tori29umai's picture
app.py
6e57b9c
raw
history blame
No virus
3.56 kB
import os
import requests
from tqdm import tqdm
import shutil
from PIL import Image, ImageOps
import numpy as np
import cv2
def load_cn_model(model_dir):
folder = model_dir
file_name = 'diffusion_pytorch_model.safetensors'
url = " https://huggingface.co/2vXpSwA7/iroiro-lora/resolve/main/test_controlnet2/CN-anytest_v3-50000_fp16.safetensors"
file_path = os.path.join(folder, file_name)
if not os.path.exists(file_path):
response = requests.get(url, allow_redirects=True)
if response.status_code == 200:
with open(file_path, 'wb') as f:
f.write(response.content)
print(f'Downloaded {file_name}')
else:
print(f'Failed to download {file_name}')
else:
print(f'{file_name} already exists.')
def load_cn_config(model_dir):
folder = model_dir
file_name = 'config.json'
file_path = os.path.join(folder, file_name)
if not os.path.exists(file_path):
config_path = os.path.join(os.getcwd(), file_name)
shutil.copy(config_path, file_path)
def load_tagger_model(model_dir):
model_id = 'SmilingWolf/wd-swinv2-tagger-v3'
files = [
'config.json', 'model.onnx', 'selected_tags.csv', 'sw_jax_cv_config.json'
]
if not os.path.exists(model_dir):
os.makedirs(model_dir)
for file in files:
file_path = os.path.join(model_dir, file)
if not os.path.exists(file_path):
url = f'https://huggingface.co/{model_id}/resolve/main/{file}'
response = requests.get(url, allow_redirects=True)
if response.status_code == 200:
with open(file_path, 'wb') as f:
f.write(response.content)
print(f'Downloaded {file}')
else:
print(f'Failed to download {file}')
else:
print(f'{file} already exists.')
def load_lora_model(model_dir):
file_name = 'sdxl_BW_bold_Line.safetensors'
file_path = os.path.join(model_dir, file_name)
if not os.path.exists(file_path):
url = "https://huggingface.co/tori29umai/lineart/resolve/main/sdxl_BW_bold_Line.safetensors"
response = requests.get(url, allow_redirects=True)
if response.status_code == 200:
with open(file_path, 'wb') as f:
f.write(response.content)
print(f'Downloaded {file_name}')
else:
print(f'Failed to download {file_name}')
else:
print(f'{file_name} already exists.')
def resize_image_aspect_ratio(image):
# 元の画像サイズを取得
original_width, original_height = image.size
# アスペクト比を計算
aspect_ratio = original_width / original_height
# 標準のアスペクト比サイズを定義
sizes = {
1: (1024, 1024), # 正方形
4/3: (1152, 896), # 横長画像
3/2: (1216, 832),
16/9: (1344, 768),
21/9: (1568, 672),
3/1: (1728, 576),
1/4: (512, 2048), # 縦長画像
1/3: (576, 1728),
9/16: (768, 1344),
2/3: (832, 1216),
3/4: (896, 1152)
}
# 最も近いアスペクト比を見つける
closest_aspect_ratio = min(sizes.keys(), key=lambda x: abs(x - aspect_ratio))
target_width, target_height = sizes[closest_aspect_ratio]
# リサイズ処理
resized_image = image.resize((target_width, target_height), Image.LANCZOS)
return resized_image
def base_generation(size, color):
canvas = Image.new("RGBA", size, color)
return canvas