问一下提取人脸相关的问题

Double2and9

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当我提取人脸时就会出现以下的错误，显卡3060，驱动都安装好了，cuda也安装了，以为是系统问题重装了系统还是这个样子，能帮我看看吗
Error while processing data: Traceback (most recent call last):
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1375, in _do_call
    return fn(*args)
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1360, in _run_fn
    target_list, run_metadata)
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1453, in _call_tf_sessionrun
    run_metadata)
tensorflow.python.framework.errors_impl.ResourceExhaustedError: 2 root error(s) found.
  (0) Resource exhausted: OOM when allocating tensor with shape[64,642,362] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[{{node Pad_1}}]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

         [[Add_29/_4049]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

  (1) Resource exhausted: OOM when allocating tensor with shape[64,642,362] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[{{node Pad_1}}]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

0 successful operations.
0 derived errors ignored.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\joblib\SubprocessorBase.py", line 71, in _subprocess_run
    result = self.process_data (data)
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\mainscripts\Extractor.py", line 104, in process_data
    rects_extractor=self.rects_extractor,
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\mainscripts\Extractor.py", line 145, in rects_stage
    rects = data.rects = rects_extractor.extract (rotated_image, is_bgr=True)
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\facelib\S3FDExtractor.py", line 193, in extract
    olist = self.model.run ([ input_image[None,...] ] )
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 167, in run
    return nn.tf_sess.run ( self.run_output, feed_dict=feed_dict)
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 968, in run
    run_metadata_ptr)
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1191, in _run
    feed_dict_tensor, options, run_metadata)
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1369, in _do_run
    run_metadata)
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1394, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.ResourceExhaustedError: 2 root error(s) found.
  (0) Resource exhausted: OOM when allocating tensor with shape[64,642,362] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[node Pad_1 (defined at E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:87) ]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

         [[Add_29/_4049]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

  (1) Resource exhausted: OOM when allocating tensor with shape[64,642,362] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
         [[node Pad_1 (defined at E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:87) ]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

0 successful operations.
0 derived errors ignored.

Errors may have originated from an input operation.
Input Source operations connected to node Pad_1:
Relu (defined at E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\facelib\S3FDExtractor.py:93)

Input Source operations connected to node Pad_1:
Relu (defined at E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\facelib\S3FDExtractor.py:93)

Original stack trace for 'Pad_1':
  File "<string>", line 1, in <module>
  File "multiprocessing\spawn.py", line 105, in spawn_main
  File "multiprocessing\spawn.py", line 118, in _main
  File "multiprocessing\process.py", line 258, in _bootstrap
  File "multiprocessing\process.py", line 93, in run
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\joblib\SubprocessorBase.py", line 62, in _subprocess_run
    self.on_initialize(client_dict)
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\mainscripts\Extractor.py", line 73, in on_initialize
    self.rects_extractor = facelib.S3FDExtractor(place_model_on_cpu=place_model_on_cpu)
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\facelib\S3FDExtractor.py", line 170, in __init__
    self.model.build_for_run ([ ( tf.float32, nn.get4Dshape (None,None,3) ) ])
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 154, in build_for_run
    self.run_output = self.__call__(self.run_placeholders)
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__
    return self.forward(*args, **kwargs)
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\facelib\S3FDExtractor.py", line 94, in forward
    x = tf.nn.relu(self.conv1_2(x))
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\LayerBase.py", line 14, in __call__
    return self.forward(*args, **kwargs)
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\DeepFaceLab\core\leras\layers\Conv2D.py", line 87, in forward
    x = tf.pad (x, padding, mode='CONSTANT')
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\util\dispatch.py", line 201, in wrapper
    return target(*args, **kwargs)
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\array_ops.py", line 3422, in pad
    result = gen_array_ops.pad(tensor, paddings, name=name)
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 6484, in pad
    "Pad", input=input, paddings=paddings, name=name)
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 750, in _apply_op_helper
    attrs=attr_protos, op_def=op_def)
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 3536, in _create_op_internal
    op_def=op_def)
  File "E:\BaiduNetdiskDownload\DeepFaceLab_NVIDIA_RTX3000_series\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 1990, in __init__
    self._traceback = tf_stack.extract_stack()


  0%|                                                                                          | 0/655 [00:24<?, ?it/s]
-------------------------
发现的图片数量 Images found:        655
检测到面部数量 Faces detected:      0
-------------------------
Done.
请按任意键继续. . .

如果有知道怎么办的话可以帮助我一下吗，非常感谢

dreamtear

2.0不是不用装CUDA了么

Double2and9

dreamtear 发表于 2021-10-26 00:56
2.0不是不用装CUDA了么

对，应该是不用的，但是无论装不装都无法正常运行

lknet

虚拟内存设大点试试

Double2and9

lknet 发表于 2021-10-26 10:10
虚拟内存设大点试试

我设置成5g，大概多少合适，我感觉不太像是虚拟内存的问题，每次我提取人脸的时候我桌面的其他应用也会崩溃

lknet

Double2and9 发表于 2021-10-26 12:41
我设置成5g，大概多少合适，我感觉不太像是虚拟内存的问题，每次我提取人脸的时候我桌面的其他应用也会崩 ...

50-100G,这东西对虚拟内存有点诡异,没怎么用过,但是少了就是会报错.只管试试吧,反正又不损失啥.

Double2and9

lknet 发表于 2021-10-26 14:27
50-100G,这东西对虚拟内存有点诡异,没怎么用过,但是少了就是会报错.只管试试吧,反正又不损失啥. ...

试了，虽然没有解决，但是感谢你的回复

Double2and9

还有大佬能帮我看看吗

koeikongxu

你这个错误写的是显存溢出了，说明你显卡的显存甚至都不够你当前的程序使用。
先确定你的是什么显卡？一般哪怕旧些的显卡都不太可能出现这个显存溢出的问题。
确定显卡没问题后，看看你下的软件版本是否正确？
软件版本正确的话看看虚拟内存是否足够，虽然上面有人说了调大到50-100G， 但是你还是再次确认下是否已经设置成功了？
因为虚拟内存改完后，还要按一下那个设置按钮，很多人都不知道，或者忘记了。
如果做完以上步骤还是不行，那就进群问问。