2019 第五届“四维图新”杯创新大赛 自动驾驶视觉综合感知算法赛 detection baseline
testA object detection map: 0.22
testA semantic segmentation miou: 0.46
author: zhengye
for the semantic segmentation part, please refer to my teammate's git repo: https://github.com/SHERLOCKLS/datafountain_siweituxin_autodriver_seg
请按照mmdetection说明进行安装配置
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数据准备
将训练数据所有训练图片放置于 data/siweituxin/train_image
两批次的数据label分别位于'data/dataset1/train.txt' 和 'data/DF_1018/train.txt'
合并label: python tools/convert_datasets/merage_txt_label.py
txt转coco json: python tools/convert_datasets/trans_txt2json.py
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模型训练
请依据mmdetection说明依据自身显卡情况线性调整lr,这里以4卡为例
CUDA_VISIBLE_DEVICES=0,1,2,3 ./tools/dist_train.sh config/siweituxin/faster_rcnn_r50_fpn.py 4
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数据准备
将测试数据所有训练图片放置于 data/siweituxin/test_images
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inference
CUDA_VISIBLE_DEVICES=0 python tools/infer_siweituxin.py config/siweituxin/faster_rcnn_r50_fpn.py /work_dirs/faster_rcnn_r50_fpn/latest.pth --out det.txt
This repo is currently maintained by Ye Zheng (@zhengye1995).