Image_classifier_using_Keras
Image Classification using Convolutional Neural Nets and Keras. This classifier uses LeNet-5, a pioneering 7-level convolutional network by LeCun et al in 1998 that classifies digits.
Requirements: Python 3.5 ,Keras 2.0.2 , Tensorflow 1.2.1 , OpenCV 3.3, numpy 1.11.0
How to:
Train your own model:
$ python train_network.py --dataset images --model Bharath_Kumar.model
Test your own model:
python test_network.py --model Bharath_Kumar.model --image images/examples/bk19.jpg
Add Your own Dataset:
Add your training images in images/<Your Label>/
Contents /Scripts of Barath Classifier :):
-train_network.py :
To train the model.
-test_network.py:
To train the model.
-Bharath_Kumar.model :
Model generated during thhe training.
- data.zip :
Contains Images for Training. Use your owm data set here.
-BK_lenet.zip :
LeNet Architecture.
About The Model:
Trained using Backpropogation algorithm with stochastic gradint descent. This is a Binary Classifier.
Accuracies after 25 epochs:
For classification based model:
-Train acc: 96.4665%
-Test acc : 88.5039%