shukkkur
commented
2 years ago Hi @azuryl! Similar to comment #2, running without GPU is not supported. Try using Google Colab if you machine doesn't support GPU, the instructions are in README.md. If this is not the case, make sure tensorflow-gpu is correctly installed.
Let me know how it goes!
2021-10-26 22:09:37.627546: W tensorflow/core/util/tensor_slice_reader.cc:95] Could not open WeightsTracknet/model.1: Data loss: not an sstable (bad magic number): perhaps your file is in a different file format and you need to use a different restore operator? OpenCV: FFMPEG: tag 0x44495658/'XVID' is not supported with codec id 12 and format 'mp4 / MP4 (MPEG-4 Part 14)' OpenCV: FFMPEG: fallback to use tag 0x7634706d/'mp4v' Using device cuda Detecting the court and the players... /home/azuryl/anaconda3/envs/tennistrack/lib/python3.8/site-packages/torch/nn/functional.py:718: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at /opt/conda/conda-bld/pytorch_1623448234945/work/c10/core/TensorImpl.h:1156.) return torch.max_pool2d(input, kernel_size, stride, padding, dilation, ceil_mode) BOXES [array([452.16757, 735.3489 , 572.748 , 954.95917], dtype=float32)] BIGGEST [452. 735. 573. 955.] Finished! Tracking the ball: 0.0 2021-10-26 22:14:17.447722: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:185] None of the MLIR Optimization Passes are enabled (registered 2) Traceback (most recent call last): File "predict_video.py", line 155, in
pr = m.predict(np.array([X]))[0]
File "/home/azuryl/anaconda3/envs/tennistrack/lib/python3.8/site-packages/keras/engine/training.py", line 1751, in predict
tmp_batch_outputs = self.predict_function(iterator)
File "/home/azuryl/anaconda3/envs/tennistrack/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 885, in call
result = self._call(*args, **kwds)
File "/home/azuryl/anaconda3/envs/tennistrack/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 956, in _call
return self._concrete_stateful_fn._call_flat(
File "/home/azuryl/anaconda3/envs/tennistrack/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 1963, in _call_flat
return self._build_call_outputs(self._inference_function.call(
File "/home/azuryl/anaconda3/envs/tennistrack/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 591, in call
outputs = execute.execute(
File "/home/azuryl/anaconda3/envs/tennistrack/lib/python3.8/site-packages/tensorflow/python/eager/execute.py", line 59, in quick_execute
tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
tensorflow.python.framework.errors_impl.InvalidArgumentError: Default MaxPoolingOp only supports NHWC on device type CPU
[[node model_1/max_pooling2d/MaxPool (defined at predict_video.py:155) ]] [Op:__inference_predict_function_1776]
Function call stack: predict_function