基于DOTA数据集的yolo训练+预训练的参数+源代码+文档说明（下载即用）

# DOTA database training with yolo | 基于DOTA数据集的yolo训练  ## clone this repo | 克隆此仓库 ``` git clone xxxx/dota-yolo cd dota-yolo ``` ## download DOTA dataset | 下载数据集 download from | 这里下载 https://captain-whu.github.io/DOTA/dataset.html then put them as following structure | 然后按如下结构存放 ``` DOTA-yolov3 | ├─dataset │ ├─train │ │ ├─images │ │ └─labelTxt │ └─val │ ├─images │ └─labelTxt ``` ## prerequisites | 必要环境 - darknent https://pjreddie.com/darknet/install/ - python3 - opencv-python etc. | opencv-python 等必要包 - Shapely (need geos|需要安装geos) ## split | 切割 ``` python3 data_transform/split.py ``` for more details refer https://github.com/CAPTAIN-WHU/DOTA_devkit ## transform label | 转换label ``` mkdir dataset/trainsplit/labels mkdir dataset/valsplit/labels python3 data_transform/YOLO_Transform.py # check labels # cd dataset/trainsplit/labels # awk -F" " '{col[$1]++} END {for (i in col) print i, col[i]}' *.txt # ``` for more details refer https://github.com/ringringyi/DOTA_YOLOv2 ## generate | 生成 train.txt & val.txt ``` ls -1d $PWD/dataset/trainsplit/images/* > cfg/train.txt ls -1d $PWD/dataset/valsplit/images/* > cfg/val.txt # when too many images # find "$(pwd)/dataset/trainsplit512/images">cfg/train.txt # find "$(pwd)/dataset/valsplit512/images">cfg/val.txt ``` ## train | 训练 ``` cd cfg mkdir backup # yolo-tiny darknet detector train dota.data dota-yolov3-tiny.cfg # more gpus darknet detector train dota.data dota-yolov3-tiny.cfg -gpus 0,1,2 # resume from unexpected stop darknet detector train dota.data dota-yolov3-tiny.cfg backup/dota-yolov3-tiny.backup # or yolov3-416 darknet detector train dota.data dota-yolov3-416.cfg ``` config cfg files refer https://medium.com/@manivannan_data/how-to-train-yolov3-to-detect-custom-objects-ccbcafeb13d2 ## predict | 预测 为了方便运行，这里用 opnencv做检测，要高性能还是用 darknent binding | Here I prepared opencv for easy set up, you can use darknet bindings for better performance ``` # tiny python test.py --image test.png --config cfg/dota-yolov3-tiny.cfg --weights cfg/backup/dota-yolov3-tiny_final.weights --classes cfg/dota.names # or 416 python test.py --image test.png --config cfg/dota-yolov3-416.cfg --weights cfg/backup/dota-yolov3-416_final.weights --classes cfg/dota.names ``` ## pretraind params | 预训练的参数 百度云 链接: https://pan.baidu.com/s/1V6fxrUpHLhukiJ-vT0F0pQ 提取码: pfq6 google drive: https://drive.google.com/drive/folders/1Y-W2npeaqflfO8IUA7gx9PzmesaSl9rY?usp=sharing