Explanation

Multiclass wild animals image classifiaction

Dataset:
This deep learning project to classify 6 types of wild animals using CNN.
Classes:
1.Cheetah 2.Fox 3.Hyena 4.Lion 5.Tiger 6.Wolf
Data colletion:
Wild animals image dataset collected from kaggle.Image_size(224,224) and each classes had 100 images.
Features:
Custom convolutional neural network with 5 layers(1-input,3-hidden and 1-output layers),also using data augmentation to improve generalization.
Tools:
language Python , Tensorflow and keras, Jupyter notebook.
Save:
Model save in h5(Hierarchical file)

Result

Model got at 85% accuracy of training by after epoch 35/50.
Validation accuracy:
Reach 65% (Improvement need)
Model save in h5 (Hirarchical data format5) for prediction.

streamlit web app for Model prediction:

User Interface for file upload:

Lion:

Tiger:

Fox: