Yolov5

YoloV5 implemented by TensorFlow2 , with support for training, evaluation and inference.

NOT perfect project currently, but I will continue to improve this, so you might want to watch/star this repo to revisit. Any contribution is highly welcomed

Key Features

minimal Yolov5 by pure tensorflow2
yaml file to configure the model
custom data training
mosaic data augmentation
label encoding by iou or wh ratio of anchor
positive sample augment
multi-gpu training
detailed code comments
full of drawbacks with huge space to improve

Usage

Clone and install requirements

$ git clone git@github.com:LongxingTan/Yolov5.git
$ cd Yolov5/
$ pip install -r requirements.txt

Download VOC

$ bash data/scripts/get_voc.sh
$ cd yolo
$ python dataset/prepare_data.py

Train

$ python train.py

Inference

$ python detect.py
$ python test.py

Train on custom data

If you want to train on custom dataset, PLEASE note the input data should like this:

image_dir/001.jpg x_min, y_min, x_max, y_max, class_id x_min2, y_min2, x_max2, y_max2, class_id2

And maybe new anchor need to be created, don't forget to change the nc(number classes) in yolo-yaml.

$ python dataset/create_anchor.py

gshashank84/Yolov5