google/automl-video-ondevice

automl-video-ondevice's Issues

Cant run Jetson example - TRT segment could not be empty

I am trying to run the Jetson example with my webcam (which I have verified is in /dev/video2), and I get the following error:

python3 examples/jetson_camera_demo.py --video_device 2

`Loading data/traffic_model_tftrt.pb with data/traffic_label_map.pbtxt labels.
Loading: data/traffic_model_tftrt.pb <Format.TENSORFLOW> data/traffic_label_map.pbtxt
2020-08-16 08:29:02.565609: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.2
WARNING:tensorflow:Deprecation warnings have been disabled. Set TF_ENABLE_DEPRECATION_WARNINGS=1 to re-enable them.
2020-08-16 08:29:08.936702: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libnvinfer.so.7
2020-08-16 08:29:08.940730: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libnvinfer_plugin.so.7
WARNING:tensorflow:
The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:
  * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
  * https://github.com/tensorflow/addons
  * https://github.com/tensorflow/io (for I/O related ops)
If you depend on functionality not listed there, please file an issue.

Loading an LSTM model.
2020-08-16 08:29:09.942331: W tensorflow/core/platform/profile_utils/cpu_utils.cc:98] Failed to find bogomips in /proc/cpuinfo; cannot determine CPU frequency
2020-08-16 08:29:09.943629: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x2babe200 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-08-16 08:29:09.943751: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2020-08-16 08:29:09.948270: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcuda.so.1
2020-08-16 08:29:10.035637: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:950] ARM64 does not support NUMA - returning NUMA node zero
2020-08-16 08:29:10.036192: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x27c586a0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2020-08-16 08:29:10.036301: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Xavier, Compute Capability 7.2
2020-08-16 08:29:10.036969: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:950] ARM64 does not support NUMA - returning NUMA node zero
2020-08-16 08:29:10.037136: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1639] Found device 0 with properties: 
name: Xavier major: 7 minor: 2 memoryClockRate(GHz): 1.109
pciBusID: 0000:00:00.0
2020-08-16 08:29:10.037360: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.2
2020-08-16 08:29:10.037572: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcublas.so.10
2020-08-16 08:29:10.037721: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcufft.so.10
2020-08-16 08:29:10.038833: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcurand.so.10
2020-08-16 08:29:10.042316: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcusolver.so.10
2020-08-16 08:29:10.044700: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcusparse.so.10
2020-08-16 08:29:10.044913: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudnn.so.8
2020-08-16 08:29:10.045253: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:950] ARM64 does not support NUMA - returning NUMA node zero
2020-08-16 08:29:10.045603: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:950] ARM64 does not support NUMA - returning NUMA node zero
2020-08-16 08:29:10.045736: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1767] Adding visible gpu devices: 0
2020-08-16 08:29:10.045955: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.2
2020-08-16 08:29:12.579091: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1180] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-08-16 08:29:12.579227: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1186]      0 
2020-08-16 08:29:12.579295: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1199] 0:   N 
2020-08-16 08:29:12.579898: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:950] ARM64 does not support NUMA - returning NUMA node zero
2020-08-16 08:29:12.580393: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:950] ARM64 does not support NUMA - returning NUMA node zero
2020-08-16 08:29:12.580673: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1325] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 767 MB memory) -> physical GPU (device: 0, name: Xavier, pci bus id: 0000:00:00.0, compute capability: 7.2)
[ WARN:0] global /tmp/build_opencv/opencv/modules/videoio/src/cap_gstreamer.cpp (935) open OpenCV | GStreamer warning: Cannot query video position: status=0, value=-1, duration=-1
2020-08-16 08:29:13.931597: E tensorflow/core/common_runtime/executor.cc:648] Executor failed to create kernel. Invalid argument: The TF function for the TRT segment could not be empty
	 [[{{node import/TRTEngineOp_0}}]]
Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1365, in _do_call
    return fn(*args)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1350, in _run_fn
    target_list, run_metadata)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1443, in _call_tf_sessionrun
    run_metadata)
tensorflow.python.framework.errors_impl.InvalidArgumentError: The TF function for the TRT segment could not be empty
	 [[{{node import/TRTEngineOp_0}}]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "examples/jetson_camera_demo.py", line 123, in <module>
    main()
  File "examples/jetson_camera_demo.py", line 102, in main
    if engine.run(timestamp, resized_frame, annotations):
  File "/home/gbenel/automl-video-ondevice/automl_video_ondevice/object_tracking/tf_object_detection.py", line 105, in run
    session_return = self.session.run(self._output_nodes, feed_dict=feed_dict)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 956, in run
    run_metadata_ptr)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1180, in _run
    feed_dict_tensor, options, run_metadata)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1359, in _do_run
    run_metadata)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1384, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: The TF function for the TRT segment could not be empty
	 [[node import/TRTEngineOp_0 (defined at /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py:1748) ]]

Original stack trace for 'import/TRTEngineOp_0':
  File "examples/jetson_camera_demo.py", line 123, in <module>
    main()
  File "examples/jetson_camera_demo.py", line 68, in main
    engine = vot.load(args.model, args.labels, config)
  File "/home/gbenel/automl-video-ondevice/automl_video_ondevice/object_tracking/__init__.py", line 68, in load
    config)
  File "/home/gbenel/automl-video-ondevice/automl_video_ondevice/object_tracking/tf_object_detection.py", line 43, in __init__
    self._load_frozen_graph(frozen_graph_path)
  File "/home/gbenel/automl-video-ondevice/automl_video_ondevice/object_tracking/tf_object_detection.py", line 66, in _load_frozen_graph
    if self._is_lstm else []))
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/util/deprecation.py", line 513, in new_func
    return func(*args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/importer.py", line 405, in import_graph_def
    producer_op_list=producer_op_list)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/importer.py", line 517, in _import_graph_def_internal
    _ProcessNewOps(graph)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/importer.py", line 243, in _ProcessNewOps
    for new_op in graph._add_new_tf_operations(compute_devices=False):  # pylint: disable=protected-access
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py", line 3561, in _add_new_tf_operations
    for c_op in c_api_util.new_tf_operations(self)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py", line 3561, in <listcomp>
    for c_op in c_api_util.new_tf_operations(self)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py", line 3451, in _create_op_from_tf_operation
    ret = Operation(c_op, self)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py", line 1748, in __init__
    self._traceback = tf_stack.extract_stack()
`

Security Policy violation Binary Artifacts

This issue was automatically created by Allstar.

Security Policy Violation
Project is out of compliance with Binary Artifacts policy: binaries present in source code

Rule Description
Binary Artifacts are an increased security risk in your repository. Binary artifacts cannot be reviewed, allowing the introduction of possibly obsolete or maliciously subverted executables. For more information see the Security Scorecards Documentation for Binary Artifacts.

Remediation Steps
To remediate, remove the generated executable artifacts from the repository.

Artifacts Found

• automl_video_ondevice/object_tracking/mediapipe_tracker/aarch64/mediapipe_tracker.so

Additional Information
This policy is drawn from Security Scorecards, which is a tool that scores a project's adherence to security best practices. You may wish to run a Scorecards scan directly on this repository for more details.

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This issue will auto resolve when the policy is in compliance.

Issue created by Allstar. See https://github.com/ossf/allstar/ for more information. For questions specific to the repository, please contact the owner or maintainer.

How to Build mediapipe_tracker.so

hi , thanks you for your this project, it is useful for me. Could you please tell how to Build mediapipe_tracker.so. Because I want to build other modules in the mediapipe.

Thank you very much.

RuntimeError: The basic tracker is not publicly available yet,

Trying to use the object tracker in coral_camera_demo.py (--use_tracker=True) and I get the error:

'''
RuntimeError: The basic tracker is not publicly available yet, please reach out to repo maintainers for early access. If this error persists, it may mean your CPU architecture is not yet supported.
'''

Notes - this is with Raspberry Pi 4 and Coral USB