lipku
使用mu生成形象时无错误反馈，但并未完成形象生成
(nerfstream) E:\1yiji\LiveTalking-main>python genavatar_musetalk.py --avatar_id musetalk_avatar2 --file E:\1yiji\1.mp4 E:\anaconda3\envs\nerfstream\lib\site-packages\torch\cuda_init_.py:129: UserWarning: CUDA initialization: The NVIDIA driver on your system is too old (found version 11040). Please update your GPU driver by downloading and installing a new version from the URL: http://www.nvidia.com/Download/index.aspx Alternatively, go to: https://pytorch.org/ to install a PyTorch version that has been compiled with your version of the CUDA driver. (Triggered internally at C:\cb\pytorch_1000000000000\work\c10\cuda\CUDAFunctions.cpp:108.) return torch._C.cuda_getDeviceCount() > 0 E:\anaconda3\envs\nerfstream\lib\site-packages\mmengine\optim\optimizer\zero_optimizer.py:11: DeprecationWarning: TorchScript support for functional optimizers is deprecated and will be removed in a future PyTorch release. Consider using the torch.compile optimizer instead. from torch.distributed.optim import Loads checkpoint by local backend from path: ./models/dwpose/dw-ll_ucoco_384.pth E:\anaconda3\envs\nerfstream\lib\site-packages\mmengine\runner\checkpoint.py:347: FutureWarning: You are using torch.load with weights_only=False (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for weights_only will be flipped to True. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via torch.serialization.add_safe_globals. We recommend you start setting weights_only=True for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature. checkpoint = torch.load(filename, map_location=map_location) load unet model from models\musetalkV15\unet.pth E:\1yiji\LiveTalking-main\musetalk\models\unet.py:44: FutureWarning: You are using torch.load with weights_only=False (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for weights_only will be flipped to True. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via torch.serialization.add_safe_globals. We recommend you start setting weights_only=True for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature. weights = torch.load(model_path) if torch.cuda.is_available() else torch.load(model_path, map_location=self.device) E:\1yiji\LiveTalking-main\musetalk\utils\face_parsing\resnet.py:83: FutureWarning: You are using torch.load with weights_only=False (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for weights_only will be flipped to True. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via torch.serialization.add_safe_globals. We recommend you start setting weights_only=True for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature. state_dict = torch.load(model_path) #modelzoo.load_url(resnet18_url) E:\1yiji\LiveTalking-main\musetalk\utils\face_parsing_init.py:67: FutureWarning: You are using torch.load with weights_only=False (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for weights_only will be flipped to True. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via torch.serialization.add_safe_globals. We recommend you start setting weights_only=True for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature. net.load_state_dict(torch.load(model_pth, map_location=torch.device('cpu'))) extracting landmarks... reading images... 100%|████████████████████████████████████████████████████████████████████████████████| 919/919 [00:12<00:00, 71.72it/s] get key_landmark and face bounding boxes with the default value 0%| | 0/919 [00:00<?, ?it/s]E:\anaconda3\envs\nerfstream\lib\site-packages\mmdet\models\layers\se_layer.py:158: FutureWarning: torch.cuda.amp.autocast(args...) is deprecated. Please use torch.amp.autocast('cuda', args...) instead. with torch.cuda.amp.autocast(enabled=False): E:\anaconda3\envs\nerfstream\lib\site-packages\mmdet\models\backbones\csp_darknet.py:118: FutureWarning: torch.cuda.amp.autocast(args...) is deprecated. Please use torch.amp.autocast('cuda', args...) instead. with torch.cuda.amp.autocast(enabled=False): 100%|████████████████████████████████████████████████████████████████████████████████| 919/919 [33:01<00:00, 2.16s/it] bbox_shift parameter adjustment************** Total frame:「919」 Manually adjust range : [ -9~9 ] , the current value: 0
各位大佬这个问题怎么解决，看样子是使用命令的时候多加一个参数吗？要怎么操作呢？
50显卡吗？ E:\1yiji\LiveTalking-main\musetalk\utils\face_parsing_init.py这个文件你搜索一下torch.load 里面加个参数：weights_only=False 有好几个文件都要改 对照错误提示每个都改一下吧 另外显卡驱动貌似要更新了· 这里有一个musetalk的50系显卡适配教程：https://gitee.com/Wilson_Lws/MuseTalk-50Series-Adaptation/blob/master/README.md
50显卡吗？ E:\1yiji\LiveTalking-main\musetalk\utils\face_parsing_init.py这个文件你搜索一下torch.load 里面加个参数：weights_only=False 有好几个文件都要改 对照错误提示每个都改一下吧 另外显卡驱动貌似要更新了· 这里有一个musetalk的50系显卡适配教程：https://gitee.com/Wilson_Lws/MuseTalk-50Series-Adaptation/blob/master/README.md
不是50，GT730很老的显卡了
50显卡吗？ E:\1yiji\LiveTalking-main\musetalk\utils\face_parsing_init.py这个文件你搜索一下torch.load 里面加个参数：weights_only=False 有好几个文件都要改 对照错误提示每个都改一下吧 另外显卡驱动貌似要更新了· 这里有一个musetalk的50系显卡适配教程：https://gitee.com/Wilson_Lws/MuseTalk-50Series-Adaptation/blob/master/README.md
不是50，GT730很老的显卡了
···GT730用musetalk估计是跑不起来的··不过可以试试·先把显卡驱动更新了吧：（CUDA initialization: The NVIDIA driver on your system is too old (found version 11040)） 驱动版本太老了 然后就是torch.load，需要对着报错挨个找文件修改了 torch.load(model_path)改成torch.load(model_path, weights_only=False)