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Duplicate from souljoy/Pokemon-Stable-Diffusion-Chinese

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Co-authored-by: 小爷毛毛-卓寿杰 <[email protected]>

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  1. .gitattributes +34 -0
  2. README.md +14 -0
  3. app.py +54 -0
  4. requirements.txt +6 -0
.gitattributes ADDED
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README.md ADDED
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+ ---
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+ title: Taiyi Stable Diffusion Chinese
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+ emoji: 🤯
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+ colorFrom: red
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+ colorTo: red
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+ sdk: gradio
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+ sdk_version: 3.10.0
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+ app_file: app.py
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+ pinned: false
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+ license: creativeml-openrail-m
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+ duplicated_from: souljoy/Pokemon-Stable-Diffusion-Chinese
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+ ---
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+
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+ Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
app.py ADDED
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+ import gradio as gr
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+ from PIL import Image
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+ import torch
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+
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+ from diffusers import (
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+ StableDiffusionPipeline,
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+ StableDiffusionImg2ImgPipeline,
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+ )
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+
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+ device = "cuda" if torch.cuda.is_available() else "cpu"
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+ model_id = "IDEA-CCNL/Taiyi-Stable-Diffusion-1B-Anime-Chinese-v0.1"
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+
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+ pipe_text2img = StableDiffusionPipeline.from_pretrained(model_id)
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+ model_path = "souljoy/sd-pokemon-model-lora-zh"
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+ pipe_text2img.unet.load_attn_procs(model_path)
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+ pipe_text2img.to(device)
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+ pipe_text2img.safety_checker = lambda images, clip_input: (images, False)
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+ pipe_img2img = StableDiffusionImg2ImgPipeline(**pipe_text2img.components).to(device)
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+
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+
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+
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+ def infer_text2img(prompt, guide, steps, width, height, image_in, strength):
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+ if image_in is not None:
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+ init_image = image_in.convert("RGB").resize((width, height))
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+ output = pipe_img2img(prompt, image=init_image, strength=strength, width=width, height=height, guidance_scale=guide, num_inference_steps=steps)
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+ else:
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+ output = pipe_text2img(prompt, width=width, height=height, guidance_scale=guide, num_inference_steps=steps)
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+ image = output.images[0]
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+ return image
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+
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+
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+ with gr.Blocks() as demo:
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+ examples = [
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+ ["粉色的蝴蝶,小精灵,卡通"],
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+ ["可爱的狗,小精灵,卡通"],
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+ ["漂亮的猫,小精灵,卡通"],
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+ ]
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+ with gr.Row():
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+ with gr.Column(scale=1, ):
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+ image_out = gr.Image(label = '输出(output)')
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+ with gr.Column(scale=1, ):
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+ image_in = gr.Image(source='upload', elem_id="image_upload", type="pil", label="参考图(非必须)(ref)")
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+ prompt = gr.Textbox(label = '提示词(prompt)')
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+ submit_btn = gr.Button("生成图像(Generate)")
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+ with gr.Row(scale=0.5 ):
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+ guide = gr.Slider(2, 15, value = 7, step = 0.1, label = '文本引导强度(guidance scale)')
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+ steps = gr.Slider(10, 30, value = 20, step = 1, label = '迭代次数(inference steps)')
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+ width = gr.Slider(384, 640, value = 512, step = 64, label = '宽度(width)')
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+ height = gr.Slider(384, 640, value = 512, step = 64, label = '高度(height)')
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+ strength = gr.Slider(0, 1.0, value = 0.8, step = 0.02, label = '参考图改变程度(strength)')
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+ ex = gr.Examples(examples, fn=infer_text2img, inputs=[prompt, guide, steps, width, height], outputs=image_out)
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+
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+ submit_btn.click(fn = infer_text2img, inputs = [prompt, guide, steps, width, height, image_in, strength], outputs = image_out)
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+ demo.queue(concurrency_count=1, max_size=8).launch()
requirements.txt ADDED
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+ --extra-index-url https://download.pytorch.org/whl/cu113
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+ torch
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+ torchvision
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+ git+https://github.com/huggingface/diffusers.git
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+ transformers
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+ accelerate