初始化：换发型/换发色/训练发型服务

包含：
- hair_service_sd: 主服务（换发型/换发色/生发，端口8801）
- photo_service: LoRA调度+训练（端口32678）
- hair_grow_service: 调试测试页（端口8888，含4个测试页）
- 批量训练脚本（batch_train_hairstyles.py）
- 发际线mask自动识别（hairline_mask.py，4种方案）
- 手绘mask换发型（hair_swap_manual.py）
- 文档：README.md + LARGE_FILES.md + docs/

大文件（模型权重200G、训练数据123G）已排除，见 LARGE_FILES.md
OSS/COS密钥已脱敏为环境变量，原文件备份在本地

project/hair_service_sd/seg/test_single.py

@@ -0,0 +1,24 @@
+from seg.hairseg_single_model import Evaluator
+import os
+import cv2
+import numpy as np
+if __name__ == "__main__":
+
+    data_path = "/home/liyang/project/matting/合格/origin"
+    dst_path = "/home/liyang/project/matting/合格/origin_seg_res1102"
+    if not os.path.exists(dst_path):
+        os.mkdir(dst_path)
+    seg_model = Evaluator(gpu_id=0, output_img_size=512, nclass=3)
+    for imgs in os.listdir(data_path):
+        if imgs.endswith(".txt"):
+            continue
+
+        img_path = os.path.join(data_path, imgs)
+        img = cv2.imread(img_path)
+        if img_path.endswith('.png'):
+            kpts_1k = np.loadtxt(img_path.replace('.png', '_landmark1k.txt'))
+        elif img_path.endswith('.jpg'):
+            kpts_1k = np.loadtxt(img_path.replace('.jpg', '_landmark1k.txt'))
+        output_img_size = 512
+        mask = seg_model.eval(img, kpts_1k)
+        cv2.imwrite(os.path.join(dst_path, imgs), mask)