A Multiclass Image Classification project using Convolutional Neural Network in Keras and Tensorflow.
The dataset was divided into two phase:
1- Training Phase: The dataset consists of 2330 images from 6 different categories where 1864 images were used for the training while 466 were used for validation. Dataset can be accessed through the link given below:
https://drive.google.com/drive/folders/1RPgYiu9eOu9q0G4S9gQThgS6Anu1DHcn?usp=sharing
2- Testing Phase: After model being trained, it was tested against 579 images from all 6 categories. Dataset can be accessed through the link given below:
https://drive.google.com/drive/folders/152Xm3U9rGuFYWfAFltaLi1Ok5WtNM5Ns?usp=sharing
Model was trained using Convolutional Neural Networks to classify different types of fruits. This model can be used for any existing dataset for Multiclass Image Classification
- Download and prepare your training data
- Use any of the file (.py or .ipynb) to play around with the code