初始化换发型项目:3个微服务代码 + 部署脚本
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。
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# --------------------------------------------------------
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# Fast R-CNN
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# Copyright (c) 2015 Microsoft
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# Licensed under The MIT License [see LICENSE for details]
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# Written by Ross Girshick
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# --------------------------------------------------------
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import numpy as np
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def py_cpu_nms(dets, thresh, min_face_size = 50):
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"""Pure Python NMS baseline."""
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x1 = dets[:, 0]
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y1 = dets[:, 1]
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x2 = dets[:, 2]
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y2 = dets[:, 3]
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scores = dets[:, 4]
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areas = (x2 - x1 + 1) * (y2 - y1 + 1)
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order = scores.argsort()[::-1]
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keep = []
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while order.size > 0:
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i = order[0]
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keep.append(i)
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xx1 = np.maximum(x1[i], x1[order[1:]])
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yy1 = np.maximum(y1[i], y1[order[1:]])
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xx2 = np.minimum(x2[i], x2[order[1:]])
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yy2 = np.minimum(y2[i], y2[order[1:]])
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w = np.maximum(0.0, xx2 - xx1 + 1)
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h = np.maximum(0.0, yy2 - yy1 + 1)
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inter = w * h
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ovr = inter / (areas[i] + areas[order[1:]] - inter)
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inds = np.where(ovr <= thresh)[0]
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order = order[inds + 1]
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#filter_small_faces
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filter_list = []
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for idx in keep:
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w = np.abs(dets[idx, 2] - dets[idx, 0])
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h = np.abs(dets[idx, 3] - dets[idx, 1])
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if max(w, h) < min_face_size: continue
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filter_list.append(idx)
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return filter_list
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