Motivation

Recently I participated in JanataHack: Computer Vision Hackathon hosted by Analytics Vidhya. The aim of the competition was to create a binary image classifier that could differentiate the Non — Emergency Vehicles eg. private owned vehicles . from the emergency vehicles (police vehicles , ambulances, etc).

Originally I had used keras at that time of submission. But then I decided to implement a pytorch version to see if there was any advantage in using pytorch as most top participants has used fastai which used pytoch in backend.

Why Is this important ?

Fatalities due to traffic delays of emergency vehicles such as ambulance & fire brigade is a huge problem. In daily life, we often see that emergency vehicles face difficulty in passing through traffic.

So differentiating a vehicle into an emergency and non emergency category can be an important component in traffic monitoring as well as self drive car systems as reaching on time to their destination is critical for these services.

Data Description

There are total of 1646 in the train set and 706 in the test set.

There are two .csv files which contain the train and test image names.

#ai #machine-learning #pytorch-vs-tensorflow #streamlit #pytorch