multimodalart's picture
Create app.py
25345fc verified
raw
history blame
6.98 kB
import os
from huggingface_hub import snapshot_download
import spaces
os.makedirs("/home/user/app/ckpts", exist_ok=True)
snapshot_download(repo_id="Tencent-Hunyuan/HunyuanDiT", local_dir="/home/user/app/ckpts")
import gradio as gr
import pandas as pd
from pathlib import Path
from PIL import Image
import sys
#sys.path.insert(0, str(Path(__file__).parent.parent))
from hydit.constants import SAMPLER_FACTORY
from sample_t2i import inferencer
ROOT = Path(__file__).parent.parent
SAMPLERS = list(SAMPLER_FACTORY.keys())
SIZES = {
"square": (1024, 1024),
"landscape": (768, 1280),
"portrait": (1280, 768),
}
def get_strings(lang):
lang_file = Path(f"app/lang/{lang}.csv")
strings = pd.read_csv(lang_file, header=0)
strings = strings.set_index("key")['value'].to_dict()
return strings
args, gen, enhancer = inferencer()
strings = get_strings("en")
@spaces.GPU
def infer(
prompt,
negative_prompt,
seed,
cfg_scale,
infer_steps,
oriW, oriH,
sampler,
size,
enhance,
progress=gr.Progress(track_tqdm=True)
):
if enhance and enhancer is not None:
success, enhanced_prompt = enhancer(prompt)
if not success:
fail_image = Image.open(ROOT / 'app/fail.png')
return fail_image
else:
enhanced_prompt = None
height, width = SIZES[size]
results = gen.predict(prompt,
height=height,
width=width,
seed=seed,
enhanced_prompt=enhanced_prompt,
negative_prompt=negative_prompt,
infer_steps=infer_steps,
guidance_scale=cfg_scale,
batch_size=1,
src_size_cond=(oriW, oriH),
sampler=sampler,
)
image = results['images'][0]
return image
def ui():
block = gr.Blocks()
description = f"""
# {strings['title']}
## {strings['desc']}
"""
with block:
with gr.Row():
gr.Markdown(description)
with gr.Row():
with gr.Column():
with gr.Row():
size = gr.Radio(
label=strings['size'], choices=[
(strings['square'], 'square'),
(strings['landscape'], 'landscape'),
(strings['portrait'], 'portrait'),
],
value="square"
)
prompt = gr.Textbox(label=strings['prompt'], value=strings['default prompt'], lines=3)
with gr.Row():
infer_steps = gr.Slider(
label=strings['infer steps'], minimum=1, maximum=200, value=50, step=1,
)
seed = gr.Number(
label=strings['seed'], minimum=-1, maximum=1_000_000_000, value=1, step=1, precision=0,
)
enhance = gr.Checkbox(
label=strings['enhance'], value=enhancer is not None, interactive=True,
)
with gr.Accordion(
strings['accordion'], open=False
):
with gr.Row():
negative_prompt = gr.Textbox(label=strings['negative_prompt'],
value=gen.default_negative_prompt,
lines=2,
)
with gr.Row():
sampler = gr.Dropdown(SAMPLERS, label=strings['sampler'], value="ddpm")
cfg_scale = gr.Slider(
label=strings['cfg'], minimum=1.0, maximum=16.0, value=6.0, step=1
)
oriW = gr.Number(
label=strings['width cond'], minimum=1024, maximum=4096, value=1024, step=64, precision=0,
min_width=80,
)
oriH = gr.Number(
label=strings['height cond'], minimum=1024, maximum=4096, value=1024, step=64, precision=0,
min_width=80,
)
with gr.Row():
advanced_button = gr.Button(strings['run'])
with gr.Column():
#default_img = Image.open(ROOT / 'app/default.png')
output_img = gr.Image(
label=strings['generated image'],
interactive=False,
format='png',
#value=default_img,
)
advanced_button.click(
fn=infer,
inputs=[
prompt, negative_prompt, seed, cfg_scale, infer_steps,
oriW, oriH, sampler, size, enhance,
],
outputs=output_img,
)
with gr.Row():
gr.Examples([
['一只小猫'],
['现实主义风格,画面主要描述一个巴洛克风格的花瓶,带有金色的装饰边框,花瓶上盛开着各种色彩鲜艳的花,白色背景'],
['一只聪明的狐狸走在阔叶树林里, 旁边是一条小溪, 细节真实, 摄影'],
['飞流直下三千尺,疑是银河落九天'],
['一只长靴猫手持亮银色的宝剑,身着铠甲,眼神坚毅,站在一堆金币上,背景是暗色调的洞穴,图像上有金币的光影点缀。'],
['麻婆豆腐'],
['苏州园林'],
['一颗新鲜的草莓特写,红色的外表,表面布满许多种子,背景是淡绿色的叶子'],
['请画出“忽如一夜春风来 千树万树梨花开”'],
['请将“杞人忧天”的样子画出来'],
['枯藤老树昏鸦,小桥流水人家'],
['湖水清澈,天空湛蓝,阳光灿烂。一只优雅的白天鹅在湖边游泳。它周围有几只小鸭子,看起来非常可爱,整个画面给人一种宁静祥和的感觉。'],
['一朵鲜艳的红色玫瑰花,花瓣撒有一些水珠,晶莹剔透,特写镜头'],
['臭豆腐'],
['九寨沟'],
['俗语“鲤鱼跃龙门”'],
['风格是写实,画面主要描述一个亚洲戏曲艺术家正在表演,她穿着华丽的戏服,脸上戴着精致的面具,身姿优雅,背景是古色古香的舞台,镜头是近景'],
],
[prompt],
label=strings['examples']
)
return block
if __name__ == "__main__":
interface = ui()
interface.launch()