Update app.py

app.py

@@ -1,344 +1,15 @@
 # -*- coding: utf-8 -*-
-"""Copy of Anime_Pack_Gradio.ipynb
+"""Unt24314212442itled0.ipynb
 
 Automatically generated by Colaboratory.
 
 Original file is located at
-    https://colab.research.google.com/drive/1RxVCwOkq3Q5qlEkQxhFGeUxICBujjEjR
+    https://colab.research.google.com/drive/1ESP90X7oIWvzEaEYUbh2Lp05cgpXSnZ8
 """
-
-
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-
-tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-zh-en")
-
-model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-zh-en")
-
 import gradio as gr
-import numpy as np
-from PIL import Image
-from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, DPMSolverMultistepScheduler, StableDiffusionImg2ImgPipeline
-
-import torch
-from controlnet_aux import HEDdetector
-from diffusers.utils import load_image
-
-import concurrent.futures
-from threading import Thread
-from compel import Compel
-
-
-from transformers import pipeline
-
-
-model_ckpt = "papluca/xlm-roberta-base-language-detection"
-pipe = pipeline("text-classification", model=model_ckpt)
-
-
-
-device="cuda" if torch.cuda.is_available() else "cpu"
-
-hidden_booster_text = ", loraeyes, beautiful face, 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"
-hidden_cn_booster_text = ",loraeyes漂亮的脸,小胸,贫乳,a罩杯"
-hidden_cn_negative = "大胸, ，, ！, 。, ；,巨乳,性感,脏,d罩杯,e罩杯,g罩杯,骚,骚气,badhandv4, ng_deepnegative_v1_75t"
-
-def translate(prompt):
-    trans_text = prompt
-    translated = model.generate(**tokenizer(trans_text, return_tensors="pt", padding=True))
-    tgt_text = [tokenizer.decode(t, skip_special_tokens=True) for t in translated]
-    tgt_text = ''.join(tgt_text)[:-1]
-    return tgt_text
-
-hed = HEDdetector.from_pretrained('lllyasviel/ControlNet')
-
-controlnet_scribble = ControlNetModel.from_pretrained(
-    "lllyasviel/sd-controlnet-scribble", torch_dtype=torch.float16, safety_checker=None, requires_safety_checker=False, )
-
-pipe_scribble = StableDiffusionControlNetPipeline.from_single_file(
-    "https://huggingface.co/shellypeng/anime-god/blob/main/animeGod_v10.safetensors", controlnet=controlnet_scribble, safety_checker=None, requires_safety_checker=False,
-    torch_dtype=torch.float16,
-)
-
-# pipe.load_lora_weights("shellypeng/detail-tweaker")
-# pipe.load_lora_weights("shellypeng/midjourney-anime")
-
-# pipe.load_lora_weights("shellypeng/animetarot")
-# pipe.load_lora_weights("shellypeng/anime-stickers-v3")
-# pipe.load_lora_weights("shellypeng/anime-magazine")
-
-# pipe_img2img.load_lora_weights("yenojunie/slit-pupils")
-
-# pipe_scribble.load_lora_weights("shellypeng/detail-tweaker")
-# pipe_scribble.fuse_lora(lora_scale=0.1)
-pipe_scribble.load_lora_weights("shellypeng/lora-eyes")
-pipe_scribble.fuse_lora(lora_scale=0.1)
-# pipe_scribble.load_lora_weights("shellypeng/beautiful-eyes")
-# pipe_scribble.fuse_lora(lora_scale=0.1)
-
-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()
-pipe_scribble.safety_checker = None
-pipe_scribble.requires_safety_checker = False
-pipe_scribble.to(device)
-
-def scribble_to_image(text, neg_prompt_box, 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)
-    """
-
-
-
-# if auto detect detects chinese => auto turn on chinese prompting checkbox
-    # 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
-    lang_check_label = pipe(text, top_k=1, truncation=True)[0]['label']
-    lang_check_score = pipe(text, top_k=1, truncation=True)[0]['score']
-    if lang_check_label == 'zh' and lang_check_score >= 0.85:
-        text = translate(text)
-    compel_proc = Compel(tokenizer=pipe_scribble.tokenizer, text_encoder=pipe_scribble.text_encoder)
-    prompt = text + hidden_booster_text
-    prompt_embeds = compel_proc(prompt)
-    negative_prompt = neg_prompt_box + hidden_negative
-    negative_prompt_embeds = compel_proc(negative_prompt)
-
-    res_image0 = pipe_scribble(image=input_img, prompt_embeds=prompt_embeds, negative_prompt_embeds=negative_prompt_embeds, num_inference_steps=40).images[0]
-    res_image1 = pipe_scribble(image=input_img, prompt_embeds=prompt_embeds, negative_prompt_embeds=negative_prompt_embeds, num_inference_steps=40).images[0]
-    res_image2 = pipe_scribble(image=input_img, prompt_embeds=prompt_embeds, negative_prompt_embeds=negative_prompt_embeds, num_inference_steps=40).images[0]
-    res_image3 = pipe_scribble(image=input_img, prompt_embeds=prompt_embeds, negative_prompt_embeds=negative_prompt_embeds, num_inference_steps=40).images[0]
-
-    return res_image0, res_image1, res_image2, res_image3
-
-def real_img2img_to_anime(text, neg_prompt_box, 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)
-    lang_check_label = pipe(text, top_k=1, truncation=True)[0]['label']
-    lang_check_score = pipe(text, top_k=1, truncation=True)[0]['score']
-    if lang_check_label == 'zh' and lang_check_score >= 0.85:
-        text = translate(text)
-
-    compel_proc = Compel(tokenizer=pipe_scribble.tokenizer, text_encoder=pipe_scribble.text_encoder)
-    prompt = text + hidden_booster_text
-    prompt_embeds = compel_proc(prompt)
-
-    negative_prompt = neg_prompt_box + hidden_negative
-    negative_prompt_embeds = compel_proc(negative_prompt)
-    # input_img = depth_estimator(input_img)['depth']
-    res_image0 = pipe_img2img(image=input_img, strength=0.6, prompt_embeds=prompt_embeds, negative_prompt_embeds=negative_prompt_embeds, num_inference_steps=40).images[0]
-    res_image1 = pipe_img2img(image=input_img, strength=0.6, prompt_embeds=prompt_embeds, negative_prompt_embeds=negative_prompt_embeds, num_inference_steps=40).images[0]
-    res_image2 = pipe_img2img(image=input_img, strength=0.6, prompt_embeds=prompt_embeds, negative_prompt_embeds=negative_prompt_embeds, num_inference_steps=40).images[0]
-    res_image3 = pipe_img2img(image=input_img, strength=0.6, prompt_embeds=prompt_embeds, negative_prompt_embeds=negative_prompt_embeds, 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'
-)
-
-# %cd /content/drive/MyDrive/stable-diffusion-webui-colab/stable-diffusion-webui
-
-pipe_img2img = StableDiffusionImg2ImgPipeline.from_single_file("https://huggingface.co/shellypeng/anime-god/blob/main/animeGod_v10.safetensors",
-                                                               torch_dtype=torch.float16, safety_checker=None, requires_safety_checker=False)
-
-# pipe_img2img.load_lora_weights("shellypeng/detail-tweaker")
-# pipe_img2img.fuse_lora(lora_scale=0.1)
-pipe_img2img.load_lora_weights("shellypeng/lora-eyes")
-pipe_img2img.fuse_lora(lora_scale=0.1)
-# pipe_img2img.load_lora_weights("shellypeng/beautiful-eyes")
-# 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()
-pipe_img2img.safety_checker = None
-pipe_img2img.requires_safety_checker = False
-pipe_img2img.to(device)
-
-# pipe_img2img.safety_checker = lambda images, **kwargs: (images, [False] * len(images))
-
-# depth_estimator = pipeline('depth-estimation')
-
-# controlnet_depth = ControlNetModel.from_pretrained(
-#     "lllyasviel/sd-controlnet-depth", torch_dtype=torch.float16
-# )
-
-
-# # models that worked well: anime god, pastel dream,
-# # https://huggingface.co/shellypeng/featureless/tree/main
-# pipe_depth = StableDiffusionControlNetPipeline.from_single_file(
-#     "https://huggingface.co/shellypeng/anime-god/blob/main/animeGod_v10.safetensors", controlnet=controlnet_depth,
-#     torch_dtype=torch.float16,
-# )
-# # pipe = StableDiffusionControlNetPipeline.from_pretrained("furusu/SSD-1B-anime",
-# #     torch_dtype=torch.float16
-# # )
-
-# pipe_depth.load_lora_weights("shellypeng/detail-tweaker")
-# pipe_depth.fuse_lora(lora_scale=0.1)
-# # pipe.load_lora_weights("shellypeng/stylized-3d")
-# # pipe.load_lora_weights("shellypeng/midjourney-anime")
-
-# # pipe.load_lora_weights("shellypeng/animetarot")
-# # pipe.load_lora_weights("shellypeng/anime-stickers-v3")
-# # pipe.load_lora_weights("shellypeng/anime-magazine")
-
-
-
-# pipe_depth.load_textual_inversion("shellypeng/bad-prompt")
-# pipe_depth.load_textual_inversion("shellypeng/badhandv4")
-# # pipe.load_textual_inversion("shellypeng/easynegative")
-# pipe_depth.load_textual_inversion("shellypeng/deepnegative")
-# pipe_depth.load_textual_inversion("shellypeng/verybadimagenegative")
-# pipe_depth.scheduler = DPMSolverMultistepScheduler.from_config(pipe_depth.scheduler.config, use_karras_sigmas=True)
-# # pipe.enable_model_cpu_offload()
-# def dummy(images, **kwargs):
-#     return images, False
-# pipe_depth.safety_checker = lambda images, **kwargs: (images, [False] * len(images))
-# pipe_depth.to(device)
-# # pipe.load_lora_weights("shellypeng/detail-tweaker", weight_name="add_detail.safetensors")
-
-# # load textual inversion negative embeddings!!!: pipe.load_textual_inversion("sd-concepts-library/cat-toy")
-
-# def real_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)
-#     input_img = depth_estimator(input_img)['depth']
-#     res_image0 = pipe_depth(prompt, input_img, negative_prompt=hidden_negative, num_inference_steps=40).images[0]
-#     res_image1 = pipe_depth(prompt, input_img, negative_prompt=hidden_negative, num_inference_steps=40).images[0]
-#     res_image2 = pipe_depth(prompt, input_img, negative_prompt=hidden_negative, num_inference_steps=40).images[0]
-#     res_image3 = pipe_depth(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'
-# )
-
-def zh_prompt_info(text, neg_text, chinese_check):
-    can_raise_info = ""
-    lang_check_label = pipe(text, top_k=1, truncation=True)[0]['label']
-    lang_check_score = pipe(text, top_k=1, truncation=True)[0]['score']
-    neg_lang_check_label = pipe(neg_text, top_k=1, truncation=True)[0]['label']
-    neg_lang_check_score = pipe(neg_text, top_k=1, truncation=True)[0]['score']
-    print(lang_check_label)
-    if lang_check_label == 'zh' and lang_check_score >= 0.85:
-        if not chinese_check:
-            chinese_check = True
-            can_raise_info = "zh"
-        if neg_lang_check_label == 'en' and neg_lang_check_score >= 0.85:
-            can_raise_info = "invalid"
-            return True, can_raise_info
-    elif lang_check_label == 'en' and lang_check_score >= 0.85:
-        if chinese_check:
-            chinese_check = False
-            can_raise_info = "en"
-        if neg_lang_check_label == 'zh' and neg_lang_check_score >= 0.85:
-            can_raise_info = "invalid"
-            return False, can_raise_info
-    return chinese_check, can_raise_info
-def mult_thread_img2img(prompt_box, neg_prompt_box, image_box):
-    with concurrent.futures.ThreadPoolExecutor(max_workers=12000) as executor:
-        future = executor.submit(real_img2img_to_anime, prompt_box, neg_prompt_box, image_box)
-        image1, image2, image3, image4 = future.result()
-    return image1, image2, image3, image4
-def mult_thread_scribble(prompt_box, neg_prompt_box, image_box):
-    with concurrent.futures.ThreadPoolExecutor(max_workers=12000) as executor:
-        future = executor.submit(scribble_to_image, prompt_box, neg_prompt_box, image_box)
-        image1, image2, image3, image4 = future.result()
-    return image1, image2, image3, image4
-def mult_thread_lang_class(prompt_box, neg_prompt_box, chinese_check):
-
-    with concurrent.futures.ThreadPoolExecutor(max_workers=12000) as executor:
-        future = executor.submit(zh_prompt_info, prompt_box, neg_prompt_box, chinese_check)
-        chinese_check, can_raise_info = future.result()
-    if can_raise_info == "zh":
-        gr.Info("Chinese Language Detected, Switching to Chinese Prompt Mode")
-    elif can_raise_info == "en":
-        gr.Info("English Language Detected, Disabling Chinese Prompt Mode")
-    return chinese_check
-
-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():
-                with gr.Row(equal_height=True):
-                    with gr.Column(scale=4):
-                        prompt_box = gr.Textbox(label="Prompt", placeholder="Enter a prompt", lines=3)
-                        neg_prompt_box = gr.Textbox(label="Negative Prompt", placeholder="Enter a negative prompt(things you don't want to include in the generated image)", lines=3)
-                    with gr.Row(equal_height=True):
-                        chinese_check = gr.Checkbox(label="Chinese Prompt Mode", info="Click here to enable Chinese Prompting（点此触发中文提示词输入）")
-
-                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(label="Result 1")
-            image2 = gr.Image(label="Result 2")
-            image3 = gr.Image(label="Result 3")
-            image4 = gr.Image(label="Result 4")
-
-
-        gr.on(triggers=[prompt_box.submit, gen_btn.click],fn=mult_thread_lang_class, inputs=[prompt_box, neg_prompt_box, chinese_check], outputs=[chinese_check], show_progress=False)
-        gr.on(triggers=[prompt_box.submit, gen_btn.click],fn=mult_thread_img2img, inputs=[prompt_box, neg_prompt_box, image_box], outputs=[image1, image2, image3, image4])
-
-    with gr.Tab("AniSketch"):
-        with gr.Row(equal_height=True):
-            with gr.Column():
-                with gr.Row(equal_height=True):
-                    with gr.Column(scale=4):
-                        prompt_box = gr.Textbox(label="Prompt", placeholder="Enter a prompt", lines=3)
-                        neg_prompt_box = gr.Textbox(label="Negative Prompt", placeholder="Enter a negative prompt(things you don't want to include in the generated image)", lines=3)
-                    with gr.Row(equal_height=True):
-                        chinese_check = gr.Checkbox(label="Chinese Prompt Mode", info="Click here to enable Chinese Prompting（点此触发中文提示词输入）")
-
-                image_box = gr.Image(label="Input Image", height=350)
-                gen_btn = gr.Button(value="Generate")
-        with gr.Row(equal_height=True):
-            image1 = gr.Image(label="Result 1")
-            image2 = gr.Image(label="Result 2")
-            image3 = gr.Image(label="Result 3")
-            image4 = gr.Image(label="Result 4")
+import os
 
-        gr.on(triggers=[prompt_box.submit, gen_btn.click],fn=mult_thread_lang_class, inputs=[prompt_box, neg_prompt_box, chinese_check], outputs=[chinese_check], show_progress=False)
-        gr.on(triggers=[prompt_box.submit, gen_btn.click],fn=mult_thread_scribble, inputs=[prompt_box, neg_prompt_box, image_box], outputs=[image1, image2, image3, image4])
 
+HF_TOKEN = os.environ.get("HUGGING_FACE_HUB_TOKEN")
 
-        # gen_btn.click(mult_thread, [prompt_box, image_box, chinese_check], [image1, image2, image3, image4, chinese_check])
-iface.dependencies[0]["show_progress"] = "hidden"
-iface.launch(debug=True, share=True)
+gr.load("shellypeng/Anime-AI-Pack", src="spaces", hf_token="HUGGING_FACE_HUB_TOKEN").launch(debug=True, share=True)