fix: 适配 ubuntu 路径并增强换发色/训练流程稳定性

将配置与训练脚本从 /home/xsl 切到本机 /home/ubuntu；换发色在 webui 增强失败或缺色板时降级返回，训练结束后自动重启 hair 服务再回调。

Co-authored-by: Cursor <cursoragent@cursor.com>

change_hair-hair.service

@@ -0,0 +1,19 @@
+[Unit]
+Description=change_hair hair_service_sd swapHair (8801)
+After=network-online.target change_hair-webui.service change_hair-photo.service
+Wants=change_hair-webui.service change_hair-photo.service
+
+[Service]
+Type=simple
+User=ubuntu
+WorkingDirectory=/home/ubuntu/change_hair/project/hair_service_sd
+Environment=CRYPTOGRAPHY_OPENSSL_NO_LEGACY=1
+Environment=CUDA_VISIBLE_DEVICES=0
+Environment=APP_WORKER_ID=1
+ExecStart=/home/ubuntu/miniconda3/envs/my_hair/bin/python run_copy_cost_colorb64.py
+Restart=on-failure
+RestartSec=10
+TimeoutStartSec=300
+
+[Install]
+WantedBy=multi-user.target

change_hair-photo.service

@@ -0,0 +1,17 @@
+[Unit]
+Description=change_hair photo_service LoRA scheduler (32678)
+After=network-online.target
+Wants=network-online.target
+
+[Service]
+Type=simple
+User=ubuntu
+WorkingDirectory=/home/ubuntu/change_hair/project/photo_service
+Environment=CUDA_VISIBLE_DEVICES=0
+Environment=APP_WORKER_ID=1
+ExecStart=/home/ubuntu/miniconda3/envs/py310/bin/python -u lora_train_service_1.py
+Restart=on-failure
+RestartSec=10
+
+[Install]
+WantedBy=multi-user.target

change_hair-webui.service

@@ -0,0 +1,20 @@
+[Unit]
+Description=change_hair SD WebUI (57860)
+After=network-online.target
+Wants=network-online.target
+
+[Service]
+Type=simple
+User=ubuntu
+WorkingDirectory=/home/ubuntu/change_hair/project/onediff/stable-diffusion-webui
+Environment=CRYPTOGRAPHY_OPENSSL_NO_LEGACY=1
+Environment=CUDA_VISIBLE_DEVICES=0
+Environment=HF_HUB_OFFLINE=1
+Environment=TRANSFORMERS_OFFLINE=1
+ExecStart=/home/ubuntu/miniconda3/envs/sdwebui/bin/python webui.py --api --listen --xformers --port 57860
+Restart=on-failure
+RestartSec=10
+TimeoutStartSec=600
+
+[Install]
+WantedBy=multi-user.target

project/hair_service_sd/change_color.py

@@ -70,7 +70,11 @@ def process_infer(user_img_path, target_color, color_dir, dst_path, ratio=1.0):
     # 通过webui对照片进行增强
     s4 = time.time()
     # cv2.imwrite('/home/student/Downloads/12121.jpg',crop_img)
-    enhanced_img = enhance_hair.webui_img2img(crop_img, crop_mask, prompt=prompt)
+    try:
+        enhanced_img = enhance_hair.webui_img2img(crop_img, crop_mask, prompt=prompt)
+    except Exception as e:
+        print(f"[process_infer] webui enhance skipped: {e}")
+        enhanced_img = crop_img
     print("----------------------------webui_img2img", time.time() - s4)
 
     # 写回原图

project/hair_service_sd/config/configure.ini

@@ -1,21 +1,21 @@
 [default]
 modelDir = weights
-hairstyleDir = /home/xsl/change_hair/project/data/ref_hairstyle
+hairstyleDir = /home/ubuntu/change_hair/project/data/ref_hairstyle
-haircolorDir= /home/xsl/change_hair/project/data/ref_haircolor
+haircolorDir= /home/ubuntu/change_hair/project/data/ref_haircolor
-userDir=/home/xsl/change_hair/project/data/userImage
+userDir=/home/ubuntu/change_hair/project/data/userImage
-tmp_dir=/home/xsl/change_hair/project/data/tmp
+tmp_dir=/home/ubuntu/change_hair/project/data/tmp
-res_dir=/home/xsl/change_hair/project/data/res_dir
+res_dir=/home/ubuntu/change_hair/project/data/res_dir
-userInfo_dir=/home/xsl/change_hair/project/data/user_info
+userInfo_dir=/home/ubuntu/change_hair/project/data/user_info
 baseColor_ID=HDR10_443322
 Port = 11023
-refer_dir = /home/xsl/change_hair/project/data/ref_online
+refer_dir = /home/ubuntu/change_hair/project/data/ref_online
-ref_user_dir = /home/xsl/change_hair/project/data/ref_user_imgs
+ref_user_dir = /home/ubuntu/change_hair/project/data/ref_user_imgs
-train_dir = /home/xsl/change_hair/data/train_material
+train_dir = /home/ubuntu/change_hair/data/train_material
-refImgDir=/home/xsl/change_hair/project/data/refImage
+refImgDir=/home/ubuntu/change_hair/project/data/refImage
-hair_template_material_dir=/home/xsl/change_hair/project/data/hair_template_material
+hair_template_material_dir=/home/ubuntu/change_hair/project/data/hair_template_material
-ref_color=/home/xsl/change_hair/project/data/ref_color
+ref_color=/home/ubuntu/change_hair/project/data/ref_color
-ref_color_img=/home/xsl/change_hair/project/data/ref_color_imgs
+ref_color_img=/home/ubuntu/change_hair/project/data/ref_color_imgs
-upload_train_dir=/home/xsl/change_hair/project/data/upload_train_imgs
+upload_train_dir=/home/ubuntu/change_hair/project/data/upload_train_imgs
 ;version=local
 version=online
 
@@ -23,7 +23,7 @@ version=online
 strength=1
 
 [logger]
-logpath = /home/xsl/change_hair/project/logs
+logpath = /home/ubuntu/change_hair/project/logs
 level=INFO
 
 [timelogger]
@@ -32,4 +32,3 @@ name=watch-time
 [errorlogger]
 level=ERROR
 name=w-error
-

project/hair_service_sd/hairstyle_model_infer.py

@@ -72,6 +72,8 @@ class HairStyle_Model_Infer(object):
         # haircolor_dir = '/home/data/hair/data/ref_color/3628746832766'
         face_base, hair_matting, status = self.infer_haircolor_new(user_rgb_8uc3_orisize, haircolor_dir,target_hair_color,
                                                                return_matting=True)
+        if status != 0:
+            return user_rgb_8uc3_orisize, None, status
         user_rgb_8uc3_orisize = face_base
         # 构建一个色板
         r, g, b = target_hair_color
@@ -1016,7 +1018,7 @@ class HairStyle_Model_Infer(object):
     def infer_haircolor_new(self, user_rgb_8uc3_orisize, haircolor_dir, target_hair_color, return_matting=False):
         landmarks_origin_img_1k= self.get_landmark.forward(user_rgb_8uc3_orisize)
         if landmarks_origin_img_1k is None:
-            return None, 10001
+            return None, None, 10001
         need_process = (target_hair_color[0] * 0.299 + target_hair_color[1] * 0.587 + target_hair_color[2] * 0.114) > 150
         _, user_matting_8uc1_bald_orisize = self.process_data_infer.generator_matte.matte_inference(user_rgb_8uc3_orisize,
                                                                                               landmarks_origin_img_1k)
@@ -1036,10 +1038,13 @@ class HairStyle_Model_Infer(object):
         need_process=True
         if need_process:
             haircolor_dir_tmp = os.path.join(config.get('default', "haircolorDir"), config.get('default', "baseColor_ID"))
-            face_base, status1 = self.infer_haircolor_tj(user_rgb_8uc3_orisize, haircolor_dir_tmp)
+            if os.path.exists(haircolor_dir_tmp):
-            # cv2.imwrite('/home/student/Desktop/tmp_color/need/face_base.png', face_base)
+                face_base, status1 = self.infer_haircolor_tj(user_rgb_8uc3_orisize, haircolor_dir_tmp)
-            if status1 == 0:
+                # cv2.imwrite('/home/student/Desktop/tmp_color/need/face_base.png', face_base)
-                return face_base, user_matting_8uc1_bald_orisize, 0
+                if status1 == 0:
+                    return face_base, user_matting_8uc1_bald_orisize, 0
+                else:
+                    need_process = False
             else:
                 need_process = False
         if not need_process:

project/hair_service_sd/run_copy_cost_colorb64.py

@@ -255,7 +255,8 @@ def change_hair_colorv3():
                 jsonify({'msg': '算法解析错误', 'result': '', 'umd': '', 'state': -1}), 400)
 
     except Exception as e:
-        print(e)
+        print(f"[hairColor ERROR] {e}")
+        traceback.print_exc()
         return make_response(
             jsonify({'msg': '算法解析错误', 'result': '', 'umd': '', 'state': -1}), 400)
 

project/hair_service_sd/utils/enhance_hair.py

@@ -43,6 +43,9 @@ def webui_img2img(img, mask, prompt='', denoising_strength=0.35):
         }
     response = requests.post(url=url, json=request_dict)
     ret_json = response.json()
+    if 'images' not in ret_json:
+        print(f"[webui_img2img ERROR] {ret_json}")
+        raise Exception(f"webui error: {ret_json.get('error', 'unknown')}")
     result = ret_json['images'][0]
     img = cv2.imdecode(np.frombuffer(base64.b64decode(result.split(",", 1)[0]), np.uint8), cv2.IMREAD_COLOR)
     return img

project/photo_service/lora_train_service_1.py

@@ -37,8 +37,8 @@ if version == "local":
     callback_url = 'http://service.aicloud.fit:7395/api/hair/trainCallBack'
 else:
     current_url = 'http://0.0.0.0:7393/'
-    kohya_ss_home_dir = '/home/xsl/change_hair/project/kohya_ss_home'
+    kohya_ss_home_dir = '/home/ubuntu/change_hair/project/kohya_ss_home'
-    webui_lora_dir = '/home/xsl/change_hair/project/onediff/stable-diffusion-webui/models/Lora'
+    webui_lora_dir = '/home/ubuntu/change_hair/project/onediff/stable-diffusion-webui/models/Lora'
     inference_use_onediff = False
     callback_url = 'http://0.0.0.0:8801/api/hair/trainCallBack'
 base_webui_port = '57860'
@@ -307,13 +307,13 @@ def train_thread(sq, gpu_id):
             #   3. GPU 固定 device=0(单卡)
             #   4. 去掉 tokenizer_cache_dir(改用 HF 本地缓存 + 离线模式)
             #   5. 设置 HF_HUB_OFFLINE 避免联网检查
-            kohya_python = '/home/xsl/miniconda3/envs/kohya/bin/python'
+            kohya_python = '/home/ubuntu/miniconda3/envs/my_hair/bin/python'
             kohya_workdir = os.path.join(kohya_ss_home_dir, 'kohya_ss')
-            base_model = '/home/xsl/change_hair/project/onediff/stable-diffusion-webui/models/Stable-diffusion/v1-5-pruned-emaonly.safetensors'
+            base_model = '/home/ubuntu/change_hair/project/onediff/stable-diffusion-webui/models/Stable-diffusion/v1-5-pruned-emaonly.safetensors'
             cmd_train = (
                 f'cd {kohya_workdir} && '
                 f'HF_HUB_OFFLINE=1 TRANSFORMERS_OFFLINE=1 CUDA_VISIBLE_DEVICES={device_id} '
-                f'/home/xsl/miniconda3/envs/kohya/bin/accelerate launch --num_cpu_threads_per_process=2 "./train_network.py" --enable_bucket '
+                f'/home/ubuntu/miniconda3/envs/my_hair/bin/accelerate launch --num_cpu_threads_per_process=2 "./train_network.py" --enable_bucket '
                 f'--min_bucket_reso=256 --max_bucket_reso=2048 --pretrained_model_name_or_path="{base_model}" '
                 f'--train_data_dir={images_dir} --resolution="2000,2000" '
                 f'--output_dir={model_dir} '

train_hairstyle_full.py

@@ -158,6 +158,10 @@ def step3_wait_and_callback(hair_id, template_img):
     else:
         print("  ✗ 训练超时"); return False
     time.sleep(5)  # 等训练进程写完
+    # 训练时停掉了 hair 服务，回调前需要重启
+    print("  重启 change_hair-hair 服务...")
+    os.system("sudo systemctl restart change_hair-hair")
+    time.sleep(20)
     # 触发回调生成ref材质
     print("  触发回调生成ref材质...")
     r = req.post(HAIR_CALLBACK, json={"task_id":f"train_{hair_id}","hair_id":hair_id,