Use TensorRT API to implement Caffe-SSD, SSD(channel pruning), Mobilenet-SSD
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I hope my code will help you learn and understand the TensorRT API
better. It’s welcome to discuss the deep learning algorithm, model
optimization, TensorRT API and so on, and learn from each other.
#Introduction:
The original Caffe-SSD can run 3-5fps on my jetson tx2.
TensorRT-SSD can run 8-10fps on my jetson tx2.
TensorRT-SSD(channel pruning) can run 16-17fps on my jetson tx2.
TensorRT-Mobilenet-SSD can run 40-43fps on my jetson tx2(it‘s cool!), and run 100+fps on gtx1060.
#Requirements:
TensorRT3.0
Cuda8.0 or Cuda9.0
OpenCV
The code will be published shortly...
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In the Other_layer_tensorRT folder, there are the implementation of some other layers with TensorRT api, including:
PReLU
Continuously updated...
2018/02/06, update detection_out layer
2018/03/07, add the common.cpp file
2018/04/21, TensorFlow 1.7 wheel with JetPack 3.2.(enable TensorRT support)