jdc08161063 / tensorflow-deconvnet-segmentation

Tensorflow implementation of "Learning Deconvolution Network for Semantic Segmentation"

Tensorflow implementation of Learning Deconvolution Network for Semantic Segmentation.

Install Instructions

1. Get a Tensorflow version that fits to your system

2. Run the following commands in your terminal

git clone https://github.com/fabianbormann/Tensorflow-DeconvNet-Segmentation.git
cd Tensorflow-DeconvNet-Segmentation
sudo pip3 install -r requirements.txt

python3

Python 3.5.2+ (default, Sep 22 2016, 12:18:14)
[GCC 6.2.0 20160927] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from DeconvNet import DeconvNet
>>> deconvNet = DeconvNet() # will start collecting the VOC2012 data

Improving training

python write-tfrecords/img_to_records_pascal.py

Will write entire PASCAL VOC2012 dataset as TFRecord. Takes about 4mins @ 100it/s.

Default behaviour:

• assumes default dataset location from DeconvNet.py
• writes TFRecord to tfrecords folder
• Uses resize_image_with_crop_or_pad to make all images and segmentations fixed size of 224x224
• run with -h to see help and change defaults, will need to change decode_png to use image format other than png.

-- Contributions welcome!