Utilities for the human-object interaction detection dataset HICO-DET

• A command-line style dataset navigator
• Large-scale visualisation in web page
• Generate object detections with Faster R-CNN
• Generate ground truth object detections
• Visualise detected objects
• Evaluate object detections
• Fine-tune Faster R-CNN on HICO-DET

1. Download the repo with git clone https://github.com/fredzzhang/hicodet.git
2. Prepare the HICO-DET dataset
   1. If you have not downloaded the dataset before, run the following script

   cd /path/to/hicodet
   bash download.sh

   2. If you have previously downloaded the dataset, simply create a soft link

   cd /path/to/hicodet
   ln -s /path/to/hico_20160224_det ./hico_20160224_det

3. Install the lightweight deep learning library Pocket
4. Make sure the environment you created for Pocket is activated. You are good to go!

The implementation of the dataset class can be found in hicodet.py. Refer to the documentation to find out more about its usage. For convenience, the dataset class has been included in the Pocket library, accessible via pocket.data.HICODet.

MIT License