YAD2K: Yet Another Darknet 2 Keras
来源:互联网 发布:淘宝每天的成交额 编辑:程序博客网 时间:2024/04/30 04:58
网址:https://github.com/allanzelener/YAD2K
Welcome to YAD2K
You only look once, but you reimplement neural nets over and over again.
YAD2K is a 90% Keras/10% Tensorflow implementation of YOLO_v2.
Original paper: YOLO9000: Better, Faster, Stronger by Joseph Redmond and Ali Farhadi.
Requirements
- Keras
- Tensorflow
- Numpy
- h5py (For Keras model serialization.)
- Pillow (For rendering test results.)
- Python 3
- pydot-ng (Optional for plotting model.)
Installation
git clone https://github.com/allanzelener/yad2k.gitcd yad2k# [Option 1] To replicate the conda environment:conda env create -f environment.ymlsource activate yad2k# [Option 2] Install everything globaly.pip install numpy h5py pillowpip install tensorflow-gpu # CPU-only: conda install -c conda-forge tensorflowpip install keras # Possibly older release: conda install keras
Quick Start
- Download Darknet model cfg and weights from the official YOLO website.
- Convert the Darknet YOLO_v2 model to a Keras model.
- Test the converted model on the small test set in
images/
.
wget http://pjreddie.com/media/files/yolo.weightswget https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/yolo.cfg./yad2k.py yolo.cfg yolo.weights model_data/yolo.h5./test_yolo.py model_data/yolo.h5 # output in images/out/
See ./yad2k.py --help
and ./test_yolo.py --help
for more options.
More Details
The YAD2K converter currently only supports YOLO_v2 style models, this include the following configurations:darknet19_448
, tiny-yolo-voc
, yolo-voc
, andyolo
.
yad2k.py -p
will produce a plot of the generated Keras model. For example seeyolo.png.
YAD2K assumes the Keras backend is Tensorflow. In particular for YOLO_v2 models with a passthrough layer, YAD2K usestf.space_to_depth
to implement the passthrough layer. The evaluation script also directly uses Tensorflow tensors and usestf.non_max_suppression
for the final output.
voc_conversion_scripts
contains two scripts for converting the Pascal VOC image dataset with XML annotations to either HDF5 or TFRecords format for easier training with Keras or Tensorflow.
yad2k/models
contains reference implementations of Darknet-19 and YOLO_v2.
train_overfit
is a sample training script that overfits a YOLO_v2 model to a single image from the Pascal VOC dataset.
Known Issues and TODOs
- Expand sample training script to train YOLO_v2 reference model on full dataset.
- Support for additional Darknet layer types.
- Tuck away the Tensorflow dependencies with Keras wrappers where possible.
- YOLO_v2 model does not support fully convolutional mode. Current implementation assumes 1:1 aspect ratio images.
Darknets of Yore
YAD2K stands on the shoulders of giants.
- 0 0
- YAD2K: Yet Another Darknet 2 Keras
- Yacc : Yet Another Compiler-Compiler 中英对照2
- Yet Another Multiple Problem
- Yet Another PhotoMosaic Generator
- Yet Another Analog Clock
- Yet Another Lambda Tutorial
- Yet Another Median Task
- Codeforces868F Yet Another MinimizationProblem
- YAD2K,pytorch-caffe-darknet-convert,转换后概率不一样的问题
- Yet Another Web Framework 1
- Yacc: Yet Another Compiler-Compiler
- hdu4474-Yet Another Multiple Problem
- hdu4474 Yet Another Multiple Problem
- HDU4474 Yet Another Multiple Problem
- CRF++: Yet Another CRF toolkit
- uva10689 Yet another Number Sequence
- Hackerrank:Yet Another KMP Problem
- UVA10689-Yet another Number Sequence
- ADB error: more than one device/emulator
- 遍历map的几种方法 java
- 你不得不知道的 MySQL 优化原理
- 实际工作中ORA-01578: ORACLE data block corrupted遇到问题的解决方式
- phpStudy for Linux (lnmp+lamp一键安装包)
- YAD2K: Yet Another Darknet 2 Keras
- Android中Looper的quit方法和quitSafely方法
- 清除svn版本号文件
- 深度学习Deeplearning4j 入门实战(4):Deep AutoEncoder进行Mnist压缩的Spark实现
- 遗传算法
- shell语法
- 数据存储:数据备份:自动备份
- I2S与pcm的区别
- C++计算PI的值