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YOLO3-TF

YOLO v3 re-implementation, and our code is based stronger-yolo, a huge thank to him.

Use pre-trained model with YOLO V3 and Mobilenet V2

Usage

  1. clone this repository

    git clone https://github.com/fanbinqi/YOLO3-TF.git
  2. prepare data
    (1) download datasets
    Create a new folder named data and then create a new folder named VOC in the data/.
    Download VOC 2012_trainvalVOC 2007_trainvalVOC 2007_test, and put datasets into data/VOC, name as 2012_trainval2007_trainval2007_test separately.
    The file structure is as follows:
    |--YOLOV3-TF
    |--data
    |--|--VOC
    |--|--|--2012_trainval
    |--|--|--2007_trainval
    |--|--|--2007_test
    (2) convert data format
    You should set DATASET_PATH in config.py to the path of the VOC dataset and then

    python voc_annotation.py
  3. prepare initial weights
    (1) yolov3 Download YOLOv3-608.weights firstly, put the yolov3.weights into yolov3_to_tf/, and then

    cd yolov3_to_tf
    python3 convert_weights.py --weights_file=yolov3.weights --dara_format=NHWC -- ckpt_file=./saved_model/yolov3_608_coco_pretrained.ckpt
    cd ..
    python rename.py

    (2) mobilenet v2 if want to train model with MoBileNet V2, the re-trained model is in our repo ./weights

    put the initial weight into `weights/`.
  4. Train

    python train.py
  5. Test

    python test.py
    cd mAP
    python main.py

If you are interested in this project, please QQ me (374873360)

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YOLO v3 re-implementation

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