colomi
0eb61f3e60
包含： - hair_service_sd: 换发型/换发色算法服务 (端口 8801) - photo_service: LoRA 训练调度服务 (端口 32678) - stable-diffusion-webui: SD WebUI 推理服务 (端口 57860) - kohya_ss_home: 训练环境代码 - meidaojia: 监控测试脚本 - setup.sh: 一键部署脚本 (conda环境恢复 + 配置生成 + 完整性检查) - start_all_services.sh: 启动3个服务 - configure.ini.template: 路径模板化 (BASE_DIR自动推导) - conda_envs/py310.yml: py310 环境定义 大文件 (weights/, models/, data/, conda_envs/*.tar.gz 等) 通过 .gitignore 排除， 由网盘单独上传。
25 lines
922 B
Python
25 lines
922 B
Python
from seg.hairseg_single_model import Evaluator
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import os
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import cv2
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import numpy as np
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if __name__ == "__main__":
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data_path = "/home/liyang/project/matting/合格/origin"
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dst_path = "/home/liyang/project/matting/合格/origin_seg_res1102"
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if not os.path.exists(dst_path):
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os.mkdir(dst_path)
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seg_model = Evaluator(gpu_id=0, output_img_size=512, nclass=3)
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for imgs in os.listdir(data_path):
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if imgs.endswith(".txt"):
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continue
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img_path = os.path.join(data_path, imgs)
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img = cv2.imread(img_path)
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if img_path.endswith('.png'):
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kpts_1k = np.loadtxt(img_path.replace('.png', '_landmark1k.txt'))
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elif img_path.endswith('.jpg'):
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kpts_1k = np.loadtxt(img_path.replace('.jpg', '_landmark1k.txt'))
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output_img_size = 512
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mask = seg_model.eval(img, kpts_1k)
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cv2.imwrite(os.path.join(dst_path, imgs), mask)
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