spytensor / Detect_steel_bar
CCFDF AI 数钢筋大赛
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提醒
由于个人版本修改较多，记不清哪个配置可以达到线上0.97。
声明
由于竞赛平台协议有规定，未经许可暂不能公开数据集，非常抱歉。
可修改的地方:
- dataloader.py 中Resize函数的图像尺寸，越大效果越好。
- main.py 中的模型 depth ，越大效果越好。
- 更有效的办法就是做数据扩充，增加数据量。
1. 比赛地址
2. 依赖
pytorch0.4.1,opencv-python,skimage
3. 使用方法
step0: 安装
git clone https://github.com/spytensor/detect_steel_bar.git
detect_steel_bar/retinanet/lib/
bash build.sh
cd ../../
step1: 下载数据解压后，将训练数据和测试数据放到 data/images/下，效果如下：
- data/
- images/
train/
test/
step2: 将训练标签文件 train_labels.csv 复制到 data/ 下，效果如下：
- data/
train_labels.csv
step3: 将官方提高数据转变成可供Retinanet训练格式
cd data
python convert.py
cd ..
step4: 训练
python retinanet/main.py
step5: 预测
python retinanet/predict.py
4. 效果
线上 0.97+
5. 参考
6. 提醒
如有疑问，请提出 issue，编码问题请自行谷歌。
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