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refactor(tensorrt_yolox)!: fix namespace and directory structure #7992

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ktro2828
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@ktro2828 ktro2828 commented Jul 12, 2024

Description

This PR puts headers in the autoware namespace.

Additional works:

  1. Align directory structure to follow the coding guidelines.
  2. Clean unused dependencies LIST

Related links

Parent Issue:

How was this PR tested?

I tested with the following launchers:

  1. ros2 launch autoware_tensorrt_yolox yolox.launch.xml
  2. ros2 launch autoware_tensorrt_yolox yolox_tiny.launch.xml

Notes for reviewers

This PR effects to the other repositories as follows:

Interface changes

None.

Effects on system behavior

None.

@github-actions github-actions bot added type:documentation Creating or refining documentation. (auto-assigned) component:perception Advanced sensor data processing and environment understanding. (auto-assigned) component:launch Launch files, scripts and initialization tools. (auto-assigned) labels Jul 12, 2024
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github-actions bot commented Jul 12, 2024

Thank you for contributing to the Autoware project!

🚧 If your pull request is in progress, switch it to draft mode.

Please ensure:

@ktro2828 ktro2828 force-pushed the refactor/tensorrt-yolox/autoware-prefix branch from de56e97 to f2b368f Compare July 12, 2024 05:27
@github-actions github-actions bot added the type:ci Continuous Integration (CI) processes and testing. (auto-assigned) label Jul 12, 2024
@MasatoSaeki MasatoSaeki changed the title refactor(tesnrorrt_yolox)!: fix namespace and directory structure refactor(tensorrt_yolox)!: fix namespace and directory structure Jul 12, 2024
@ktro2828 ktro2828 force-pushed the refactor/tensorrt-yolox/autoware-prefix branch 2 times, most recently from 5389a66 to f07dad9 Compare July 22, 2024 10:37
@ktro2828
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@badai-nguyen I updated yolox_tiny.param.yaml by f07dad9 because it raises error when I launched yolox_tiny.launch.xml. Could you check this whether it is OK?

@ktro2828 ktro2828 marked this pull request as ready for review July 22, 2024 10:37
@ktro2828 ktro2828 requested a review from MasatoSaeki July 22, 2024 10:37
@ktro2828 ktro2828 added the run:build-and-test-differential Mark to enable build-and-test-differential workflow. (used-by-ci) label Jul 22, 2024
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codecov bot commented Jul 22, 2024

Codecov Report

Attention: Patch coverage is 0% with 8 lines in your changes missing coverage. Please review.

Project coverage is 28.96%. Comparing base (5415162) to head (959d59f).
Report is 3 commits behind head on main.

Files Patch % Lines
..._detector/src/traffic_light_fine_detector_node.cpp 0.00% 5 Missing ⚠️
...ion/autoware_tensorrt_yolox/src/tensorrt_yolox.cpp 0.00% 1 Missing ⚠️
...utoware_tensorrt_yolox/src/tensorrt_yolox_node.cpp 0.00% 1 Missing ⚠️
...rt_yolox/src/yolox_single_image_inference_node.cpp 0.00% 1 Missing ⚠️
Additional details and impacted files
@@            Coverage Diff             @@
##             main    #7992      +/-   ##
==========================================
- Coverage   29.23%   28.96%   -0.27%     
==========================================
  Files        1596     1603       +7     
  Lines      117709   118802    +1093     
  Branches    50709    50867     +158     
==========================================
  Hits        34415    34415              
- Misses      74104    75197    +1093     
  Partials     9190     9190              
Flag Coverage Δ *Carryforward flag
differential 0.00% <0.00%> (?)
total 29.23% <ø> (+<0.01%) ⬆️ Carriedforward from 5415162

*This pull request uses carry forward flags. Click here to find out more.

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@badai-nguyen
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@badai-nguyen I updated yolox_tiny.param.yaml by f07dad9 because it raises error when I launched yolox_tiny.launch.xml. Could you check this whether it is OK?

@ktro2828 Thank you for your fixing.
I confirmed this update fixed the issue and yolox_tiny is successfull to execute

autoware@npc2201009-ubuntu22:~/autoware$ ros2 launch tensorrt_yolox yolox_tiny.launch.xml 
[INFO] [launch]: All log files can be found below /home/autoware/.ros/log/2024-07-22-20-07-01-530387-npc2201009-ubuntu22-92237
[INFO] [launch]: Default logging verbosity is set to INFO
[INFO] [tensorrt_yolox_node_exe-1]: process started with pid [92239]
[tensorrt_yolox_node_exe-1] failed to open 
[tensorrt_yolox_node_exe-1] [I] [TRT] [MemUsageChange] Init CUDA: CPU +563, GPU +0, now: CPU 591, GPU 264 (MiB)
[tensorrt_yolox_node_exe-1] [I] [TRT] [MemUsageChange] Init CUDA: CPU +0, GPU +0, now: CPU 610, GPU 264 (MiB)
[tensorrt_yolox_node_exe-1] [I] [TRT] [MemUsageChange] Init builder kernel library: CPU +434, GPU +102, now: CPU 1044, GPU 366 (MiB)
[tensorrt_yolox_node_exe-1] [I] [TRT] ----------------------------------------------------------------
[tensorrt_yolox_node_exe-1] [I] [TRT] Input filename:   /home/autoware/autoware_data/tensorrt_yolox/yolox-tiny.onnx
[tensorrt_yolox_node_exe-1] [I] [TRT] ONNX IR version:  0.0.8
[tensorrt_yolox_node_exe-1] [I] [TRT] Opset version:    11
[tensorrt_yolox_node_exe-1] [I] [TRT] Producer name:    pytorch
[tensorrt_yolox_node_exe-1] [I] [TRT] Producer version: 1.12.0
[tensorrt_yolox_node_exe-1] [I] [TRT] Domain:           
[tensorrt_yolox_node_exe-1] [I] [TRT] Model version:    0
[tensorrt_yolox_node_exe-1] [I] [TRT] Doc string:       
[tensorrt_yolox_node_exe-1] [I] [TRT] ----------------------------------------------------------------
[tensorrt_yolox_node_exe-1] [W] [TRT] onnx2trt_utils.cpp:369: Your ONNX model has been generated with INT64 weights, while TensorRT does not natively support INT64. Attempting to cast down to INT32.
[tensorrt_yolox_node_exe-1] [W] [TRT] onnx2trt_utils.cpp:395: One or more weights outside the range of INT32 was clamped
[tensorrt_yolox_node_exe-1] [I] [TRT] No importer registered for op: EfficientNMS_TRT. Attempting to import as plugin.
[tensorrt_yolox_node_exe-1] [I] [TRT] Searching for plugin: EfficientNMS_TRT, plugin_version: 1, plugin_namespace: 
[tensorrt_yolox_node_exe-1] [I] [TRT] Successfully created plugin: EfficientNMS_TRT
[tensorrt_yolox_node_exe-1] L9 [conv 3x3 (1) /1] 480x304x12 -> 480x304x24 weights:2592 GFLOPs:0.756449
[tensorrt_yolox_node_exe-1] L12 [conv 3x3 (1) /2] 480x304x24 -> 240x152x48 weights:10368 GFLOPs:0.756449
[tensorrt_yolox_node_exe-1] L15 [conv 1x1 (1) /1] 240x152x48 -> 240x152x24 weights:1152 GFLOPs:0.0840499
[tensorrt_yolox_node_exe-1] L16 [conv 1x1 (1) /1] 240x152x48 -> 240x152x24 weights:1152 GFLOPs:0.0840499
[tensorrt_yolox_node_exe-1] L21 [conv 1x1 (1) /1] 240x152x24 -> 240x152x24 weights:576 GFLOPs:0.042025
[tensorrt_yolox_node_exe-1] L24 [conv 3x3 (1) /1] 240x152x24 -> 240x152x24 weights:5184 GFLOPs:0.378225
[tensorrt_yolox_node_exe-1] L29 [conv 1x1 (1) /1] 240x152x48 -> 240x152x48 weights:2304 GFLOPs:0.1681
[tensorrt_yolox_node_exe-1] L32 [conv 3x3 (1) /2] 240x152x48 -> 120x76x96 weights:41472 GFLOPs:0.756449
[tensorrt_yolox_node_exe-1] L35 [conv 1x1 (1) /1] 120x76x96 -> 120x76x48 weights:4608 GFLOPs:0.0840499
[tensorrt_yolox_node_exe-1] L36 [conv 1x1 (1) /1] 120x76x96 -> 120x76x48 weights:4608 GFLOPs:0.0840499
[tensorrt_yolox_node_exe-1] L41 [conv 1x1 (1) /1] 120x76x48 -> 120x76x48 weights:2304 GFLOPs:0.042025
[tensorrt_yolox_node_exe-1] L44 [conv 3x3 (1) /1] 120x76x48 -> 120x76x48 weights:20736 GFLOPs:0.378225
[tensorrt_yolox_node_exe-1] L48 [conv 1x1 (1) /1] 120x76x48 -> 120x76x48 weights:2304 GFLOPs:0.042025
[tensorrt_yolox_node_exe-1] L51 [conv 3x3 (1) /1] 120x76x48 -> 120x76x48 weights:20736 GFLOPs:0.378225
[tensorrt_yolox_node_exe-1] L55 [conv 1x1 (1) /1] 120x76x48 -> 120x76x48 weights:2304 GFLOPs:0.042025
[tensorrt_yolox_node_exe-1] L58 [conv 3x3 (1) /1] 120x76x48 -> 120x76x48 weights:20736 GFLOPs:0.378225
[tensorrt_yolox_node_exe-1] L63 [conv 1x1 (1) /1] 120x76x96 -> 120x76x96 weights:9216 GFLOPs:0.1681
[tensorrt_yolox_node_exe-1] L66 [conv 3x3 (1) /2] 120x76x96 -> 60x38x192 weights:165888 GFLOPs:0.756449
[tensorrt_yolox_node_exe-1] L69 [conv 1x1 (1) /1] 60x38x192 -> 60x38x96 weights:18432 GFLOPs:0.0840499
[tensorrt_yolox_node_exe-1] L70 [conv 1x1 (1) /1] 60x38x192 -> 60x38x96 weights:18432 GFLOPs:0.0840499
[tensorrt_yolox_node_exe-1] L75 [conv 1x1 (1) /1] 60x38x96 -> 60x38x96 weights:9216 GFLOPs:0.042025
[tensorrt_yolox_node_exe-1] L78 [conv 3x3 (1) /1] 60x38x96 -> 60x38x96 weights:82944 GFLOPs:0.378225
[tensorrt_yolox_node_exe-1] L82 [conv 1x1 (1) /1] 60x38x96 -> 60x38x96 weights:9216 GFLOPs:0.042025
[tensorrt_yolox_node_exe-1] L85 [conv 3x3 (1) /1] 60x38x96 -> 60x38x96 weights:82944 GFLOPs:0.378225
[tensorrt_yolox_node_exe-1] L89 [conv 1x1 (1) /1] 60x38x96 -> 60x38x96 weights:9216 GFLOPs:0.042025
[tensorrt_yolox_node_exe-1] L92 [conv 3x3 (1) /1] 60x38x96 -> 60x38x96 weights:82944 GFLOPs:0.378225
[tensorrt_yolox_node_exe-1] L97 [conv 1x1 (1) /1] 60x38x192 -> 60x38x192 weights:36864 GFLOPs:0.1681
[tensorrt_yolox_node_exe-1] L100 [conv 3x3 (1) /2] 60x38x192 -> 30x19x384 weights:663552 GFLOPs:0.756449
[tensorrt_yolox_node_exe-1] L103 [conv 1x1 (1) /1] 30x19x384 -> 30x19x192 weights:73728 GFLOPs:0.0840499
[tensorrt_yolox_node_exe-1] L106 [max pool 5x5] GFLOPs:0.002736
[tensorrt_yolox_node_exe-1] L107 [max pool 9x9] GFLOPs:0.00886464
[tensorrt_yolox_node_exe-1] L108 [max pool 13x13] GFLOPs:0.0184954
[tensorrt_yolox_node_exe-1] L110 [conv 1x1 (1) /1] 30x19x768 -> 30x19x384 weights:294912 GFLOPs:0.3362
[tensorrt_yolox_node_exe-1] L113 [conv 1x1 (1) /1] 30x19x384 -> 30x19x192 weights:73728 GFLOPs:0.0840499
[tensorrt_yolox_node_exe-1] L114 [conv 1x1 (1) /1] 30x19x384 -> 30x19x192 weights:73728 GFLOPs:0.0840499
[tensorrt_yolox_node_exe-1] L119 [conv 1x1 (1) /1] 30x19x192 -> 30x19x192 weights:36864 GFLOPs:0.042025
[tensorrt_yolox_node_exe-1] L122 [conv 3x3 (1) /1] 30x19x192 -> 30x19x192 weights:331776 GFLOPs:0.378225
[tensorrt_yolox_node_exe-1] L126 [conv 1x1 (1) /1] 30x19x384 -> 30x19x384 weights:147456 GFLOPs:0.1681
[tensorrt_yolox_node_exe-1] L129 [conv 1x1 (1) /1] 30x19x384 -> 30x19x192 weights:73728 GFLOPs:0.0840499
[tensorrt_yolox_node_exe-1] L132 [resize]
[tensorrt_yolox_node_exe-1] L134 [conv 1x1 (1) /1] 60x38x384 -> 60x38x96 weights:36864 GFLOPs:0.1681
[tensorrt_yolox_node_exe-1] L135 [conv 1x1 (1) /1] 60x38x384 -> 60x38x96 weights:36864 GFLOPs:0.1681
[tensorrt_yolox_node_exe-1] L140 [conv 1x1 (1) /1] 60x38x96 -> 60x38x96 weights:9216 GFLOPs:0.042025
[tensorrt_yolox_node_exe-1] L143 [conv 3x3 (1) /1] 60x38x96 -> 60x38x96 weights:82944 GFLOPs:0.378225
[tensorrt_yolox_node_exe-1] L147 [conv 1x1 (1) /1] 60x38x192 -> 60x38x192 weights:36864 GFLOPs:0.1681
[tensorrt_yolox_node_exe-1] L150 [conv 1x1 (1) /1] 60x38x192 -> 60x38x96 weights:18432 GFLOPs:0.0840499
[tensorrt_yolox_node_exe-1] L153 [resize]
[tensorrt_yolox_node_exe-1] L155 [conv 1x1 (1) /1] 120x76x192 -> 120x76x48 weights:9216 GFLOPs:0.1681
[tensorrt_yolox_node_exe-1] L156 [conv 1x1 (1) /1] 120x76x192 -> 120x76x48 weights:9216 GFLOPs:0.1681
[tensorrt_yolox_node_exe-1] L161 [conv 1x1 (1) /1] 120x76x48 -> 120x76x48 weights:2304 GFLOPs:0.042025
[tensorrt_yolox_node_exe-1] L164 [conv 3x3 (1) /1] 120x76x48 -> 120x76x48 weights:20736 GFLOPs:0.378225
[tensorrt_yolox_node_exe-1] L168 [conv 1x1 (1) /1] 120x76x96 -> 120x76x96 weights:9216 GFLOPs:0.1681
[tensorrt_yolox_node_exe-1] L171 [conv 3x3 (1) /2] 120x76x96 -> 60x38x96 weights:82944 GFLOPs:0.378225
[tensorrt_yolox_node_exe-1] L172 [conv 1x1 (1) /1] 120x76x96 -> 120x76x96 weights:9216 GFLOPs:0.1681
[tensorrt_yolox_node_exe-1] L178 [conv 3x3 (1) /1] 120x76x96 -> 120x76x96 weights:82944 GFLOPs:1.5129
[tensorrt_yolox_node_exe-1] L179 [conv 3x3 (1) /1] 120x76x96 -> 120x76x96 weights:82944 GFLOPs:1.5129
[tensorrt_yolox_node_exe-1] L180 [conv 1x1 (1) /1] 60x38x192 -> 60x38x96 weights:18432 GFLOPs:0.0840499
[tensorrt_yolox_node_exe-1] L181 [conv 1x1 (1) /1] 60x38x192 -> 60x38x96 weights:18432 GFLOPs:0.0840499
[tensorrt_yolox_node_exe-1] L190 [conv 3x3 (1) /1] 120x76x96 -> 120x76x96 weights:82944 GFLOPs:1.5129
[tensorrt_yolox_node_exe-1] L191 [conv 3x3 (1) /1] 120x76x96 -> 120x76x96 weights:82944 GFLOPs:1.5129
[tensorrt_yolox_node_exe-1] L192 [conv 1x1 (1) /1] 60x38x96 -> 60x38x96 weights:9216 GFLOPs:0.042025
[tensorrt_yolox_node_exe-1] L199 [conv 1x1 (1) /1] 120x76x96 -> 120x76x8 weights:768 GFLOPs:0.0140083
[tensorrt_yolox_node_exe-1] L200 [conv 1x1 (1) /1] 120x76x96 -> 120x76x4 weights:384 GFLOPs:0.00700416
[tensorrt_yolox_node_exe-1] L201 [conv 1x1 (1) /1] 120x76x96 -> 120x76x1 weights:96 GFLOPs:0.00175104
[tensorrt_yolox_node_exe-1] L202 [conv 3x3 (1) /1] 60x38x96 -> 60x38x96 weights:82944 GFLOPs:0.378225
[tensorrt_yolox_node_exe-1] L210 [conv 1x1 (1) /1] 60x38x192 -> 60x38x192 weights:36864 GFLOPs:0.1681
[tensorrt_yolox_node_exe-1] L213 [conv 3x3 (1) /2] 60x38x192 -> 30x19x192 weights:331776 GFLOPs:0.378225
[tensorrt_yolox_node_exe-1] L214 [conv 1x1 (1) /1] 60x38x192 -> 60x38x96 weights:18432 GFLOPs:0.0840499
[tensorrt_yolox_node_exe-1] L220 [conv 3x3 (1) /1] 60x38x96 -> 60x38x96 weights:82944 GFLOPs:0.378225
[tensorrt_yolox_node_exe-1] L221 [conv 3x3 (1) /1] 60x38x96 -> 60x38x96 weights:82944 GFLOPs:0.378225
[tensorrt_yolox_node_exe-1] L222 [conv 1x1 (1) /1] 30x19x384 -> 30x19x192 weights:73728 GFLOPs:0.0840499
[tensorrt_yolox_node_exe-1] L223 [conv 1x1 (1) /1] 30x19x384 -> 30x19x192 weights:73728 GFLOPs:0.0840499
[tensorrt_yolox_node_exe-1] L232 [conv 3x3 (1) /1] 60x38x96 -> 60x38x96 weights:82944 GFLOPs:0.378225
[tensorrt_yolox_node_exe-1] L233 [conv 3x3 (1) /1] 60x38x96 -> 60x38x96 weights:82944 GFLOPs:0.378225
[tensorrt_yolox_node_exe-1] L234 [conv 1x1 (1) /1] 30x19x192 -> 30x19x192 weights:36864 GFLOPs:0.042025
[tensorrt_yolox_node_exe-1] L241 [conv 1x1 (1) /1] 60x38x96 -> 60x38x8 weights:768 GFLOPs:0.00350208
[tensorrt_yolox_node_exe-1] L242 [conv 1x1 (1) /1] 60x38x96 -> 60x38x4 weights:384 GFLOPs:0.00175104
[tensorrt_yolox_node_exe-1] L243 [conv 1x1 (1) /1] 60x38x96 -> 60x38x1 weights:96 GFLOPs:0.00043776
[tensorrt_yolox_node_exe-1] L244 [conv 3x3 (1) /1] 30x19x192 -> 30x19x192 weights:331776 GFLOPs:0.378225
[tensorrt_yolox_node_exe-1] L252 [conv 1x1 (1) /1] 30x19x384 -> 30x19x384 weights:147456 GFLOPs:0.1681
[tensorrt_yolox_node_exe-1] L255 [conv 1x1 (1) /1] 30x19x384 -> 30x19x96 weights:36864 GFLOPs:0.042025
[tensorrt_yolox_node_exe-1] L258 [conv 3x3 (1) /1] 30x19x96 -> 30x19x96 weights:82944 GFLOPs:0.0945562
[tensorrt_yolox_node_exe-1] L259 [conv 3x3 (1) /1] 30x19x96 -> 30x19x96 weights:82944 GFLOPs:0.0945562
[tensorrt_yolox_node_exe-1] L264 [conv 3x3 (1) /1] 30x19x96 -> 30x19x96 weights:82944 GFLOPs:0.0945562
[tensorrt_yolox_node_exe-1] L265 [conv 3x3 (1) /1] 30x19x96 -> 30x19x96 weights:82944 GFLOPs:0.0945562
[tensorrt_yolox_node_exe-1] L270 [conv 1x1 (1) /1] 30x19x96 -> 30x19x8 weights:768 GFLOPs:0.00087552
[tensorrt_yolox_node_exe-1] L271 [conv 1x1 (1) /1] 30x19x96 -> 30x19x4 weights:384 GFLOPs:0.00043776
[tensorrt_yolox_node_exe-1] L272 [conv 1x1 (1) /1] 30x19x96 -> 30x19x1 weights:96 GFLOPs:0.00010944
[tensorrt_yolox_node_exe-1] Total 21.4927 GFLOPs
[tensorrt_yolox_node_exe-1] Total 5.01754 M params
[tensorrt_yolox_node_exe-1] Loading... "/home/autoware/autoware_data/tensorrt_yolox/yolox-tiny.fp16-batch1.engine"
[tensorrt_yolox_node_exe-1] [I] [TRT] Loaded engine size: 12 MiB
[tensorrt_yolox_node_exe-1] [I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +1325, GPU +346, now: CPU 1980, GPU 622 (MiB)
[tensorrt_yolox_node_exe-1] [I] [TRT] [MemUsageChange] Init cuDNN: CPU +258, GPU +60, now: CPU 2238, GPU 682 (MiB)
[tensorrt_yolox_node_exe-1] [I] [TRT] [MemUsageChange] TensorRT-managed allocation in engine deserialization: CPU +0, GPU +10, now: CPU 0, GPU 10 (MiB)
[tensorrt_yolox_node_exe-1] [I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 2210, GPU 674 (MiB)
[tensorrt_yolox_node_exe-1] [I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 2210, GPU 682 (MiB)
[tensorrt_yolox_node_exe-1] [I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +17, now: CPU 0, GPU 27 (MiB)
[tensorrt_yolox_node_exe-1] [I] [TRT] [MemUsageChange] Init CUDA: CPU +0, GPU +0, now: CPU 2211, GPU 698 (MiB)
[tensorrt_yolox_node_exe-1] [I] [TRT] The profiling verbosity was set to ProfilingVerbosity::kLAYER_NAMES_ONLY when the engine was built, so only the layer names will be returned. Rebuild the engine with ProfilingVerbosity::kDETAILED to get more verbose layer information.

@ktro2828 ktro2828 force-pushed the refactor/tensorrt-yolox/autoware-prefix branch 2 times, most recently from 080c5ae to bbce2bb Compare July 24, 2024 01:01
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I ran object detection and traffic light recognition to make sure the output is correct in local env.

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@ktro2828 @badai-nguyen @MasatoSaeki
I highly appreciate your help with this fixing. LGTM!

@ktro2828 ktro2828 enabled auto-merge (squash) July 25, 2024 01:42
@ktro2828 ktro2828 disabled auto-merge July 25, 2024 01:43
@ktro2828 ktro2828 force-pushed the refactor/tensorrt-yolox/autoware-prefix branch from 98679f8 to 959d59f Compare July 25, 2024 06:04
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@Shin-kyoto @miursh @tzhong518 Could you review this? (I need at least 1 approve from the maintainer of autoware_traffic_light_fine_detector.)

@ktro2828 ktro2828 merged commit 9ab3799 into autowarefoundation:main Jul 25, 2024
28 of 30 checks passed
@ktro2828 ktro2828 deleted the refactor/tensorrt-yolox/autoware-prefix branch July 25, 2024 08:21
chihungtzeng pushed a commit to chihungtzeng/autoware.universe that referenced this pull request Jul 26, 2024
…owarefoundation#7992)

* refactor: add autoware namespace prefix to `tensorrt_yolox`

Signed-off-by: ktro2828 <[email protected]>

* refactor: apply `autoware` namespace to tensorrt_yolox

Signed-off-by: ktro2828 <[email protected]>

* chore: update CODEOWNERS

Signed-off-by: ktro2828 <[email protected]>

* fix: resolve `yolox_tiny` to work

Signed-off-by: ktro2828 <[email protected]>

---------

Signed-off-by: ktro2828 <[email protected]>
a-maumau pushed a commit to a-maumau/autoware.universe that referenced this pull request Jul 28, 2024
…owarefoundation#7992)

* refactor: add autoware namespace prefix to `tensorrt_yolox`

Signed-off-by: ktro2828 <[email protected]>

* refactor: apply `autoware` namespace to tensorrt_yolox

Signed-off-by: ktro2828 <[email protected]>

* chore: update CODEOWNERS

Signed-off-by: ktro2828 <[email protected]>

* fix: resolve `yolox_tiny` to work

Signed-off-by: ktro2828 <[email protected]>

---------

Signed-off-by: ktro2828 <[email protected]>
esteve pushed a commit to esteve/autoware.universe that referenced this pull request Aug 13, 2024
…owarefoundation#7992)

* refactor: add autoware namespace prefix to `tensorrt_yolox`

Signed-off-by: ktro2828 <[email protected]>

* refactor: apply `autoware` namespace to tensorrt_yolox

Signed-off-by: ktro2828 <[email protected]>

* chore: update CODEOWNERS

Signed-off-by: ktro2828 <[email protected]>

* fix: resolve `yolox_tiny` to work

Signed-off-by: ktro2828 <[email protected]>

---------

Signed-off-by: ktro2828 <[email protected]>
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