File size: 9,732 Bytes
9857f35 3a56c9c 4ad1c5e 534feb5 3a56c9c cd732b5 0ce6b41 902134a 534feb5 559ce8f 8ee38b9 1d0d081 9857f35 3a56c9c 9857f35 3a56c9c 8b76381 3a56c9c dbe1a2e 7859661 559ce8f f3670b6 42c0ba5 3a56c9c 9857f35 534feb5 0eaa47c 559ce8f f3670b6 7859661 f3670b6 559ce8f f3670b6 559ce8f 0eaa47c 559ce8f 9857f35 0eaa47c 9857f35 212d8b1 8e53416 a6fce5e 58d88ba a6fce5e 9061138 a6fce5e 9857f35 dd3f930 9857f35 a6fce5e 9857f35 a6fce5e 9857f35 a6fce5e 9857f35 cddff24 8ee38b9 7735836 559ce8f 0ce6b41 064dd5f 0ce6b41 064dd5f 0ce6b41 7859661 f3670b6 3d34613 9857f35 a6fce5e 9857f35 a6fce5e 9857f35 9061138 9857f35 89d112b 9857f35 881b727 1d0d081 9857f35 a6fce5e 9857f35 881b727 628a218 9857f35 a6fce5e 9857f35 204c1ca 9857f35 58d88ba 2fe06d5 ab3b95d 2fe06d5 a6fce5e f588de8 a6fce5e 9857f35 064dd5f a6fce5e f3670b6 9061138 9857f35 4aea187 9857f35 a6fce5e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 |
import gradio as gr
import numpy as np
import random
import torch
import spaces
import re
import os
from diffusers import (
DiffusionPipeline,
AutoencoderTiny,
)
from huggingface_hub import hf_hub_download
#from feifeilib.feifeichat import feifeichat
IS_ZERO_GPU = bool(os.getenv("SPACES_ZERO_GPU"))
IS_GPU_MODE = True if IS_ZERO_GPU else (True if torch.cuda.is_available() else False)
if IS_ZERO_GPU:
import subprocess
subprocess.run("rm -rf /data-nvme/zerogpu-offload/*", env={}, shell=True)
torch.set_float32_matmul_precision("high")
torch.backends.cuda.matmul.allow_tf32 = True
IS_COMPILE = False
import config
styles_name = [style["name"] for style in config.style_list]
MAX_SEED = np.iinfo(np.int32).max
MAX_IMAGE_SIZE = 2240
def feifeimodload():
dtype = torch.bfloat16
device = "cuda" if torch.cuda.is_available() else "cpu"
pipe = DiffusionPipeline.from_pretrained(
"aifeifei798/DarkIdol-flux-v1", torch_dtype=dtype
).to(device)
pipe.load_lora_weights(
hf_hub_download("aifeifei798/feifei-flux-lora-v1.1", "feifei-v1.1.safetensors"),
adapter_name="feifei",
)
pipe.load_lora_weights(
hf_hub_download("aifeifei798/sldr_flux_nsfw_v2-studio", "sldr_flux_nsfw_v2-studio.safetensors"),
adapter_name="sldr_flux_nsfw_v2",
)
pipe.load_lora_weights(
hf_hub_download(
"aifeifei798/big-boobs-clothed",
"big-boobs-clothed-v2.safetensors",
),
adapter_name="big-boobs-clothed-v2",
)
pipe.vae.enable_slicing()
pipe.vae.enable_tiling()
torch.cuda.empty_cache()
return pipe
pipe = feifeimodload()
if IS_ZERO_GPU:
os.environ["DIFFUSERS_ENABLE_HUB_KERNELS"] = "yes"
pipe.transformer.set_attention_backend("flash_hub")
if IS_COMPILE:
from optimization import optimize_pipeline_
optimize_pipeline_(pipe, "prompt")
def get_duration(prompt, styles_Radio, feife_select, bigboobs_select, seed, randomize_seed, width, height, num_inference_steps, guidancescale, num_feifei, nsfw_select, nsfw_slider, progress):
def_duration = 15.
def_steps = 4.
return int(def_duration * float(num_inference_steps) / def_steps)
@spaces.GPU(duration=get_duration)
def infer(prompt="", styles_Radio="(None)", feife_select = False, bigboobs_select = True, seed=42, randomize_seed=False, width=1024, height=1024, num_inference_steps=4, guidancescale=3.5, num_feifei=0.35, nsfw_select=False, nsfw_slider=1, progress=gr.Progress(track_tqdm=True)):
Duke86Syl_lora_name=[]
adapter_weights_num=[]
if feife_select:
Duke86Syl_lora_name.append("feifei")
adapter_weights_num.append(num_feifei)
if bigboobs_select:
Duke86Syl_lora_name.append("big-boobs-clothed-v2")
adapter_weights_num.append(0.45)
if nsfw_select:
Duke86Syl_lora_name.append("sldr_flux_nsfw_v2")
adapter_weights_num.append(nsfw_slider)
pipe.set_adapters(
Duke86Syl_lora_name,
adapter_weights=adapter_weights_num,
)
pipe.fuse_lora(
adapter_name=Duke86Syl_lora_name,
lora_scale=1.0,
)
#if feife_select:
# # Define the replacement string
# replacement = " feifei, A beautiful, 18 yo kpop idol, large-busted Japanese slim girl, with light makeup, gazing deeply into the camera, "
#
# # Perform the replacements with re.IGNORECASE
# prompt = re.sub(r"girl", replacement, prompt, flags=re.IGNORECASE)
# prompt = re.sub(r"young woman", replacement, prompt, flags=re.IGNORECASE)
# prompt = re.sub(r"woman", replacement, prompt, flags=re.IGNORECASE)
# prompt = re.sub(r"model", replacement, prompt, flags=re.IGNORECASE)
if styles_Radio:
style_name = styles_Radio
for style in config.style_list:
if style["name"] == style_name:
prompt = style["prompt"].replace("{prompt}", prompt)
if randomize_seed:
seed = random.randint(0, MAX_SEED)
generator = torch.Generator().manual_seed(seed)
image = pipe(
prompt = "flux, 8k, ",
prompt_2 = prompt,
width = width,
height = height,
num_inference_steps = num_inference_steps,
generator = generator,
guidance_scale=guidancescale
).images[0]
return image, seed
examples = [
"this photo is a girl",
"this photo is a girl in bikini",
"this photo is a cute girl in cute bikini",
"girl, sunrise",
"DarkIdol flux girl",
"a sexy girl,poses,look at camera,Slim figure, gigantic breasts,poses,natural,High-quality photography, creative composition, fashion foresight, a strong visual style, and an aura of luxury and sophistication collectively define the distinctive aesthetic of Vogue magazine.",
"real model slight smile girl in real life",
"real model smile girl in real life",
"real model girl in real life",
"A high-resolution photograph of girl in a serene, natural setting, with soft, warm lighting, and a minimalist aesthetic, showcasing a elegant fragrance bottle and the model's effortless, emotive expression, with impeccable styling, and a muted color palette, evoking a sense of understated luxury and refinement."
]
css="""
#col-container {
margin: 0 auto;
max-width: 520px;
}
"""
with gr.Blocks(css=css) as demo:
with gr.Column(elem_id="col-container"):
result = gr.Image(label="Result", show_label=False,height=500,format="png")
with gr.Row():
prompt = gr.Text(
label="Prompt",
show_label=False,
max_lines=12,
placeholder="Enter your prompt",
value="",
container=False,
)
run_button = gr.Button("Run")
with gr.Row():
styles_Radio = gr.Dropdown(
styles_name,
label="Styles",
multiselect=False,
value="(None)",
)
#feifei_chat_text1 = gr.Textbox(
# label="输入您的问题1:", show_label=False, container=False, lines=1, value="")
#feifei_chat_text2 = gr.Textbox(
# label="输入您的问题2:", show_label=False, container=False, lines=3, value="")
# 定义模型选择下拉框
#feifei_chat_Dropdown = gr.Dropdown(
# [
# "meta/llama-3.3-70b-instruct",
# "nvidia/llama-3.3-nemotron-super-49b-v1",
# "mistralai/Mistral-Nemo-Instruct-2411",
# ],
# value="mistralai/Mistral-Nemo-Instruct-2411",
# label="选择模型", show_label=False, container=False
#)
# 定义提交按钮
#feifei_chat_btn = gr.Button(value="Gen Prompt")
feife_select = gr.Checkbox(label="FeiFei Expansion", value=True)
bigboobs_select = gr.Checkbox(label="bigboobs", value=True)
nsfw_select = gr.Checkbox(label="NSFW")
nsfw_slider = gr.Slider(
label="NSFW",
minimum=0,
maximum=2,
step=0.05,
value=0.75,
)
with gr.Accordion("Advanced Settings", open=False):
seed = gr.Slider(
label="Seed",
minimum=0,
maximum=MAX_SEED,
step=1,
value=0,
)
randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
with gr.Row():
gr.Markdown(''' - 21:9 2240x1024
- 16:9 1856x1024
- 9:7 1344x1024 ''')
width = gr.Slider(
label="Width",
minimum=256,
maximum=MAX_IMAGE_SIZE,
step=64,
value=1024,
)
height = gr.Slider(
label="Height",
minimum=256,
maximum=MAX_IMAGE_SIZE,
step=64,
value=1856,
)
with gr.Row():
num_inference_steps = gr.Slider(
label="Number of inference steps",
minimum=1,
maximum=50,
step=1,
value=4,
)
with gr.Row():
guidancescale = gr.Slider(
label="Guidance scale",
minimum=0,
maximum=10,
step=0.1,
value=3.5,
)
with gr.Row():
num_feifei = gr.Slider(
label="FeiFei",
minimum=0,
maximum=2,
step=0.05,
value=0.35,
)
gr.Examples(
examples = examples,
fn = infer,
inputs = [prompt],
outputs = [result, seed],
cache_examples=False
)
run_button.click(
fn = infer,
inputs = [prompt, styles_Radio, feife_select, bigboobs_select, seed, randomize_seed, width, height, num_inference_steps, guidancescale, num_feifei, nsfw_select, nsfw_slider],
outputs = [result, seed]
)
#feifei_chat_btn.click(
# fn=feifeichat,
# inputs=[feifei_chat_text1, feifei_chat_text2, feifei_chat_Dropdown],
# outputs=prompt
#)
demo.launch() |