文件名称：trt_pose_trt.zip
文件大小：122.22MB
文件格式：ZIP
更新时间：2023-04-08 05:08:28
trt_pose
https://github.com/NVIDIA-AI-IOT/trt_pose This project features multi-instance pose estimation accelerated by NVIDIA TensorRT. It is ideal for applications where low latency is necessary. It includes Training scripts to train on any keypoint task data in MSCOCO format A collection of models that may be easily optimized with TensorRT using torch2trt This project can be used easily for the task of human pose estimation, or extended for something new. contains convert pytorch model into tensorrt model
【文件预览】：
trt
----parse_objects.py(1KB)
----trt_pose()
--------parse_objects.py(1KB)
--------models()
--------draw_objects.py(1KB)
--------coco.py(16KB)
--------__init__.pyc(134B)
--------train.py(6KB)
--------plugins()
--------__pycache__()
--------__init__.py(12B)
--------plugins.cpython-35m-x86_64-linux-gnu.so(11.6MB)
--------utils()
----draw_objects.py(2KB)
----human_pose.json(510B)
----1.jpg(20KB)
----live_demo.ipynb(11KB)
----test.py(193B)
----__pycache__()
--------parse_objects.cpython-35.pyc(1KB)
--------trt_pose_module.cpython-35.pyc(13KB)
--------trt_pose_module_drawing.cpython-36.pyc(5KB)
--------parse_objects.cpython-36.pyc(1KB)
--------pose_module_drawing.cpython-35.pyc(3KB)
--------trt_pose_module_drawing.cpython-35.pyc(6KB)
--------draw_objects.cpython-35.pyc(2KB)
----download_coco.sh(182B)
----demo.py(4KB)
----build_trt.py(4KB)
----trt_pose_module_drawing.py(5KB)
----experiments()
--------resnet18_baseline_att_368x368_A.json(2KB)
--------densenet121_baseline_att_320x320_A.json(2KB)
--------mnasnet0_5_baseline_att_224x224_keepAR.json(2KB)
--------densenet169_baseline_att_368x368_A.json(2KB)
--------densenet121_baseline_att_256x256_A.json(2KB)
--------resnet18_baseline_att_224x224_A.json(2KB)
--------resnet50_baseline_att_384x384_A.json(2KB)
--------densenet121_baseline_att_256x256_B.json(2KB)
--------resnet18_baseline_att_224x224_B.json(2KB)
--------densenet169_baseline_att_256x256_A.json(2KB)
--------densenet121_baseline_att_224x224_A.json(2KB)
--------resnet18_baseline_att_256x256_A.json(2KB)
--------dla34up_pose_256x256_A.json(2KB)
--------densenet121_baseline_att_224x224_B.json(2KB)
--------resnet50_baseline_att_256x256_A.json(2KB)
--------resnet18_baseline_att_224x224_keepAR.json(2KB)
--------resnet50_baseline_att_368x368_A.json(2KB)
----eval.ipynb(12KB)
----trt_pose_module.py(18KB)
----preprocess_coco_person.py(2KB)
----2.mp4(118.03MB)