Tensorflow implementation mobilenetv2-yolov3 inspired by keras-yolo3
usage: yolo_video.py [-h] [--model MODEL] [--anchors ANCHORS]
[--classes CLASSES] [--gpu_num GPU_NUM] [--image]
[--input] [--output]
positional arguments:
--input Video input path
--output Video output path
optional arguments:
-h, --help show this help message and exit
--model MODEL path to model weight file, default model_data/yolo.h5
--anchors ANCHORS path to anchor definitions, default
model_data/yolo_anchors.txt
--classes CLASSES path to class definitions, default
model_data/coco_classes.txt
--gpu_num GPU_NUM Number of GPU to use, default 1
--image Image detection mode, will ignore all positional arguments
--export Export binary pb model for tensorflow,which you can put it in tensorflow serving directly
- Download pascal tfrecords from here.
- Change train.py
opt = <your session config> backbone = <your yolov3 backbone> log_dir = <path/to/your/tensorboard/log> batch_size = <you batch size> train_dataset_path = <path/to/your/train/folder> val_dataset_path = <path/to/your/val/folder> train_dataset_glob = <train glob> val_dataset_glob = <val glob>
3 times faster than darknet53-yolov3 with alpha=1.4 and higher accuracy
I have packaged a pascal tfrecords for you.See here