sense_classification

中文版本

Introduction

RSCUP: 遥感图像场景分类

This repo is organized as follows:

sense_classification/
    |->examples
    |->models
    |->prepare_data
    |->data
    |   |->rssrai_sense_cls
    |   |   |->train
    |   |   |->val
    |   |   |->test
    |   |->tf_records
    |   |->train_list
    |->ckpt
    |->tools

Requirements

1. tensorflow-gpu==1.12.0 (I only test on tensorflow 1.12.0)
2. python==3.4.3
3. numpy
4. easydict
5. opencv==3.4.1
6. Python packages might missing. pls fix it according to the error message.

Installation, Prepare data, Training, Val, Generate submit

Installation

1. Clone the sense_classification repository, and we'll call the directory that you cloned sense_classification as ${sense_classification_ROOT}.

git clone https://github.com/vicwer/sense_classification.git

Prepare data

data should be organized as follows:

data/
    |->rssrai_sense_cls
    |   |->train
    |   |->val
    |   |->test
    |   |->ClsName2id.txt
    |->train_list/train.txt
    |->tf_records

1. Download dataset and unzip: train.zip, val.zip, test.zip, ClsName2id.txt

2. Generate tf_records:

cd tools
python3 img_encode.py

Training

I provide common used config.py in ${sense_classification_ROOT}, which can set hyperparameters.

e.g.

cd ${sense_classification_ROOT}
vim config.py
cfg.train.num_gpus = {your gpu nums}
etc.

cd ${sense_classification_ROOT}/examples/
python3 multi_gpus_train.py

Val

cd ${sense_classification_ROOT}/examples/
python3 accuracy.py

Generate submit

cd ${sense_classification_ROOT}/examples/
python3 submit.py

Result:

Val: 0.908+ Test: 0.90509