文件列表:

CMakeLists.txt (590, 2020-01-02)
calib_img_list.txt (35280, 2020-01-02)
eval_coco.py (6141, 2020-01-02)
example/ (0, 2020-01-02)
example/CMakeLists.txt (346, 2020-01-02)
example/buildEngine.cpp (1248, 2020-01-02)
example/runDet.cpp (2577, 2020-01-02)
img/ (0, 2020-01-02)
img/show.gif (2887521, 2020-01-02)
img/show3.png (1258669, 2020-01-02)
img/show4.png (2176919, 2020-01-02)
include/ (0, 2020-01-02)
include/argparse.h (11007, 2020-01-02)
include/ctdetConfig.h (3520, 2020-01-02)
include/ctdetLayer.h (559, 2020-01-02)
include/ctdetNet.h (2003, 2020-01-02)
include/entroyCalibrator.h (1198, 2020-01-02)
include/python_api.h (543, 2020-01-02)
include/utils.h (5400, 2020-01-02)
model/ (0, 2020-01-02)
model/centerface.onnx (7304528, 2020-01-02)
model/ctdet_helmet.onnx (7949004, 2020-01-02)
onnx-tensorrt/ (0, 2020-01-02)
onnx-tensorrt/CMakeLists.txt (11541, 2020-01-02)
onnx-tensorrt/DCNv2.cpp (6213, 2020-01-02)
onnx-tensorrt/DCNv2.hpp (3990, 2020-01-02)
onnx-tensorrt/Dockerfile (2514, 2020-01-02)
onnx-tensorrt/FancyActivation.cu (4517, 2020-01-02)
onnx-tensorrt/FancyActivation.hpp (3537, 2020-01-02)
onnx-tensorrt/ImporterContext.hpp (4031, 2020-01-02)
onnx-tensorrt/InstanceNormalization.cpp (7416, 2020-01-02)
onnx-tensorrt/InstanceNormalization.hpp (3583, 2020-01-02)
onnx-tensorrt/LICENSE (1146, 2020-01-02)
onnx-tensorrt/ModelImporter.cpp (24582, 2020-01-02)
onnx-tensorrt/ModelImporter.hpp (3607, 2020-01-02)
onnx-tensorrt/NvOnnxParser.cpp (1560, 2020-01-02)
onnx-tensorrt/NvOnnxParser.h (7640, 2020-01-02)
... ...

# TensorRT-CenterNet ### demo (GT 1070) * [ctdet_coco_dla_2x](https://github.com/xingyizhou/CenterNet/blob/master/readme/MODEL_ZOO.md) *  * [centerface](https://github.com/Star-Clouds/centerface) *  * cthelmet *  ### Performance | model | input_size | GPU | mode | inference Time | |----------------|------------|----------|--------|---------------| | [mobilenetv2](https://github.com/CaoWGG/Mobilenetv2-CenterNet) | 512x512 | gtx 1070 |float32 | 3.798ms | | [mobilenetv2](https://github.com/CaoWGG/Mobilenetv2-CenterNet) | 512x512 | gtx 1070 |int8 | 1.75ms | | [mobilenetv2](https://github.com/CaoWGG/Mobilenetv2-CenterNet) | 512x512 | jetson TX2|float16 | 22ms | | [dla34](https://github.com/xingyizhou/CenterNet/blob/master/src/lib/models/networks/pose_dla_dcn.py)| 512x512 | gtx 1070 |float32 | 24ms | | [dla34](https://github.com/xingyizhou/CenterNet/blob/master/src/lib/models/networks/pose_dla_dcn.py)| 512x512 | gtx 1070 |int8 | 19.6ms | | [dla34](https://github.com/xingyizhou/CenterNet/blob/master/src/lib/models/networks/pose_dla_dcn.py)| 512x512 | jetson TX2 |fp32 | 209ms | | [dla34](https://github.com/xingyizhou/CenterNet/blob/master/src/lib/models/networks/pose_dla_dcn.py)| 512x512 | jetson TX2 |fp16 | 186ms | | [dla34v0](https://github.com/xingyizhou/CenterNet/blob/master/src/lib/models/networks/dlav0.py)| 512x512 | gtx 1070 |float32 | 12.6ms | | [dla34v0](https://github.com/xingyizhou/CenterNet/blob/master/src/lib/models/networks/dlav0.py)| 512x512 | gtx 1070 |int8 | 6.76ms | | [dla34v0](https://github.com/xingyizhou/CenterNet/blob/master/src/lib/models/networks/dlav0.py)| 512x512 | jetson TX2 |fp32 | 114ms | | [dla34v0](https://github.com/xingyizhou/CenterNet/blob/master/src/lib/models/networks/dlav0.py)| 512x512 | jetson TX2 |fp16 | 80ms | | [resdcn101](https://github.com/xingyizhou/CenterNet/blob/master/src/lib/models/networks/resnet_dcn.py)| 512x512 | gtx 1070 |float32 | 20.9ms | | [resdcn18](https://github.com/xingyizhou/CenterNet/blob/master/src/lib/models/networks/resnet_dcn.py)| 512x512 | gtx 1070 |float32 | 5.81ms | | [resdcn18](https://github.com/xingyizhou/CenterNet/blob/master/src/lib/models/networks/resnet_dcn.py)| 512x512 | gtx 1070 |int8 | 3.63ms | | [resdcn18](https://github.com/xingyizhou/CenterNet/blob/master/src/lib/models/networks/resnet_dcn.py)| 512x512 | jetson TX2 |fp32 | 54ms | | [resdcn18](https://github.com/xingyizhou/CenterNet/blob/master/src/lib/models/networks/resnet_dcn.py)| 512x512 | jetson TX2 |fp16 | 41ms | 1. support Deform Conv v2. 2. no nms. 3. support fp32 fp16 int8 mode. ### Eval Result |model|GPU|mode|AP^trt/AP^paper|AP^trt₅₀|AP^trt₇₅|AP^trt_S|AP^trt_M|AP^trt_L| |---|---|---|---|---|---|---|---|---| |ctdet_coco_dla_2x|gtx 1070|float32|0.365/0.374|0.543|0.390|0.164|0.398|0.536| |ctdet_coco_dlav0_1x|gtx 1070|float32|0.324/--|0.511|0.343|0.140|0.350|0.476| |ctdet_coco_dlav0_1x|gtx 1070|int8|0.295/--|0.468|0.311|0.123|0.318|0.446| |ctdet_coco_resdcn101|gtx 1070|float32|0.332/0.346|0.516|0.349|0.115|0.367|0.531| |ctdet_coco_resdcn18|gtx 1070|float32|0.277/0.281|0.448|0.286|0.083|0.290|0.454| |ctdet_coco_resdcn18|gtx 1070|int8|0.242/0.281|0.401|0.250|0.061|0.255|0.409| #### notes * cocoval2017 test AP with no augmentation. * input_szie = 512x512 * thresh = 0.01 * maxpool kernel_size = 3 * calib_img_list.txt : random sample 700 images from COCO2017/val2017 ### Enviroments 1. gtx 1070 ``` pytorch 1.0-1.1 ubuntu 1604 TensorRT 5.0 onnx-tensorrt v5.0 cuda 9.0 ``` 2. jetson TX2 ``` jetpack 4.2 ``` ### Models 1. Convert [CenterNet](https://github.com/xingyizhou/centernet) model to onnx. See [here](readme/ctdet2onnx.md) for details. 2. Use [netron](https://github.com/lutzroeder/netron) to observe whether the output of the converted onnx model is (hm, reg, wh) ### Example ```bash git clone https://github.com/CaoWGG/TensorRT-CenterNet.git cd TensorRT-CenterNet mkdir build cd build && cmake .. && make cd .. ##ctdet | config include/ctdetConfig.h ## float32 ./buildEngine -i model/ctdet_coco_dla_2x.onnx -o model/ctdet_coco_dla_2x.engine ./runDet -e model/ctdet_coco_dla_2x.engine -i test.jpg -c test.h264 ##cthelmet | config include/ctdetConfig.h ## flaot32 ./buildEngine -i model/ctdet_helmet.onnx -o model/ctdet_helmet.engine -m 0 ./runDet -e model/ctdet_helmet.engine -i test.jpg -c test.h264 ## int8 ./buildEngine -i model/ctdet_helmet.onnx -o model/ctdet_helmet.engine -m 2 -c calib_img_list.txt ./runDet -e model/ctdet_helmet.engine -i test.jpg -c test.h264 ##centerface | config include/ctdetConfig.h ./buildEngine -i model/centerface.onnx -o model/centerface.engine ./runDet -e model/centerface.engine -i test.jpg -c test.h264 ## run eval_coco.py | conifg your cocodaset and ctdet_coco engine python3 eval_coco.py model/ctdet_coco_dla_2x.engine ``` ### Related projects * [TensorRT-Yolov3](https://github.com/lewes6369/TensorRT-Yolov3) * [onnx-tensorrt](https://github.com/onnx/onnx-tensorrt) * [TensorRT](https://github.com/NVIDIA/TensorRT) * [CenterNet](https://github.com/xingyizhou/centernet) * [centerface](https://github.com/Star-Clouds/centerface) * [netron](https://github.com/lutzroeder/netron) * [cpp-optparse](https://github.com/weisslj/cpp-optparse)

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