/Pelee

Pelee: A Real-Time Object Detection System on Mobile Devices

Primary LanguagePythonApache License 2.0Apache-2.0

Pelee: A Real-Time Object Detection System on Mobile Devices

This repository contains the code for the following paper.

Pelee: A Real-Time Object Detection System on Mobile Devices (ICLR 2018 workshop track)

The code is based on the SSD framework.

Citation

If you find this work useful in your research, please consider citing:

@article{wang2018pelee,
  title={Pelee: A Real-Time Object Detection System on Mobile Devices},
  author={Wang, Robert J and Li, Xiang and Ao, Shuang and Ling, Charles X},
  journal={arXiv preprint arXiv:1804.06882},
  year={2018}
}

Results on VOC 2007

The table below shows the results on PASCAL VOC 2007 test.

Method mAP (%) FPS (Intel i7) FPS (iPhone 6s) FPS (iPhone 8) # parameters
YOLOv2-288 69.0 1.0 - - 58.0M
DSOD300_smallest 73.6 1.3 - - 5.9M
Tiny-YOLOv2 57.1 2.4 9.3 23.8 15.9M
SSD+MobileNet 68.0 6.1 16.1 22.8 5.8M
Pelee 70.9 6.7 17.1 23.6 5.4M
Method 07+12 07+12+coco
SSD300 77.2 81.2
SSD+MobileNet 68 72.7
Pelee 70.9 76.4

Results on COCO

The table below shows the results on COCO test-dev2015.

Method mAP@[0.5:0.95] mAP@0.5 mAP@0.75 Computational Cost (MACs) # parameters
SSD300 25.1 43.1 25.8 34,360 M 34.30 M
YOLOv2-416 21.6 44.0 19.2 17,500 M 67.43 M
SSD+MobileNet 18.8 - - 1,200 M 6.80 M
Pelee 22.4 38.3 22.9 1,290 M 5.98 M

Preparation

  1. Install SSD (https://github.com/weiliu89/caffe/tree/ssd) following the instructions there, including: (1) Install SSD caffe; (2) Download PASCAL VOC 2007 and 2012 datasets; and (3) Create LMDB file. Make sure you can run it without any errors.

  2. Download the pretrained PeleeNet model. By default, we assume the model is stored in $CAFFE_ROOT/models/

  3. Clone this repository and create a soft link to $CAFFE_ROOT/examples

git clone https://github.com/Robert-JunWang/Pelee.git
ln -sf `pwd`/Pelee $CAFFE_ROOT/examples/pelee

Training & Testing

  • Train a Pelee model on VOC 07+12:

    cd $CAFFE_ROOT
python examples/pelee/train_voc.py

  • Evaluate the model:

    cd $CAFFE_ROOT
python examples/pelee/eval_voc.py

Models