Image-Classification

CNN based classifier to classify images of vessels into 5 different categories. This solution was for a hackathon organized by Analytics Vidhya.

Problem Statement

Ship or vessel detection has a wide range of applications, in the areas of maritime safety, fisheries management, marine pollution, defence and maritime security, protection from piracy, illegal migration, etc.

Keeping this in mind, a Governmental Maritime and Coastguard Agency is planning to deploy a computer vision based automated system to identify ship type only from the images taken by the survey boats. You have been hired as a consultant to build an efficient model for this project.

There are 5 classes of ships to be detected which are as follows:

1. Cargo
2. Military
3. Tanker
4. Carrier
5. Cruise

Dataset Description

There are 6252 train images and 2680 images in the test set.he categories of ships and their corresponding codes in the dataset are as follows:

'Cargo' -> 1 'Military' -> 2 'Carrier' -> 3 'Cruise' -> 4 'Tankers' -> 5

There are 2 files provided to us along with the dataset:

1. train.csv: Train dataset 2 .test_ApKoW4T.csv: Test dataset

Code Files:

1. Data_create.py: Divide dataset into train and test folders based on csv files
2. Classify.py: CNN architecture to classify the images

Evaluation Metric

The evaluation metrics for this competition was weighted F1 score