Upload app.py

app.py

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+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)
+
+
+