A deep learning model to classify between dogs and cats using transfer learning with RESNET50
ResNet50 is a variant of ResNet model which has 48 Convolution layers along with 1 MaxPool and 1 Average Pool layer. It has 3.8 x 10^9 Floating points operations. It is a widely used ResNet model and we have explored ResNet50 architecture in depth. his architecture can be used on computer vision tasks such as image classififcation, object localisation, object detection.And this framework can also be applied to non computer vision tasks to give them the benifit of depth and to reduce the computational expense also.
Libraries used :
Tensorflow
Keras
Numpy
Matplotlib
Pandas
Seaborn
Sklearn
Tqdm
Random
openCV
The data set can be downloaded from below links and extracted inside the input folder:
https://www.kaggle.com/c/dogs-vs-cats-redux-kernels-edition
https://www.kaggle.com/keras/resnet50
The Output looks like :
