Butterflies are the adult flying stage of certain insects belonging to an order or group called Lepidoptera. The word "Lepidoptera" means "scaly wings" in Greek. This name perfectly suits the insects in this group because their wings are covered with thousands of tiny scales overlapping in rows. An agency of the Governmental Wildlife Conservation is planning to implement an automated system based on computer vision so that it can identify butterflies based on captured images. As a consultant for this project, you are responsible for developing an efficient model.
Our object was to build an Image Classification Model using CNN that classifies to which class of weather each image belongs to
1.train - contains all the images that are to be used for training your model. In this folder you will find 75 folders namely - 'SOUTHERN DOGFACE', 'ADONIS', 'BROWN SIPROETA', 'MONARCH','GREEN CELLED CATTLEHEART', 'CAIRNS BIRDWING','EASTERN DAPPLE WHITE', 'RED POSTMAN', 'MANGROVE SKIPPER',which contain the images of the respective butterflies
2.Training_set.csv - this csv file has contains the labels for the training images
3.test - contains 2786 images of Butterflies. For these images you are required to make predictions as the respective class names -'SOUTHERN DOGFACE', 'ADONIS', 'BROWN SIPROETA', 'MONARCH','GREEN CELLED CATTLEHEART', 'CAIRNS BIRDWING'.
4.Testing_set.csv - this is the order of the predictions for each image that is to be submitted on the platform. Make sure the predictions you submit are with their image’s filename in the same order as given in this file.
You can find the dataset that was used in this link
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