While several datasets for autonomous navigation have become available in recent years, they have tended to focus on structured driving environments. This usually corresponds to well-delineated infrastructure such as lanes, a small number of well-defined categories for traffic participants, low variation in an object or background appearance and strong adherence to traffic rules.

I recently worked with IDD, dataset collected from India. It’s relatively more challenging than other autonomous navigation-related datasets (such as Berkeley deep drive or cityscapes) since much of the data has been captured from non standard conditions (drivable areas except roads etc.).

I’m releasing the code for this work, feel free to use it for your projects or research.

Github: https://github.com/prajjwal1/autonomous-object-detection

Dataset: https://idd.insaan.iiit.ac.in/