nilboy/tensorflow-yolo has 768 GitHub stars and 306 forks. GitHot measured 0 stars in 24 hours. Last checked 2026-11-15 11:01 UTC. Last push 2018-10-22.
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概要
tensorflow implementation of 'YOLO : Real-Time Object Detection'(train and test)
機械学習README.md
オリジナルtensorflow-yolo
Require
tensorflow-1.0
download pretrained model
yolo_tiny: https://drive.google.com/file/d/0B-yiAeTLLamRekxqVE01Yi1RRlk/view?usp=sharing
mv yolo_tiny.ckpt models/pretrain/
Train
Train on pascal-voc2007 data
Download pascal-Voc2007 data
Download the training, validation and test data
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtrainval_06-Nov-2007.tar wget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtest_06-Nov-2007.tarExtract all of these tars into one directory named
VOCdevkittar xvf VOCtrainval_06-Nov-2007.tar tar xvf VOCtest_06-Nov-2007.tarIt should have this basic structure
$VOCdevkit/ # development kit $VOCdevkit/VOCcode/ # VOC utility code $VOCdevkit/VOC2007 # image sets, annotations, etc. # ... and several other directories ...Create symlinks for the PASCAL VOC dataset
cd $YOLO_ROOT/data ln -s $VOCdevkit VOCdevkit2007Using symlinks is a good idea because you will likely want to share the same PASCAL dataset installation between multiple projects.
convert the Pascal-voc data to text_record file
python tools/preprocess_pascal_voc.py
train
python tools/train.py -c conf/train.cfg
Train your customer data
transform your training data to text_record file(the format reference to pascal_voc)
write your own train-configure file
train (python tools/train.py -c $your_configure_file)
test demo
python demo.py