Contributors:
Dhruv Chawla
Aaryansh Bhargavan
Phaneesh R Katti
A CNN model to classify given image input into a whooping 131 different classes of fruits and veggies
Here we use the fruits-360 kaggle dataset(https://www.kaggle.com/moltean/fruits) to train a CNN model to learn to classify objects into 131 varities of fruits and vegetables
The dataset by default has about 90,000 images of which 75% are training images images are of resolution 100x100 pixels We have used InceptionV3 Architecture for Transfer Learning, as well as Data Augmentation
The 131 classes have been named in the pre-defined order and must not be changed Model is trained for 30 epochs and gives reasonably good accuracy
Video presentation: https://drive.google.com/drive/u/0/folders/1pvuebms0wIzaXzCSbQfcJH11q9O9CwJT (Be sure to follow certain in script instructions to get the o/p)