facechain tab does not appear in Automatic1111 WebUI version: v1.9.4

[nitinmukesh]

venv "C:\sd\stable-diffusion-webui\venv\Scripts\Python.exe"
Python 3.10.6 (tags/v3.10.6:9c7b4bd, Aug  1 2022, 21:53:49) [MSC v.1932 64 bit (AMD64)]
Version: v1.9.4
Commit hash: feee37d75f1b168768014e4634dcb156ee649c05
Installing requirements for diffusers
Launching Web UI with arguments:
no module 'xformers'. Processing without...
no module 'xformers'. Processing without...
No module 'xformers'. Proceeding without it.
Loading weights [6ce0161689] from C:\sd\stable-diffusion-webui\models\Stable-diffusion\v1-5-pruned-emaonly.safetensors
Creating model from config: C:\sd\stable-diffusion-webui\configs\v1-inference.yaml
C:\sd\stable-diffusion-webui\venv\lib\site-packages\huggingface_hub\file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
  warnings.warn(
C:\sd\stable-diffusion-webui\venv\lib\site-packages\diffusers\models\transformers\transformer_2d.py:34: FutureWarning: `Transformer2DModelOutput` is deprecated and will be removed in version 1.0.0. Importing `Transformer2DModelOutput` from `diffusers.models.transformer_2d` is deprecated and this will be removed in a future version. Please use `from diffusers.models.modeling_outputs import Transformer2DModelOutput`, instead.
  deprecate("Transformer2DModelOutput", "1.0.0", deprecation_message)
2024-06-27 16:03:08,582 - modelscope - INFO - PyTorch version 2.1.2+cu121 Found.
2024-06-27 16:03:08,586 - modelscope - INFO - Loading ast index from C:\Users\nitin\.cache\modelscope\ast_indexer
2024-06-27 16:03:08,860 - modelscope - INFO - Loading done! Current index file version is 1.15.0, with md5 7155d354cd150df5c8c5540d1c5c849a and a total number of 980 components indexed
秋日胡杨风(Autumn populus euphratica style)
2024-06-27 16:03:11,986 - modelscope - INFO - Use user-specified model revision: v1
Applying attention optimization: Doggettx... done.
萧瑟秋天风(Bleak autumn style)
Model loaded in 5.8s (load weights from disk: 0.3s, create model: 0.4s, apply weights to model: 4.7s, calculate empty prompt: 0.3s).
2024-06-27 16:03:13,893 - modelscope - INFO - Use user-specified model revision: v1
漫画风(Cartoon)
2024-06-27 16:03:15,843 - modelscope - INFO - Use user-specified model revision: v1.0.0
旗袍风(Cheongsam)
2024-06-27 16:03:17,801 - modelscope - INFO - Use user-specified model revision: v1.0.0
中国新年风(Chinese New Year Style)
2024-06-27 16:03:19,730 - modelscope - INFO - Use user-specified model revision: v2
冬季汉服(Chinese winter hanfu)
2024-06-27 16:03:21,600 - modelscope - INFO - Use user-specified model revision: v1.0.0
圣诞风(Christmas)
2024-06-27 16:03:23,550 - modelscope - INFO - Use user-specified model revision: v1.0.0
炫彩少女风(Colorful rainbow style)
2024-06-27 16:03:25,304 - modelscope - INFO - Use user-specified model revision: v1.0.0
自然清冷风(Cool tones)
2024-06-27 16:03:27,214 - modelscope - INFO - Use user-specified model revision: v1.0.0
西部牛仔风(Cowboy style)
2024-06-27 16:03:29,006 - modelscope - INFO - Use user-specified model revision: v1.0.0
林中鹿女风(Deer girl)
2024-06-27 16:03:30,895 - modelscope - INFO - Use user-specified model revision: v3.2.0
主题乐园风(Disneyland)
2024-06-27 16:03:32,939 - modelscope - INFO - Use user-specified model revision: v1.0.0
海洋风(Ocean)
2024-06-27 16:03:34,819 - modelscope - INFO - Use user-specified model revision: v2.0.0
敦煌风(Dunhuang)
2024-06-27 16:03:36,632 - modelscope - INFO - Use user-specified model revision: v2
多巴胺风格(Colourful Style)
2024-06-27 16:03:38,765 - modelscope - INFO - Use user-specified model revision: v1.0.0
中华刺绣风(Embroidery)
2024-06-27 16:03:40,858 - modelscope - INFO - Use user-specified model revision: v1.0.0
欧式田野风(European fields)
2024-06-27 16:03:42,875 - modelscope - INFO - Use user-specified model revision: v5
仙女风(Fairy style)
2024-06-27 16:03:45,108 - modelscope - INFO - Use user-specified model revision: v1.0.0
时尚墨镜风(Fashion glasses)
2024-06-27 16:03:47,127 - modelscope - INFO - Use user-specified model revision: v1.1
火红少女风(Flame Red Style)
2024-06-27 16:03:49,181 - modelscope - INFO - Use user-specified model revision: v1.0.0
花园风(Flowers)
2024-06-27 16:03:51,149 - modelscope - INFO - Use user-specified model revision: v1.0.0
绅士风(Gentleman style)
2024-06-27 16:03:53,448 - modelscope - INFO - Use user-specified model revision: v1.0.0
国风(GuoFeng Style)
2024-06-27 16:03:55,411 - modelscope - INFO - Use user-specified model revision: v1.0.0
嘻哈风(Hiphop style)
2024-06-27 16:03:57,226 - modelscope - INFO - Use user-specified model revision: v1.0.1
夜景港风(Hong Kong night)
2024-06-27 16:03:59,139 - modelscope - INFO - Use user-specified model revision: v1.0.0
印度风(India)
2024-06-27 16:04:01,076 - modelscope - INFO - Use user-specified model revision: v1.0.0
雪山羽绒服风(Jacket in Snow Mountain)
2024-06-27 16:04:03,051 - modelscope - INFO - Use user-specified model revision: v7
Downloading: 100%|██████████████████████████████████████████████████████████████████████| 248/248 [00:01<00:00, 186B/s]
日系和服风(Kimono Style)
2024-06-27 16:04:06,338 - modelscope - INFO - Use user-specified model revision: v1.0.0
哥特洛丽塔(Gothic Lolita)
2024-06-27 16:04:08,342 - modelscope - INFO - Use user-specified model revision: v1.0.0
洛丽塔(Lolita)
2024-06-27 16:04:10,317 - modelscope - INFO - Use user-specified model revision: v1.0.0
花环洛丽塔(Flora Lolita)
2024-06-27 16:04:12,310 - modelscope - INFO - Use user-specified model revision: v3.0.1
女仆风(Maid style)
2024-06-27 16:04:14,174 - modelscope - INFO - Use user-specified model revision: v1.0.0
机械风(Mechanical)
2024-06-27 16:04:16,003 - modelscope - INFO - Use user-specified model revision: v1.0.0
男士西装风(Men's Suit)
2024-06-27 16:04:17,874 - modelscope - INFO - Use user-specified model revision: v2
苗族服装风(Miao style)
2024-06-27 16:04:19,679 - modelscope - INFO - Use user-specified model revision: v3.0
模特风(Model style)
2024-06-27 16:04:21,528 - modelscope - INFO - Use user-specified model revision: v1.0.0
蒙古草原风(Mongolian)
2024-06-27 16:04:23,414 - modelscope - INFO - Use user-specified model revision: v1.0.0
机车风(Motorcycle race style)
2024-06-27 16:04:25,613 - modelscope - INFO - Use user-specified model revision: v1.0.0
夏日海滩风(Summer Ocean Vibe)
2024-06-27 16:04:27,515 - modelscope - INFO - Use user-specified model revision: v1.0.0
京剧名旦风(Female role in Peking opera)
2024-06-27 16:04:29,623 - modelscope - INFO - Use user-specified model revision: v1.0.0
拍立得风(Polaroid style)
2024-06-27 16:04:31,451 - modelscope - INFO - Use user-specified model revision: v1.0.0
贵族公主风(Princess costum)
2024-06-27 16:04:33,374 - modelscope - INFO - Use user-specified model revision: v1.0.0
雨夜(Rainy night)
2024-06-27 16:04:35,224 - modelscope - INFO - Use user-specified model revision: v1.0.0
红发礼服风(Red Style)
2024-06-27 16:04:37,091 - modelscope - INFO - Use user-specified model revision: v1.0.0
复古风(Retro Style)
2024-06-27 16:04:39,091 - modelscope - INFO - Use user-specified model revision: v1.0.0
漫游宇航员(Roaming Astronaut)
2024-06-27 16:04:41,064 - modelscope - INFO - Use user-specified model revision: v3.0.1
校服风(School uniform)
2024-06-27 16:04:42,953 - modelscope - INFO - Use user-specified model revision: v1.0.0
科幻风(Science fiction style)
2024-06-27 16:04:45,011 - modelscope - INFO - Use user-specified model revision: v1.0.0
绿茵球场风(Soccer Field)
2024-06-27 16:04:46,831 - modelscope - INFO - Use user-specified model revision: v1.0.0
街拍风(Street style)
2024-06-27 16:04:48,758 - modelscope - INFO - Use user-specified model revision: v1.0.0
藏族服饰风(Tibetan clothing style)
2024-06-27 16:04:50,580 - modelscope - INFO - Use user-specified model revision: v1
古风(Traditional chinese style)
2024-06-27 16:04:52,444 - modelscope - INFO - Use user-specified model revision: v5
Downloading: 100%|██████████████████████████████████████████████████████████████████████| 302/302 [00:01<00:00, 248B/s]
丁达尔风(Tyndall Light)
2024-06-27 16:04:55,529 - modelscope - INFO - Use user-specified model revision: v1.0.0
梦幻深海风(Sea World)
2024-06-27 16:04:57,390 - modelscope - INFO - Use user-specified model revision: v1.0.0
婚纱风(Wedding dress)
2024-06-27 16:04:59,261 - modelscope - INFO - Use user-specified model revision: v1.0.0
婚纱风-2(Wedding dress 2)
2024-06-27 16:05:01,161 - modelscope - INFO - Use user-specified model revision: v1.0.0
西部牛仔风(West cowboy)
2024-06-27 16:05:03,058 - modelscope - INFO - Use user-specified model revision: v1.0.0
西部风(Wild west style)
2024-06-27 16:05:04,843 - modelscope - INFO - Use user-specified model revision: v1.0.0
女巫风(Witch style)
2024-06-27 16:05:06,955 - modelscope - INFO - Use user-specified model revision: v1.0.0
绿野仙踪(Wizard of Oz)
2024-06-27 16:05:08,777 - modelscope - INFO - Use user-specified model revision: v1.0.0
藏族风(ZangZu Style)
2024-06-27 16:05:10,598 - modelscope - INFO - Use user-specified model revision: v1.0.0
壮族服装风(Zhuang style)
2024-06-27 16:05:12,514 - modelscope - INFO - Use user-specified model revision: v5
盔甲风(Armor)
芭比娃娃(Barbie Doll)
2024-06-27 16:05:14,350 - modelscope - INFO - Use user-specified model revision: v2
休闲生活风(Casual Lifestyle)
2024-06-27 16:05:16,205 - modelscope - INFO - Use user-specified model revision: v2
凤冠霞帔(Chinese traditional gorgeous suit)
2024-06-27 16:05:18,019 - modelscope - INFO - Use user-specified model revision: v1.0.0
赛博朋克(Cybernetics punk)
优雅公主(Elegant Princess)
2024-06-27 16:05:19,784 - modelscope - INFO - Use user-specified model revision: v2
女士晚礼服(Gown)
汉服风(Hanfu)
白月光(Innocent Girl in White Dress)
鬼马少女(Pixy Girl)
2024-06-27 16:05:21,709 - modelscope - INFO - Use user-specified model revision: v2
白雪公主(Snow White)
2024-06-27 16:05:23,783 - modelscope - INFO - Use user-specified model revision: v1.0.0
T恤衫(T-shirt)
工作服(Working suit)
2024-06-27 16:05:25,601 - modelscope - INFO - Use user-specified model revision: v1.0.1
2024-06-27 16:05:30,363 - modelscope - INFO - Use user-specified model revision: v1.0.1
2024-06-27 16:05:31,705 - modelscope - INFO - initiate model from C:\Users\nitin\.cache\modelscope\hub\damo\cv_resnet101_image-multiple-human-parsing
2024-06-27 16:05:31,705 - modelscope - INFO - initiate model from location C:\Users\nitin\.cache\modelscope\hub\damo\cv_resnet101_image-multiple-human-parsing.
2024-06-27 16:05:31,708 - modelscope - INFO - initialize model from C:\Users\nitin\.cache\modelscope\hub\damo\cv_resnet101_image-multiple-human-parsing
2024-06-27 16:05:32,014 - modelscope - INFO - loading model from C:\Users\nitin\.cache\modelscope\hub\damo\cv_resnet101_image-multiple-human-parsing\pytorch_model.pt
2024-06-27 16:05:32,788 - modelscope - INFO - criterion.empty_weight doesn't exist in current model, skip loading.
2024-06-27 16:05:32,917 - modelscope - INFO - load model done
2024-06-27 16:05:32,941 - modelscope - WARNING - No preprocessor field found in cfg.
2024-06-27 16:05:32,942 - modelscope - WARNING - No val key and type key found in preprocessor domain of configuration.json file.
2024-06-27 16:05:32,942 - modelscope - WARNING - Cannot find available config to build preprocessor at mode inference, current config: {'model_dir': 'C:\\Users\\nitin\\.cache\\modelscope\\hub\\damo\\cv_resnet101_image-multiple-human-parsing'}. trying to build by task and model information.
2024-06-27 16:05:32,942 - modelscope - WARNING - No preprocessor key ('m2fp', 'image-segmentation') found in PREPROCESSOR_MAP, skip building preprocessor.
2024-06-27 16:05:35,884 - modelscope - INFO - Use user-specified model revision: v1.0.3
2024-06-27 16:05:37,594 - modelscope - WARNING - ('PIPELINES', 'face_fusion_torch', 'face_fusion_torch') not found in ast index file
2024-06-27 16:05:37,597 - modelscope - INFO - initiate model from C:\Users\nitin\.cache\modelscope\hub\damo\cv_unet_face_fusion_torch
2024-06-27 16:05:37,598 - modelscope - INFO - initiate model from location C:\Users\nitin\.cache\modelscope\hub\damo\cv_unet_face_fusion_torch.
2024-06-27 16:05:37,605 - modelscope - INFO - initialize model from C:\Users\nitin\.cache\modelscope\hub\damo\cv_unet_face_fusion_torch
2024-06-27 16:05:37,636 - modelscope - WARNING - ('MODELS', 'face_fusion_torch', 'face_fusion_torch') not found in ast index file
2024-06-27 16:05:40,725 - modelscope - WARNING - Model revision not specified, use revision: v1.1
2024-06-27 16:05:41,307 - modelscope - INFO - initiate model from C:\Users\nitin\.cache\modelscope\hub\damo\cv_ddsar_face-detection_iclr23-damofd
2024-06-27 16:05:41,308 - modelscope - INFO - initiate model from location C:\Users\nitin\.cache\modelscope\hub\damo\cv_ddsar_face-detection_iclr23-damofd.
2024-06-27 16:05:41,313 - modelscope - INFO - initialize model from C:\Users\nitin\.cache\modelscope\hub\damo\cv_ddsar_face-detection_iclr23-damofd
2024-06-27 16:05:42,385 - mmcv - INFO - initialize PAFPN with init_cfg {'type': 'Xavier', 'layer': 'Conv2d', 'distribution': 'uniform'}
2024-06-27 16:05:42,389 - mmcv - INFO -
lateral_convs.0.conv.weight - torch.Size([16, 64, 1, 1]):
XavierInit: gain=1, distribution=uniform, bias=0

2024-06-27 16:05:42,389 - mmcv - INFO -
lateral_convs.0.conv.bias - torch.Size([16]):
The value is the same before and after calling `init_weights` of PAFPN

2024-06-27 16:05:42,389 - mmcv - INFO -
lateral_convs.1.conv.weight - torch.Size([16, 120, 1, 1]):
XavierInit: gain=1, distribution=uniform, bias=0

2024-06-27 16:05:42,389 - mmcv - INFO -
lateral_convs.1.conv.bias - torch.Size([16]):
The value is the same before and after calling `init_weights` of PAFPN

2024-06-27 16:05:42,391 - mmcv - INFO -
lateral_convs.2.conv.weight - torch.Size([16, 160, 1, 1]):
XavierInit: gain=1, distribution=uniform, bias=0

2024-06-27 16:05:42,391 - mmcv - INFO -
lateral_convs.2.conv.bias - torch.Size([16]):
The value is the same before and after calling `init_weights` of PAFPN

2024-06-27 16:05:42,391 - mmcv - INFO -
fpn_convs.0.conv.weight - torch.Size([16, 16, 3, 3]):
XavierInit: gain=1, distribution=uniform, bias=0

2024-06-27 16:05:42,391 - mmcv - INFO -
fpn_convs.0.conv.bias - torch.Size([16]):
The value is the same before and after calling `init_weights` of PAFPN

2024-06-27 16:05:42,391 - mmcv - INFO -
fpn_convs.1.conv.weight - torch.Size([16, 16, 3, 3]):
XavierInit: gain=1, distribution=uniform, bias=0

2024-06-27 16:05:42,392 - mmcv - INFO -
fpn_convs.1.conv.bias - torch.Size([16]):
The value is the same before and after calling `init_weights` of PAFPN

2024-06-27 16:05:42,392 - mmcv - INFO -
fpn_convs.2.conv.weight - torch.Size([16, 16, 3, 3]):
XavierInit: gain=1, distribution=uniform, bias=0

2024-06-27 16:05:42,392 - mmcv - INFO -
fpn_convs.2.conv.bias - torch.Size([16]):
The value is the same before and after calling `init_weights` of PAFPN

2024-06-27 16:05:42,392 - mmcv - INFO -
downsample_convs.0.conv.weight - torch.Size([16, 16, 3, 3]):
XavierInit: gain=1, distribution=uniform, bias=0

2024-06-27 16:05:42,393 - mmcv - INFO -
downsample_convs.0.conv.bias - torch.Size([16]):
The value is the same before and after calling `init_weights` of PAFPN

2024-06-27 16:05:42,393 - mmcv - INFO -
downsample_convs.1.conv.weight - torch.Size([16, 16, 3, 3]):
XavierInit: gain=1, distribution=uniform, bias=0

2024-06-27 16:05:42,393 - mmcv - INFO -
downsample_convs.1.conv.bias - torch.Size([16]):
The value is the same before and after calling `init_weights` of PAFPN

2024-06-27 16:05:42,393 - mmcv - INFO -
pafpn_convs.0.conv.weight - torch.Size([16, 16, 3, 3]):
XavierInit: gain=1, distribution=uniform, bias=0

2024-06-27 16:05:42,393 - mmcv - INFO -
pafpn_convs.0.conv.bias - torch.Size([16]):
The value is the same before and after calling `init_weights` of PAFPN

2024-06-27 16:05:42,393 - mmcv - INFO -
pafpn_convs.1.conv.weight - torch.Size([16, 16, 3, 3]):
XavierInit: gain=1, distribution=uniform, bias=0

2024-06-27 16:05:42,393 - mmcv - INFO -
pafpn_convs.1.conv.bias - torch.Size([16]):
The value is the same before and after calling `init_weights` of PAFPN

2024-06-27 16:05:42,394 - modelscope - INFO - loading model from C:\Users\nitin\.cache\modelscope\hub\damo\cv_ddsar_face-detection_iclr23-damofd\pytorch_model.pt
load checkpoint from local path: C:\Users\nitin\.cache\modelscope\hub\damo\cv_ddsar_face-detection_iclr23-damofd\pytorch_model.pt
2024-06-27 16:05:42,743 - modelscope - INFO - load model done
2024-06-27 16:05:54,169 - modelscope - INFO - load facefusion models done
2024-06-27 16:05:56,355 - modelscope - INFO - init done
2024-06-27 16:05:56,420 - modelscope - WARNING - No preprocessor field found in cfg.
2024-06-27 16:05:56,420 - modelscope - WARNING - No val key and type key found in preprocessor domain of configuration.json file.
2024-06-27 16:05:56,420 - modelscope - WARNING - Cannot find available config to build preprocessor at mode inference, current config: {'model_dir': 'C:\\Users\\nitin\\.cache\\modelscope\\hub\\damo\\cv_unet_face_fusion_torch'}. trying to build by task and model information.
2024-06-27 16:05:56,420 - modelscope - WARNING - No preprocessor key ('face_fusion_torch', 'face_fusion_torch') found in PREPROCESSOR_MAP, skip building preprocessor.
2024-06-27 16:05:56,426 - modelscope - INFO - image face fusion model init done
2024-06-27 16:05:57,715 - modelscope - INFO - Use user-specified model revision: v1.0.1
2024-06-27 16:06:04,110 - modelscope - INFO - Use user-specified model revision: v2.0
2024-06-27 16:06:04,733 - modelscope - INFO - initiate model from C:\Users\nitin\.cache\modelscope\hub\damo\cv_manual_face-quality-assessment_fqa
2024-06-27 16:06:04,733 - modelscope - INFO - initiate model from location C:\Users\nitin\.cache\modelscope\hub\damo\cv_manual_face-quality-assessment_fqa.
2024-06-27 16:06:04,753 - modelscope - WARNING - No preprocessor field found in cfg.
2024-06-27 16:06:04,754 - modelscope - WARNING - No val key and type key found in preprocessor domain of configuration.json file.
2024-06-27 16:06:04,755 - modelscope - WARNING - Cannot find available config to build preprocessor at mode inference, current config: {'model_dir': 'C:\\Users\\nitin\\.cache\\modelscope\\hub\\damo\\cv_manual_face-quality-assessment_fqa'}. trying to build by task and model information.
2024-06-27 16:06:04,755 - modelscope - WARNING - Find task: face-quality-assessment, model type: None. Insufficient information to build preprocessor, skip building preprocessor
2024-06-27 16:06:07,657 - modelscope - WARNING - Model revision not specified, use revision: v1.1
2024-06-27 16:06:08,192 - modelscope - INFO - initiate model from C:\Users\nitin\.cache\modelscope\hub\damo\cv_ddsar_face-detection_iclr23-damofd
2024-06-27 16:06:08,193 - modelscope - INFO - initiate model from location C:\Users\nitin\.cache\modelscope\hub\damo\cv_ddsar_face-detection_iclr23-damofd.
2024-06-27 16:06:08,200 - modelscope - INFO - initialize model from C:\Users\nitin\.cache\modelscope\hub\damo\cv_ddsar_face-detection_iclr23-damofd
2024-06-27 16:06:08,347 - mmcv - INFO - initialize PAFPN with init_cfg {'type': 'Xavier', 'layer': 'Conv2d', 'distribution': 'uniform'}
2024-06-27 16:06:08,350 - mmcv - INFO -
lateral_convs.0.conv.weight - torch.Size([16, 64, 1, 1]):
XavierInit: gain=1, distribution=uniform, bias=0

2024-06-27 16:06:08,351 - mmcv - INFO -
lateral_convs.0.conv.bias - torch.Size([16]):
The value is the same before and after calling `init_weights` of PAFPN

2024-06-27 16:06:08,351 - mmcv - INFO -
lateral_convs.1.conv.weight - torch.Size([16, 120, 1, 1]):
XavierInit: gain=1, distribution=uniform, bias=0

2024-06-27 16:06:08,352 - mmcv - INFO -
lateral_convs.1.conv.bias - torch.Size([16]):
The value is the same before and after calling `init_weights` of PAFPN

2024-06-27 16:06:08,352 - mmcv - INFO -
lateral_convs.2.conv.weight - torch.Size([16, 160, 1, 1]):
XavierInit: gain=1, distribution=uniform, bias=0

2024-06-27 16:06:08,352 - mmcv - INFO -
lateral_convs.2.conv.bias - torch.Size([16]):
The value is the same before and after calling `init_weights` of PAFPN

2024-06-27 16:06:08,354 - mmcv - INFO -
fpn_convs.0.conv.weight - torch.Size([16, 16, 3, 3]):
XavierInit: gain=1, distribution=uniform, bias=0

2024-06-27 16:06:08,354 - mmcv - INFO -
fpn_convs.0.conv.bias - torch.Size([16]):
The value is the same before and after calling `init_weights` of PAFPN

2024-06-27 16:06:08,354 - mmcv - INFO -
fpn_convs.1.conv.weight - torch.Size([16, 16, 3, 3]):
XavierInit: gain=1, distribution=uniform, bias=0

2024-06-27 16:06:08,355 - mmcv - INFO -
fpn_convs.1.conv.bias - torch.Size([16]):
The value is the same before and after calling `init_weights` of PAFPN

2024-06-27 16:06:08,355 - mmcv - INFO -
fpn_convs.2.conv.weight - torch.Size([16, 16, 3, 3]):
XavierInit: gain=1, distribution=uniform, bias=0

2024-06-27 16:06:08,356 - mmcv - INFO -
fpn_convs.2.conv.bias - torch.Size([16]):
The value is the same before and after calling `init_weights` of PAFPN

2024-06-27 16:06:08,356 - mmcv - INFO -
downsample_convs.0.conv.weight - torch.Size([16, 16, 3, 3]):
XavierInit: gain=1, distribution=uniform, bias=0

2024-06-27 16:06:08,357 - mmcv - INFO -
downsample_convs.0.conv.bias - torch.Size([16]):
The value is the same before and after calling `init_weights` of PAFPN

2024-06-27 16:06:08,357 - mmcv - INFO -
downsample_convs.1.conv.weight - torch.Size([16, 16, 3, 3]):
XavierInit: gain=1, distribution=uniform, bias=0

2024-06-27 16:06:08,358 - mmcv - INFO -
downsample_convs.1.conv.bias - torch.Size([16]):
The value is the same before and after calling `init_weights` of PAFPN

2024-06-27 16:06:08,358 - mmcv - INFO -
pafpn_convs.0.conv.weight - torch.Size([16, 16, 3, 3]):
XavierInit: gain=1, distribution=uniform, bias=0

2024-06-27 16:06:08,359 - mmcv - INFO -
pafpn_convs.0.conv.bias - torch.Size([16]):
The value is the same before and after calling `init_weights` of PAFPN

2024-06-27 16:06:08,359 - mmcv - INFO -
pafpn_convs.1.conv.weight - torch.Size([16, 16, 3, 3]):
XavierInit: gain=1, distribution=uniform, bias=0

2024-06-27 16:06:08,360 - mmcv - INFO -
pafpn_convs.1.conv.bias - torch.Size([16]):
The value is the same before and after calling `init_weights` of PAFPN

2024-06-27 16:06:08,361 - modelscope - INFO - loading model from C:\Users\nitin\.cache\modelscope\hub\damo\cv_ddsar_face-detection_iclr23-damofd\pytorch_model.pt
load checkpoint from local path: C:\Users\nitin\.cache\modelscope\hub\damo\cv_ddsar_face-detection_iclr23-damofd\pytorch_model.pt
2024-06-27 16:06:08,679 - modelscope - INFO - load model done
2024-06-27 16:06:08,722 - modelscope - INFO - loading model from C:\Users\nitin\.cache\modelscope\hub\damo\cv_manual_face-quality-assessment_fqa\model.onnx
2024-06-27 16:06:08.9216281 [E:onnxruntime:Default, provider_bridge_ort.cc:1744 onnxruntime::TryGetProviderInfo_CUDA] C:\a\_work\1\s\onnxruntime\core\session\provider_bridge_ort.cc:1426 onnxruntime::ProviderLibrary::Get [ONNXRuntimeError] : 1 : FAIL : LoadLibrary failed with error 126 "" when trying to load "C:\sd\stable-diffusion-webui\venv\lib\site-packages\onnxruntime\capi\onnxruntime_providers_cuda.dll"

*************** EP Error ***************
EP Error C:\a\_work\1\s\onnxruntime\python\onnxruntime_pybind_state.cc:866 onnxruntime::python::CreateExecutionProviderInstance CUDA_PATH is set but CUDA wasnt able to be loaded. Please install the correct version of CUDA andcuDNN as mentioned in the GPU requirements page  (https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html#requirements),  make sure they're in the PATH, and that your GPU is supported.
 when using ['CUDAExecutionProvider', 'CPUExecutionProvider']
Falling back to ['CUDAExecutionProvider', 'CPUExecutionProvider'] and retrying.
****************************************
2024-06-27 16:06:09.0845694 [E:onnxruntime:Default, provider_bridge_ort.cc:1744 onnxruntime::TryGetProviderInfo_CUDA] C:\a\_work\1\s\onnxruntime\core\session\provider_bridge_ort.cc:1426 onnxruntime::ProviderLibrary::Get [ONNXRuntimeError] : 1 : FAIL : LoadLibrary failed with error 126 "" when trying to load "C:\sd\stable-diffusion-webui\venv\lib\site-packages\onnxruntime\capi\onnxruntime_providers_cuda.dll"

*** Error executing callback ui_tabs_callback for C:\sd\stable-diffusion-webui\extensions\facechain\scripts\facechain_sdwebui.py
    Traceback (most recent call last):
      File "C:\sd\stable-diffusion-webui\venv\lib\site-packages\onnxruntime\capi\onnxruntime_inference_collection.py", line 419, in __init__
        self._create_inference_session(providers, provider_options, disabled_optimizers)
      File "C:\sd\stable-diffusion-webui\venv\lib\site-packages\onnxruntime\capi\onnxruntime_inference_collection.py", line 483, in _create_inference_session
        sess.initialize_session(providers, provider_options, disabled_optimizers)
    RuntimeError: C:\a\_work\1\s\onnxruntime\python\onnxruntime_pybind_state.cc:866 onnxruntime::python::CreateExecutionProviderInstance CUDA_PATH is set but CUDA wasnt able to be loaded. Please install the correct version of CUDA andcuDNN as mentioned in the GPU requirements page  (https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html#requirements),  make sure they're in the PATH, and that your GPU is supported.


    The above exception was the direct cause of the following exception:

    Traceback (most recent call last):
      File "C:\sd\stable-diffusion-webui\venv\lib\site-packages\modelscope\utils\registry.py", line 212, in build_from_cfg
        return obj_cls(**args)
      File "C:\sd\stable-diffusion-webui\venv\lib\site-packages\modelscope\pipelines\cv\face_quality_assessment_pipeline.py", line 55, in __init__
        self.sess, self.input_node_name, self.out_node_name = self.load_onnx_model(
      File "C:\sd\stable-diffusion-webui\venv\lib\site-packages\modelscope\pipelines\cv\face_quality_assessment_pipeline.py", line 63, in load_onnx_model
        sess = onnxruntime.InferenceSession(
      File "C:\sd\stable-diffusion-webui\venv\lib\site-packages\onnxruntime\capi\onnxruntime_inference_collection.py", line 432, in __init__
        raise fallback_error from e
      File "C:\sd\stable-diffusion-webui\venv\lib\site-packages\onnxruntime\capi\onnxruntime_inference_collection.py", line 427, in __init__
        self._create_inference_session(self._fallback_providers, None)
      File "C:\sd\stable-diffusion-webui\venv\lib\site-packages\onnxruntime\capi\onnxruntime_inference_collection.py", line 483, in _create_inference_session
        sess.initialize_session(providers, provider_options, disabled_optimizers)
    RuntimeError: C:\a\_work\1\s\onnxruntime\python\onnxruntime_pybind_state.cc:866 onnxruntime::python::CreateExecutionProviderInstance CUDA_PATH is set but CUDA wasnt able to be loaded. Please install the correct version of CUDA andcuDNN as mentioned in the GPU requirements page  (https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html#requirements),  make sure they're in the PATH, and that your GPU is supported.


    During handling of the above exception, another exception occurred:

    Traceback (most recent call last):
      File "C:\sd\stable-diffusion-webui\modules\script_callbacks.py", line 283, in ui_tabs_callback
        res += c.callback() or []
      File "C:\sd\stable-diffusion-webui\extensions\facechain\scripts\facechain_sdwebui.py", line 15, in on_ui_tabs
        import app
      File "C:\sd\stable-diffusion-webui\extensions\facechain\app.py", line 434, in <module>
        gen_portrait = GenPortrait()
      File "C:\sd\stable-diffusion-webui\extensions\facechain\facechain\inference_fact.py", line 305, in __init__
        self.face_quality_func = pipeline(
      File "C:\sd\stable-diffusion-webui\venv\lib\site-packages\modelscope\pipelines\builder.py", line 170, in pipeline
        return build_pipeline(cfg, task_name=task)
      File "C:\sd\stable-diffusion-webui\venv\lib\site-packages\modelscope\pipelines\builder.py", line 65, in build_pipeline
        return build_from_cfg(
      File "C:\sd\stable-diffusion-webui\venv\lib\site-packages\modelscope\utils\registry.py", line 215, in build_from_cfg
        raise type(e)(f'{obj_cls.__name__}: {e}')
    RuntimeError: FaceQualityAssessmentPipeline: C:\a\_work\1\s\onnxruntime\python\onnxruntime_pybind_state.cc:866 onnxruntime::python::CreateExecutionProviderInstance CUDA_PATH is set but CUDA wasnt able to be loaded. Please install the correct version of CUDA andcuDNN as mentioned in the GPU requirements page  (https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html#requirements),  make sure they're in the PATH, and that your GPU is supported.


---
Running on local URL:  http://127.0.0.1:7860

To create a public link, set `share=True` in `launch()`.
Startup time: 209.1s (prepare environment: 11.5s, import torch: 4.9s, import gradio: 2.6s, setup paths: 3.5s, initialize shared: 0.7s, other imports: 1.7s, load scripts: 1.0s, create ui: 182.4s, gradio launch: 0.5s).

(venv) C:\sd\stable-diffusion-webui>pip list

Package Version ------------------------- ------------ absl-py 2.1.0 accelerate 0.21.0 addict 2.4.0 aenum 3.1.15 aiofiles 23.2.1 aiohttp 3.9.5 aiosignal 1.3.1 aliyun-python-sdk-core 2.15.1 aliyun-python-sdk-kms 2.16.3 altair 5.3.0 antlr4-python3-runtime 4.9.3 anyio 3.7.1 async-timeout 4.0.3 attrs 23.2.0 blendmodes 2022 certifi 2024.6.2 cffi 1.16.0 charset-normalizer 3.3.2 clean-fid 0.1.35 click 8.1.7 clip 1.0 colorama 0.4.6 coloredlogs 15.0.1 contourpy 1.2.1 controlnet-aux 0.0.6 crcmod 1.7 cryptography 42.0.8 cycler 0.12.1 datasets 2.18.0 deprecation 2.1.0 diffusers 0.29.1 dill 0.3.8 diskcache 5.6.3 edge-tts 6.1.12 einops 0.4.1 exceptiongroup 1.2.1 facexlib 0.3.0 fastapi 0.94.0 ffmpy 0.3.2 filelock 3.15.4 filterpy 1.4.5 flatbuffers 24.3.25 fonttools 4.53.0 frozenlist 1.4.1 fsspec 2023.9.2 ftfy 6.2.0 gast 0.5.4 gitdb 4.0.11 GitPython 3.1.32 gradio 3.41.2 gradio_client 0.5.0 h11 0.12.0 httpcore 0.15.0 httpx 0.24.1 huggingface-hub 0.23.4 humanfriendly 10.0 idna 3.7 imageio 2.34.2 importlib_metadata 8.0.0 importlib_resources 6.4.0 inflection 0.5.1 Jinja2 3.1.4 jmespath 0.10.0 jsonmerge 1.8.0 jsonschema 4.22.0 jsonschema-specifications 2023.12.1 kiwisolver 1.4.5 kornia 0.6.7 lark 1.1.2 lazy_loader 0.4 lightning-utilities 0.11.2 llvmlite 0.43.0 MarkupSafe 2.1.5 matplotlib 3.9.0 mediapipe 0.10.3 mmcv-full 1.7.2 mmdet 2.26.0 modelscope 1.15.0 mpmath 1.3.0 multidict 6.0.5 multiprocess 0.70.16 networkx 3.3 numba 0.60.0 numpy 1.26.2 omegaconf 2.2.3 onnxruntime-gpu 1.18.0 open-clip-torch 2.20.0 opencv-contrib-python 4.10.0.84 opencv-python 4.10.0.84 orjson 3.10.5 oss2 2.18.6 packaging 24.1 pandas 2.2.2 piexif 1.1.3 Pillow 9.5.0 pillow-avif-plugin 1.4.3 pip 22.2.1 platformdirs 4.2.2 protobuf 3.20.1 psutil 5.9.5 pyarrow 16.1.0 pyarrow-hotfix 0.6 pycocotools 2.0.8 pycparser 2.22 pycryptodome 3.20.0 pydantic 1.10.17 pydub 0.25.1 pyparsing 3.1.2 pyreadline3 3.4.1 python-dateutil 2.9.0.post0 python-multipart 0.0.9 python-slugify 8.0.1 pytorch-lightning 1.9.4 pytz 2024.1 PyWavelets 1.6.0 PyYAML 6.0.1 referencing 0.35.1 regex 2024.5.15 requests 2.32.3 resize-right 0.0.2 rpds-py 0.18.1 safetensors 0.4.2 scikit-image 0.21.0 scipy 1.14.0 semantic-version 2.10.0 sentencepiece 0.2.0 setuptools 69.5.1 simplejson 3.19.2 six 1.16.0 slugify 0.0.1 smmap 5.0.1 sniffio 1.3.1 sortedcontainers 2.4.0 sounddevice 0.4.7 spandrel 0.1.6 starlette 0.26.1 sympy 1.12.1 terminaltables 3.1.10 text-unidecode 1.3 tifffile 2024.6.18 timm 1.0.7 tokenizers 0.13.3 tomesd 0.1.3 tomli 2.0.1 toolz 0.12.1 torch 2.1.2+cu121 torchdiffeq 0.2.3 torchmetrics 1.4.0.post0 torchsde 0.2.6 torchvision 0.16.2+cu121 tqdm 4.66.4 trampoline 0.1.2 transformers 4.30.2 typing_extensions 4.12.2 tzdata 2024.1 urllib3 2.2.2 uvicorn 0.30.1 wcwidth 0.2.13 websockets 11.0.3 xxhash 3.4.1 yapf 0.40.2 yarl 1.9.4 zipp 3.19.2