eragonruan / Refinenet Image Segmentation
a tensorflow implement of refinenet ,RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
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refinenet
a tensorflow implement of refinenet. RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
Introduction
this is a tensorflow implement of refinenet discribed in arxiv:1611.06612.I have not finished it yet, this is just a demo, but the model is already able to work.
prepare
- download the pretrain model of resnet_v1_101.ckpt, you can download it from here
- download the pascal voc dataset
- some dependence like cv2, numpy and etc. recommend to install Anaconda
training
- first, run convert_pascal_voc_to_tfrecords.py to convert training data into .tfrecords, Or you can use the tfrecord I converted In BaiduYun.Currently, I only use the pascal voc 2012 for training.
- second, run python RefineNet/multi_gpu_train.py, also, you can change some hyper parameters in this file, like the batch size.
eval
- if you have already got a model, or just download the model I trained on pascal voc.model.
- put images in demo/ and run python RefineNet/demo.py
roadmap
- [x] python2/3 compatibility
- [ ] Complete realization of refinenet model
- [ ] test on pascal voc, give the IoU result
- [ ] training on other datasets
some result
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