Thomas is a training engine that runs on coal
Being cute aside, thomas is an object detection and segmentation model that we extend to detect objects in imagery - using Tensorflow, Keras amd Coco.
While we train the models with new data, the majority of the hard work was done here.
The base mrcnn model was copied from that repo and slightly modified to fix a bug or two. The code in the mrcnn
directory should
not be touched unless you really know what you are doing.
Our model code lives in the objects directory
.
The dev environment for this can be a little trick but works on my machine (osx) as well as on Amazon's deep learning AMI
To get up and running:
- Setup a python 3.6 virtual env and source it
pip install -r requirements
export PYTHONPATH=$PATHONPATH:.
- Get the precomputed model weights from S3, either
s3://tomsorflow/coco/mask_rcnn_coco.h5
ors3://tomsorflow/buildings/mask_rcnn_buildings_1.h5
The setup_env.sh
should do the trick most of the time