/Yolact_ROS

Primary LanguagePython

Yolact_ROS

Integrates Yolact with ROS

Requirement

  • ROS(Kinetic)
  • GPU supporting CUDA

Installation

  • Set up a Python3 environment.
  • Install Pytorch 1.0.1 (or higher) and TorchVision.
  • Install some other packages: 
    # Cython needs to be installed before pycocotools
pip install cython
pip install opencv-python pillow pycocotools matplotlib
  • Clone this repository and enter it: 
    git clone https://github.com/dbolya/yolact.git
cd yolact
  • If you'd like to train YOLACT, download the COCO dataset and the 2014/2017 annotations. Note that this script will take a while and dump 21gb of files into ./data/coco. 
    sh data/scripts/COCO.sh
  • If you'd like to evaluate YOLACT on test-dev, download test-dev with this script. 
    sh data/scripts/COCO_test.sh

Weight

Image Size Backbone FPS mAP Weights
550 Resnet50-FPN 42.5 28.2 yolact_resnet50_54_800000.pth Mirror
550 Darknet53-FPN 40.0 28.7 yolact_darknet53_54_800000.pth Mirror
550 Resnet101-FPN 33.0 29.8 yolact_base_54_800000.pth Mirror
700 Resnet101-FPN 23.6 31.2 yolact_im700_54_800000.pth Mirror

To evalute the model, put the corresponding weights file in the ./weights directory and run one of the following commands.

webcam demo

rosrun test eval.py --trained_model={weight 주소} --score_threshold=0.3 --top_k=100 --video_multiframe=2 --video=0

webcam publish

rosrun test test_sub.py

rosrun test eval.py --trained_model={weight 주소} --score_threshold=0.3 --top_k=100 --video_multiframe=2 --video=0