=True)
-# pipe.enable_model_cpu_offload()
-def dummy(images, **kwargs):
-    return images, False
-pipe_img2img.safety_checker = lambda images, **kwargs: (images, [False] * len(images))
-pipe_img2img = pipe_img2img.to("cuda")
-
-def real_img2img_to_anime(text, input_img):
-    """
-    pass the sd model and do scribble to image
-    include Adetailer, detail tweaker lora, prompt backend include: beautiful eyes, beautiful face, beautiful hand, (maybe infer from user's prompt for gesture and facial
-    expression to improve hand)
-    """
-    input_img = Image.fromarray(input_img)
-    input_img = load_image(input_img)
-    prompt = text + hidden_booster_text
-    # input_img = depth_estimator(input_img)['depth']
-    res_image0 = pipe_img2img(prompt, input_img, negative_prompt=hidden_negative, num_inference_steps=40).images[0]
-    res_image1 = pipe_img2img(prompt, input_img, negative_prompt=hidden_negative, num_inference_steps=40).images[0]
-    res_image2 = pipe_img2img(prompt, input_img, negative_prompt=hidden_negative, num_inference_steps=40).images[0]
-    res_image3 = pipe_img2img(prompt, input_img, negative_prompt=hidden_negative, num_inference_steps=40).images[0]
-
-    return res_image0, res_image1, res_image2, res_image3
-
-
-theme = gr.themes.Soft(
-    primary_hue="orange",
-    secondary_hue="orange",
-).set(
-    block_background_fill='*primary_50'
-)
-
-
-generator = torch.manual_seed(33)
-
-with gr.Blocks(theme=theme, css="footer {visibility: hidden}", title="ShellAI Apps") as iface:
-    with gr.Tab("Animefier"):
-        with gr.Row(equal_height=True):
-            with gr.Column():
-                prompt_box = gr.Textbox(label="Prompt", placeholder="Enter a prompt")
-                image_box = gr.Image(label="Input Image", height=350)
-                gen_btn = gr.Button(value="Generate")
-        with gr.Row(equal_height=True):
-            global image1
-            global image2
-            global image3
-            global image4
-            image1 = gr.Image()
-            image2 = gr.Image()
-            image3 = gr.Image()
-            image4 = gr.Image()
-
-        def mult_thread(prompt_box, image_box):
-            with concurrent.futures.ThreadPoolExecutor(max_workers=12000) as executor:
-                future = executor.submit(real_img2img_to_anime, prompt_box, image_box)
-                image1, image2, image3, image4 = future.result()
-            return image1, image2, image3, image4
-
-        gen_btn.click(mult_thread, [prompt_box, image_box], [image1, image2, image3, image4])
-    with gr.Tab("AniSketch"):
-        with gr.Row(equal_height=True):
-            with gr.Column():
-                prompt_box = gr.Textbox(label="Prompt", placeholder="Enter a prompt")
-                image_box = gr.Image(label="Input Image", height=350)
-                gen_btn = gr.Button(value="Generate")
-        with gr.Row(equal_height=True):
-            image1 = gr.Image()
-            image2 = gr.Image()
-            image3 = gr.Image()
-            image4 = gr.Image()
-
-        def mult_thread(prompt_box, image_box):
-            with concurrent.futures.ThreadPoolExecutor(max_workers=12000) as executor:
-                future = executor.submit(scribble_to_image, prompt_box, image_box)
-                image1, image2, image3, image4 = future.result()
-            return image1, image2, image3, image4
-
-        gen_btn.click(mult_thread, [prompt_box, image_box], [image1, image2, image3, image4])
-
-iface.launch(inline=False)
-
-
-