error

[loboere]

Downloading: "https://www.adrianbulat.com/downloads/python-fan/2DFAN4-11f355bf06.pth.tar" to /root/.cache/torch/hub/checkpoints/2DFAN4-11f355bf06.pth.tar
100% 91.2M/91.2M [00:05<00:00, 19.1MB/s]
WARNING: Logging before flag parsing goes to stderr.
W1124 05:18:17.878163 140281471424384 module_wrapper.py:139] From /content/style_avatar/deep_3drecon/utils.py:68: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.

W1124 05:18:17.879213 140281471424384 module_wrapper.py:139] From /content/style_avatar/deep_3drecon/utils.py:14: The name tf.gfile.GFile is deprecated. Please use tf.io.gfile.GFile instead.

W1124 05:18:17.879425 140281471424384 module_wrapper.py:139] From /content/style_avatar/deep_3drecon/utils.py:15: The name tf.GraphDef is deprecated. Please use tf.compat.v1.GraphDef instead.

W1124 05:18:18.932533 140281471424384 module_wrapper.py:139] From /content/style_avatar/deep_3drecon/face_decoder.py:129: The name tf.cross is deprecated. Please use tf.linalg.cross instead.

W1124 05:18:18.933541 140281471424384 deprecation.py:506] From /content/style_avatar/deep_3drecon/face_decoder.py:131: calling l2_normalize (from tensorflow.python.ops.nn_impl) with dim is deprecated and will be removed in a future version.
Instructions for updating:
dim is deprecated, use axis instead
W1124 05:18:19.503320 140281471424384 deprecation.py:323] From /content/style_avatar/deep_3drecon/mesh_renderer/mesh_renderer.py:165: where (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.where in 2.0, which has the same broadcast rule as np.where
W1124 05:18:19.969749 140281471424384 module_wrapper.py:139] From /content/style_avatar/deep_3drecon/utils.py:85: The name tf.GPUOptions is deprecated. Please use tf.compat.v1.GPUOptions instead.

W1124 05:18:19.970036 140281471424384 module_wrapper.py:139] From /content/style_avatar/deep_3drecon/utils.py:86: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.

W1124 05:18:19.970237 140281471424384 module_wrapper.py:139] From /content/style_avatar/deep_3drecon/utils.py:86: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.

2021-11-24 05:18:19.983109: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2299995000 Hz
2021-11-24 05:18:19.983801: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x5565daed5d40 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2021-11-24 05:18:19.983842: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2021-11-24 05:18:19.987771: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2021-11-24 05:18:19.992980: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-11-24 05:18:19.993832: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x5565daed5b80 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2021-11-24 05:18:19.993868: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Tesla K80, Compute Capability 3.7
2021-11-24 05:18:19.994966: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-11-24 05:18:19.995591: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1639] Found device 0 with properties: 
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:00:04.0
2021-11-24 05:18:20.022505: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2021-11-24 05:18:20.211194: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2021-11-24 05:18:20.237375: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2021-11-24 05:18:20.260865: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2021-11-24 05:18:20.509169: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2021-11-24 05:18:20.528118: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2021-11-24 05:18:20.896984: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2021-11-24 05:18:20.897234: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-11-24 05:18:20.898117: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-11-24 05:18:20.898852: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1767] Adding visible gpu devices: 0
2021-11-24 05:18:20.902326: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2021-11-24 05:18:20.903938: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1180] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-11-24 05:18:20.903995: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1186]      0 
2021-11-24 05:18:20.904026: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1199] 0:   N 
2021-11-24 05:18:20.905518: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-11-24 05:18:20.906512: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-11-24 05:18:20.907194: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1325] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10199 MB memory) -> physical GPU (device: 0, name: Tesla K80, pci bus id: 0000:00:04.0, compute capability: 3.7)
2021-11-24 05:18:24.483044: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-11-24 05:18:24.483631: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1639] Found device 0 with properties: 
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:00:04.0
2021-11-24 05:18:24.483758: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2021-11-24 05:18:24.483833: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2021-11-24 05:18:24.483898: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2021-11-24 05:18:24.483972: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2021-11-24 05:18:24.484039: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2021-11-24 05:18:24.484101: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2021-11-24 05:18:24.484165: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2021-11-24 05:18:24.484282: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-11-24 05:18:24.484860: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-11-24 05:18:24.485335: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1767] Adding visible gpu devices: 0
2021-11-24 05:18:24.486420: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-11-24 05:18:24.486925: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1639] Found device 0 with properties: 
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:00:04.0
2021-11-24 05:18:24.487000: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2021-11-24 05:18:24.487065: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2021-11-24 05:18:24.487127: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2021-11-24 05:18:24.487192: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2021-11-24 05:18:24.487254: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2021-11-24 05:18:24.487315: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2021-11-24 05:18:24.487376: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2021-11-24 05:18:24.487489: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-11-24 05:18:24.488060: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-11-24 05:18:24.488592: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1767] Adding visible gpu devices: 0
2021-11-24 05:18:24.488651: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1180] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-11-24 05:18:24.488687: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1186]      0 
2021-11-24 05:18:24.488714: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1199] 0:   N 
2021-11-24 05:18:24.488897: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-11-24 05:18:24.489464: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-11-24 05:18:24.489974: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1325] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10199 MB memory) -> physical GPU (device: 0, name: Tesla K80, pci bus id: 0000:00:04.0, compute capability: 3.7)
/content/style_avatar/align_img.py:21: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  k,_,_,_ = np.linalg.lstsq(A,b)
/content/style_avatar/align_img.py:97: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray
  trans_params = np.array([w0,h0,102.0/s,t[0],t[1]])
2021-11-24 05:18:27.965252: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2021-11-24 05:18:30.431787: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2021-11-24 05:18:32.221454: I tensorflow/stream_executor/cuda/cuda_driver.cc:831] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2021-11-24 05:18:32.233011: I tensorflow/stream_executor/cuda/cuda_driver.cc:831] failed to allocate 3.60G (3865470464 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2021-11-24 05:18:32.244708: I tensorflow/stream_executor/cuda/cuda_driver.cc:831] failed to allocate 3.24G (3478923264 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2021-11-24 05:18:32.255462: I tensorflow/stream_executor/cuda/cuda_driver.cc:831] failed to allocate 2.92G (3131030784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2021-11-24 05:18:32.268217: I tensorflow/stream_executor/cuda/cuda_driver.cc:831] failed to allocate 2.62G (2817927680 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2021-11-24 05:18:32.280419: I tensorflow/stream_executor/cuda/cuda_driver.cc:831] failed to allocate 2.36G (2536134912 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2021-11-24 05:18:32.280486: W tensorflow/core/common_runtime/bfc_allocator.cc:305] Garbage collection: deallocate free memory regions (i.e., allocations) so that we can re-allocate a larger region to avoid OOM due to memory fragmentation. If you see this message frequently, you are running near the threshold of the available device memory and re-allocation may incur great performance overhead. You may try smaller batch sizes to observe the performance impact. Set TF_ENABLE_GPU_GARBAGE_COLLECTION=false if you'd like to disable this feature.
2021-11-24 05:18:34.034494: W tensorflow/core/framework/cpu_allocator_impl.cc:81] Allocation of 75497472 exceeds 10% of system memory.
rm: cannot remove '/content/outt/*.png': No such file or directory
2021-11-24 05:18:35.471827: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-11-24 05:18:35.472222: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1639] Found device 0 with properties: 
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:00:04.0
2021-11-24 05:18:35.472343: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2021-11-24 05:18:35.472443: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2021-11-24 05:18:35.472528: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2021-11-24 05:18:35.472621: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2021-11-24 05:18:35.472738: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2021-11-24 05:18:35.472816: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2021-11-24 05:18:35.472911: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2021-11-24 05:18:35.473096: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-11-24 05:18:35.476636: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-11-24 05:18:35.477987: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1767] Adding visible gpu devices: 0
2021-11-24 05:18:35.479073: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1180] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-11-24 05:18:35.479127: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1186]      0 
2021-11-24 05:18:35.479157: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1199] 0:   N 
2021-11-24 05:18:35.479720: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-11-24 05:18:35.480132: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-11-24 05:18:35.480518: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1325] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10199 MB memory) -> physical GPU (device: 0, name: Tesla K80, pci bus id: 0000:00:04.0, compute capability: 3.7)
2021-11-24 05:18:36.163937: W tensorflow/core/framework/cpu_allocator_impl.cc:81] Allocation of 57802752 exceeds 10% of system memory.
FATAL Flags parsing error: Unknown command line flag 'in_img'
Pass --helpshort or --helpfull to see help on flags.

[wuhaozhe]

hi, what's your running command? log shows that you have error command of 'in_img'

[loboere]

!python demo.py --in_img /content/9.jpg --in_audio /content/acapella_res.wav --output_path /content/out

[wuhaozhe]

hi, can you run python demo.py without specifying in_img, in_audio and output_path?

[islamikoo]

excuse me, I'm facing the same error did you solve it?
I tried running python demo.py without specifying in_img, in_audio and output_path
but I get No such file or directory: 'output'
so what's wrong?

[wuhaozhe]

hi, you can makedir output?

[islamikoo]

this solved it but still got another error
I think something makes problems when trying to run the system on google colab

[wuhaozhe]

Well, maybe that's because i use some precompiled lib of https://github.com/microsoft/Deep3DFaceReconstruction