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fix: 适配 ubuntu 路径并增强换发色/训练流程稳定性

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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>
This commit is contained in:
xsl
2026-07-19 00:49:16 +08:00
co-authored by Cursor
parent fc66534a74
commit 0926c61bd0
7 changed files with 44 additions and 28 deletions
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project/hair_service_sd/change_color.py
+5 -1
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@@ -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
+15 -16
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@@ -1,21 +1,21 @@
[default]
modelDir = weights
hairstyleDir = /home/xsl/change_hair/project/data/ref_hairstyle
haircolorDir= /home/xsl/change_hair/project/data/ref_haircolor
userDir=/home/xsl/change_hair/project/data/userImage
tmp_dir=/home/xsl/change_hair/project/data/tmp
res_dir=/home/xsl/change_hair/project/data/res_dir
userInfo_dir=/home/xsl/change_hair/project/data/user_info
hairstyleDir = /home/ubuntu/change_hair/project/data/ref_hairstyle
haircolorDir= /home/ubuntu/change_hair/project/data/ref_haircolor
userDir=/home/ubuntu/change_hair/project/data/userImage
tmp_dir=/home/ubuntu/change_hair/project/data/tmp
res_dir=/home/ubuntu/change_hair/project/data/res_dir
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
ref_user_dir = /home/xsl/change_hair/project/data/ref_user_imgs
train_dir = /home/xsl/change_hair/data/train_material
refImgDir=/home/xsl/change_hair/project/data/refImage
hair_template_material_dir=/home/xsl/change_hair/project/data/hair_template_material
ref_color=/home/xsl/change_hair/project/data/ref_color
ref_color_img=/home/xsl/change_hair/project/data/ref_color_imgs
upload_train_dir=/home/xsl/change_hair/project/data/upload_train_imgs
refer_dir = /home/ubuntu/change_hair/project/data/ref_online
ref_user_dir = /home/ubuntu/change_hair/project/data/ref_user_imgs
train_dir = /home/ubuntu/change_hair/data/train_material
refImgDir=/home/ubuntu/change_hair/project/data/refImage
hair_template_material_dir=/home/ubuntu/change_hair/project/data/hair_template_material
ref_color=/home/ubuntu/change_hair/project/data/ref_color
ref_color_img=/home/ubuntu/change_hair/project/data/ref_color_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
+10 -5
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@@ -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)
# cv2.imwrite('/home/student/Desktop/tmp_color/need/face_base.png', face_base)
if status1 == 0:
return face_base, user_matting_8uc1_bald_orisize, 0
if os.path.exists(haircolor_dir_tmp):
face_base, status1 = self.infer_haircolor_tj(user_rgb_8uc3_orisize, haircolor_dir_tmp)
# cv2.imwrite('/home/student/Desktop/tmp_color/need/face_base.png', face_base)
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
+2 -1
View File
@@ -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
+3
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@@ -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
+5 -5
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@@ -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'
webui_lora_dir = '/home/xsl/change_hair/project/onediff/stable-diffusion-webui/models/Lora'
kohya_ss_home_dir = '/home/ubuntu/change_hair/project/kohya_ss_home'
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
+4
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@@ -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,