reeceshearsmith / FCOS_Tensorflow

FCOS: Fully Convolutional One-Stage Object Detection.

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

FCOS: Fully Convolutional One-Stage Object Detection

Note

It can be seen from the tensorboard that the classification ability of the model is particularly poor and the score is relatively low. There may be a problem with the focal loss, and I am still looking for the cause.

Abstract

This is a tensorflow re-implementation of FCOS: Fully Convolutional One-Stage Object Detection, and completed by YangXue.

COCO

Model Backbone Train Schedule GPU Image/GPU FP16 Box AP
FCOS (ours) R50v1 1X 8X GeForce RTX 2080 Ti 2 no Debugging

2

My Development Environment

1、python3.5 (anaconda recommend)
2、cuda9.0
3、opencv(cv2)
4、tfplot
5、tensorflow >= 1.12

Download Model

Pretrain weights

1、Please download resnet50_v1, resnet101_v1 pre-trained models on Imagenet, put it to data/pretrained_weights.
2、Or you can choose to use a better backbone, refer to gluon2TF. Pretrain Model Link, password: q4jg.

Trained weights

Select a configuration file in the folder ($PATH_ROOT/libs/configs/) and copy its contents into cfgs.py, then download the corresponding weights.

Compile

cd $PATH_ROOT/libs/box_utils/cython_utils
python setup.py build_ext --inplace

cd $PATH_ROOT/libs/box_utils/nms
python setup.py build_ext --inplace

Train

1、If you want to train your own data, please note:

(1) Modify parameters (such as CLASS_NUM, DATASET_NAME, VERSION, etc.) in $PATH_ROOT/libs/configs/cfgs.py
(2) Add category information in $PATH_ROOT/libs/label_name_dict/lable_dict.py     
(3) Add data_name to line 76 of $PATH_ROOT/data/io/read_tfrecord.py 

2、make tfrecord

cd $PATH_ROOT/data/io/  
python convert_data_to_tfrecord_coco.py --VOC_dir='/PATH/TO/JSON/FILE/' 
                                        --save_name='train' 
                                        --dataset='coco'

3、multi-gpu train

cd $PATH_ROOT/tools
python multi_gpu_train.py

Eval

cd $PATH_ROOT/tools
python eval_coco.py --eval_data='/PATH/TO/IMAGES/'  
                    --eval_gt='/PATH/TO/TEST/ANNOTATION/'
                    --GPU='0'

Tensorboard

cd $PATH_ROOT/output/summary
tensorboard --logdir=.

3

4

Reference

1、https://github.com/endernewton/tf-faster-rcnn
2、https://github.com/zengarden/light_head_rcnn
3、https://github.com/tensorflow/models/tree/master/research/object_detection
4、https://github.com/CharlesShang/FastMaskRCNN
5、https://github.com/matterport/Mask_RCNN
6、https://github.com/msracver/Deformable-ConvNets
7、https://github.com/tianzhi0549/FCOS

About

FCOS: Fully Convolutional One-Stage Object Detection.

License:MIT License


Languages

Language:Jupyter Notebook 70.2%Language:Python 28.7%Language:C++ 0.5%Language:C 0.4%Language:Cuda 0.2%Language:Makefile 0.0%