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KITTI-Road-Segmentation
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Segment lanes on KITTI
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KITTI-Road-Segmentation
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# Kitti- Road Segmentation > Lane Segmentation using several architectures. [](https://www.python.org/) [](https://pypi.python.org/pypi/ansicolortags/) [](http://makeapullrequest.com) [](https://github.com/ellerbrock/open-source-badges/) It contains the code for both training and segmentation of lane lines using Deep Learning. Currently the supported architectures are ENET, UNET, Modified VGG. ## Features - [x] The training code is very much scalable towards any new architecture. - [x] All changes made in the config file will effect in the training process so that the training logic can be without hassle. - [x] The training configuartion are easily tunable through the config file provided. ## Requirements - The training module has been built using Pycharm 2018.1.4. - The System requirement’s are 2.7 GHz Intel Core i5 with atleast 8 GB of RAM. ## Installation #### OpenCV You can use [Anaconda](https://conda.io/) to install `opencv` with the following command line.: ``` conda install -c conda-forge opencv ``` #### Image Augmentation You can use [PIP](https://pypi.org/project/pip/) to install the module `imgaug` with the following command line.: ``` pip install imgaug ``` #### Tensorflow You can use [PIP](https://pypi.org/project/pip/) to install `tensorflow` with the following command line or please go through their official installation [guideline](https://www.tensorflow.org/install/pip) ``` pip install tensorflow ``` #### Keras You can use [PIP](https://pypi.org/project/pip/) to install `keras` with the following command line or please go through their official installation [guideline](https://keras.io/#installation) ``` pip install keras ``` ## Usage example Run the following script to dispatch the trainer. ``` python3 train.py --conf=./config.json ``` ## Contribute Don't feel shy to drop a star, if you find this repo useful.I would love for you to contribute to **KITT-Road Segmentation**, check the ``LICENSE`` file for more info. ## Meta Stanly Moses – [@Linkedin](https://in.linkedin.com/in/stanlymoses) – stanlimoses@gmail.com Distributed under the MIT license. See ``LICENSE`` for more information. [https://github.com/StanlyHardy/KITTI-Road-Segmentation](https://github.com/StanlyHardy/)
