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README.md

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 (NeurIPS 2018)

The code is based on the SSD framework.

Citation

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


@incollection{NIPS2018_7466,
title = {Pelee: A Real-Time Object Detection System on Mobile Devices},
author = {Wang, Robert J and Li, Xiang and Ling, Charles X},
booktitle = {Advances in Neural Information Processing Systems 31},
editor = {S. Bengio and H. Wallach and H. Larochelle and K. Grauman and N. Cesa-Bianchi and R. Garnett},
pages = {1967--1976},
year = {2018},
publisher = {Curran Associates, Inc.},
url = {http://papers.nips.cc/paper/7466-pelee-a-real-time-object-detection-system-on-mobile-devices.pdf}
}

Results on VOC 2007

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

Method mAP (%) FPS (Intel i7) FPS (NVIDIA TX2) 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 - 23.8 15.9M
SSD+MobileNet 68.0 6.1 82 22.8 5.8M
Pelee 70.9 6.7 125 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 FPS (NVIDIA TX2) # parameters
SSD300 25.1 43.1 25.8 - 34.30 M
YOLOv2-416 21.6 44.0 19.2 32.2 67.43 M
YOLOv3-320 - 51.5 - 21.5 67.43 M
TinyYOLOv3-416 - 33.1 - 105 12.3 M
SSD+MobileNet-300 18.8 - - 80 6.80 M
SSDLite+MobileNet V2-320 22 - - 61 6.80 M
Pelee-304 22.4 38.3 22.9 120 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

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