C++ object detection module for mxnet-ssd.
Note that python detection module is already included in mxnet-ssd. The goal of this repository is to create a test end for mxnet-ssd with no external dependency.
- Install prerequisites, via
sudo apt-get install cmake git build-essentialsand make sure your c++ compiler support C++11 (g++4.8 or above):g++ --version - Clone this repo recursively:
git clone --recursive https://github.com/zhreshold/mxnet-ssd.cpp - Build all using script:
cd $REPO_ROOT/build
bash ./install.sh
- Install prerequisite:
cmakeandgit(git is optional, highly recommended), they both provide installer online.- Install Visual Studio 2015(verified version).
- Clone this repo:
git clone https://github.com/zhreshold/mxnet-ssd.cpp
git checkout win
# or you can download from github as zip file if git was not installed
# be sure to switch to branch win before download
- Generate VS solution:
cd /path/to/repo/build
./create_sln_vs2015.bat
# the solution will be created in build/vc14/
# open this solution and build, the executable and dlls will be copied to /repo/build if success
Installation guide to be added.
Download the pretrained model and unzip to the same folder as the executable.
By default it's the build directory.
You can put the model any where you like, as long as you run the program with --model /path/to/model_prefix
cd $REPO_ROOT/build
./ssd ../demo/000001.jpg
# save detection image
./ssd ../demo/000004.jpg -o out.jpg
# save detection results to text file
./ssd ../demo/000002.jpg --save-result result.txt
Full usage info: ./ssd -h
Usage: ssd [-hv] [-o <FILE>] [-m <FILE>] [-e <INT>] [--class-map <FILE>] [--width <INT>] [--height <INT>] [-r <FLOAT>] [-g <FLOAT>] [-b <FLOAT>] [-t <FLOAT>] [--gpu <INT>] [--disp-size <INT>] [--save-result <FILE>] <FILE>
Required options:
<FILE> input image
Optional options:
-h, --help print this help and exit
-v, --version print version and exit
-o, --out=FILE output detection result to image
-m, --model=FILE load model prefix(default: deploy_ssd_300)
-e, --epoch=INT load model epoch(default: 1)
--class-map=FILE load classes from text file
--width=INT resize width(default: 300)
--height=INT resize height(default: 300)
-r, --red=FLOAT red mean pixel value(default: 123)
-g, --green=FLOAT green mean pixel value(default: 117)
-b, --blue=FLOAT blue mean pixel value(default: 104)
-t, --thresh=FLOAT visualize threshold(default: 0.5)
--gpu=INT gpu id to detect with, default use cpu(default: -1)
--disp-size=INT display size, -1 to disable display(default: 640)
--save-result=FILE save result in text file