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Running
on
Zero
Running
on
Zero
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 |