Multiple Class Flower Image Classification CNN using Keras
Multiple Class Flower Image Classification using Keras
USAGE
For training model : python3 training_model —dataset training_set —model trained_model —plot plot
For predicting image : python3 predict.py —dataset training_set —model trained_model —image test_set/rose1
The model have been trained using Keras Library.
The architecture of the neural network used here is commonly known as LeNet architecture which is depiced as below
INPUT => CONV => RELU => POOL => CONV => RELU => POOL => FC => RELU => FC
For training this model, the most optimized No of Epochs were 25 and the Batch Size of 32 with the Adam Optimizer with the Initial Learning Rate of 1e-3.
The pre-trained model here has the following accuracy/loss which is also shown in the figure plot.png
Training Accuracy - 0.9057
Validation Accuracy - 0.8864
Training Loss - 0.2225
Validation Loss - 0.2838