keras_yolov3_mobilnet
0-背景
change the backend of darknet53 into
- Mobilenet
- VGG16
- ResNet101
- ResNeXt101
1-training
1.制作自己的数据集
行形式:image_file_path box1 box2 ... boxN
框形式:x_min,y_min,x_max,y_max,class_id (no space).
转换成VOC格式数据:python voc_annotation.py
举例:
path/to/img1.jpg 50,100,150,200,0 30,50,200,120,3
path/to/img2.jpg 120,300,250,600,2
...
2.运行下面脚本
python convert.py -w yolov3.cfg yolov3.weights model_data/yolo_weights.h5
3.开始训练
python train.py
3-log
tensorboard --logdir ./logs/carMobilenet/001_Mobilenet_finetune_02/
4-test
python test_folder.py
5-h5模型格式转换成tensorflow-serving格式
python h52pb.py -path "./*.h5" -num 2 -anchor 9 -export "./pb_folder"
6-serving部署以及测试
仔细查阅tensorflow-serving