@@ -11,7 +11,64 @@ This is an evolving dataset, where we will release more data as the dataset grow

# Baseline
**TODO** : @Nikhil : Please add some description of this baseline, links to MMDection paper etc.
MMdetection is an open source object detection toolbox based on PyTorch, with a large Model Zoo with many customised models that can be plugged and tested in with just a single config file modification. PYou can read more about it at: [mmdetection github](https://github.com/open-mmlab/mmdetection/)
Follow the installation instructions as given in the above link.
# Training with MMDetection:
Let us look at training MMDetection using Hybrid Task Cascade [HTC research paper](https://arxiv.org/abs/1901.07518).
A score of AP_50 of 0.526 and AR_50 of 0.729, can be achieved with Hybrid Task Cascade of Resnet50 Backbone.
MMDetection provides us with a config file especially for HTC, available at [HTC config](https://github.com/open-mmlab/mmdetection/tree/master/configs/htc)
Also make sure you have downloaded the training data to a subfolder of your project.
Modify your config file and point your dataset variables to your data folder.
As given in [MMDetection Getting Started](https://github.com/open-mmlab/mmdetection/blob/master/docs/GETTING_STARTED.md),