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hsuwill000
commited on
Update app.py
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app.py
CHANGED
@@ -1,44 +1,80 @@
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import gradio as gr
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import torch
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from
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model_id = "hsuwill000/Fluently-v4-LCM-openvino"
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batch_size = -1
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pipe = OVStableDiffusionPipeline.from_pretrained(
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print(pipe.scheduler.compatibles)
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pipe.reshape(batch_size=-1, height=HIGH, width=WIDTH, num_images_per_prompt=1)
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pipe.compile()
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prompt
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negative_prompt
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def infer(prompt, negative_prompt, num_inference_steps):
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image = pipe(
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prompt=prompt,
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negative_prompt=negative_prompt,
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width=WIDTH,
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height=HIGH,
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guidance_scale=1.0,
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num_inference_steps=
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num_images_per_prompt=1,
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).images[0]
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return image
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examples = [
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"(Digital art, highres, best quality, 8K, masterpiece, anime screencap, perfect eyes:1.4, ultra detailed:1.5),1girl,flat chest,short messy pink hair,blue eyes,tall,thick thighs,light blue hoodie,collar,light blue shirt,black sport shorts,bulge,black thigh highs,femboy,okoto no ko,smiling,blushing,looking at viewer,inside,livingroom,sitting on couch,nighttime,dark,hand_to_mouth,",
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"1girl, silver hair, symbol-shaped pupils, yellow eyes, smiling, light particles, light rays, wallpaper, star guardian, serious face, red inner hair, power aura, grandmaster1, golden and white clothes",
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"((colofrul:1.7)),((best quality)), ((masterpiece)), ((ultra-detailed)), (illustration), (detailed light), (an extremely delicate and beautiful),incredibly_absurdres,(glowing),(1girl:1.7),solo,a beautiful girl,(((cowboy shot))),standding,((Hosiery)),((beautiful off-shoulder lace-trimmed layered strapless dress+white stocking):1.25),((Belts)),(leg loops),((Hosiery)),((flower headdress)),((long white hair)),(((beautiful eyes))),BREAK,((english text)),(flower:1.35),(garden),(((border:1.75))),",
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]
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css
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#col-container {
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margin: 0 auto;
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max-width: 520px;
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}
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"""
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power_device = "CPU"
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with gr.Blocks(css=css) as demo:
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@@ -73,28 +110,19 @@ with gr.Blocks(css=css) as demo:
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)
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run_button = gr.Button("Run", scale=0)
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# Slider for num_inference_steps
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num_inference_steps_slider = gr.Slider(
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minimum=1,
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maximum=30,
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step=1,
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value=4,
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label="Number of Inference Steps"
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)
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result = gr.Image(label="Result", show_label=False)
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gr.Examples(
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examples=examples,
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fn=infer,
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inputs=[prompt
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outputs=[result]
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)
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run_button.click(
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fn=infer,
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inputs=[prompt
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outputs=[result]
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)
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demo.queue().launch()
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幫我移除不需要的註解
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import gradio as gr
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import numpy as np
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import random
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from diffusers import DiffusionPipeline
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from optimum.intel.openvino.modeling_diffusion import OVModelVaeDecoder, OVBaseModel, OVStableDiffusionPipeline
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import torch
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from huggingface_hub import snapshot_download
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import openvino.runtime as ov
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from typing import Optional, Dict
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#from diffusers import EulerAncestralDiscreteScheduler, LCMScheduler
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#LCMScheduler 產生垃圾
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#EulerDiscreteScheduler 尚可
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#EulerAncestralDiscreteScheduler 很不錯chatgpt推薦
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model_id = "hsuwill000/Fluently-v4-LCM-openvino"
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#model_id = "spamsoms/LCM-anything-v5-openvino2"
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#adapter_id = "latent-consistency/lcm-lora-sdv1-5"
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#512*512 好 太大會變形
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HIGH=1024
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WIDTH=512
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batch_size = -1
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pipe = OVStableDiffusionPipeline.from_pretrained(
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model_id,
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compile = False,
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ov_config = {"CACHE_DIR":""},
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torch_dtype=torch.int8, #快
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#torch_dtype=torch.bfloat16, #中
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#variant="fp16",
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#torch_dtype=torch.IntTensor, #慢,
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safety_checker=None,
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use_safetensors=False,
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)
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print(pipe.scheduler.compatibles)
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#pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
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#pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
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#pipe.load_lora_weights(adapter_id)
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#pipe.fuse_lora()
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pipe.reshape( batch_size=-1, height=HIGH, width=WIDTH, num_images_per_prompt=1)
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#pipe.load_textual_inversion("./badhandv4.pt", "badhandv4")
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#pipe.load_textual_inversion("./Konpeto.pt", "Konpeto")
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#<shigure-ui-style>
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#pipe.load_textual_inversion("sd-concepts-library/shigure-ui-style")
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#pipe.load_textual_inversion("sd-concepts-library/ruan-jia")
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#pipe.load_textual_inversion("sd-concepts-library/agm-style-nao")
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pipe.compile()
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prompt=""
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negative_prompt="EasyNegative, "
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def infer(prompt,negative_prompt):
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image = pipe(
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prompt = prompt,
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negative_prompt = negative_prompt,
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width = WIDTH,
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height = HIGH,
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guidance_scale=1.0,
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num_inference_steps=8,
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num_images_per_prompt=1,
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).images[0]
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return image
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examples = [
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"(Digital art, highres, best quality, 8K, masterpiece, anime screencap, perfect eyes:1.4, ultra detailed:1.5),1girl,flat chest,short messy pink hair,blue eyes,tall,thick thighs,light blue hoodie,collar,light blue shirt,black sport shorts,bulge,black thigh highs,femboy,okoto no ko,smiling,blushing,looking at viewer,inside,livingroom,sitting on couch,nighttime,dark,hand_to_mouth,",
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"1girl, silver hair, symbol-shaped pupils, yellow eyes, smiling, light particles, light rays, wallpaper, star guardian, serious face, red inner hair, power aura, grandmaster1, golden and white clothes",
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"((colofrul:1.7)),((best quality)), ((masterpiece)), ((ultra-detailed)), (illustration), (detailed light), (an extremely delicate and beautiful),incredibly_absurdres,(glowing),(1girl:1.7),solo,a beautiful girl,(((cowboy shot))),standding,((Hosiery)),((beautiful off-shoulder lace-trimmed layered strapless dress+white stocking):1.25),((Belts)),(leg loops),((Hosiery)),((flower headdress)),((long white hair)),(((beautiful eyes))),BREAK,((english text)),(flower:1.35),(garden),(((border:1.75))),",
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]
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css="""
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#col-container {
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margin: 0 auto;
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max-width: 520px;
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}
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"""
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power_device = "CPU"
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with gr.Blocks(css=css) as demo:
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)
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run_button = gr.Button("Run", scale=0)
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result = gr.Image(label="Result", show_label=False)
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gr.Examples(
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examples = examples,
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fn = infer,
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inputs = [prompt],
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outputs = [result]
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)
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run_button.click(
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fn = infer,
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inputs = [prompt],
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outputs = [result]
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)
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demo.queue().launch()
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