ardamavi/cat-segmentation

Cat segmentation with deep learning

Cat-Segmentation

By Arda Mavi

Cat segmentation with deep learning.
Database created by myself.

Segmentation Example:

Orijinal	Segmented

Using Predict Command:

python3 predict.py <ImageFileName>

Model Training:

python3 train.py

Using TensorBoard:

tensorboard --logdir=Data/Checkpoints/logs

Model Architecture:

• Input Data Shape: 64x64x3

• Convolutional Layer 32 filter Filter shape: 3x3 Strides: 1x1

• Activation Function: ReLu

• Convolutional Layer 64 filter Filter shape: 3x3 Strides: 1x1

• Activation Function: ReLu

• Transpose Convolutional Layer 64 filter Filter shape: 3x3 Strides: 1x1

• Activation Function: ReLu

• Merge Layer

• Transpose Convolutional Layer 1 filter Filter shape: 3x3 Strides: 1x1

• Activation Function: Sigmoid

Optimizer: Adadelta

Loss: Dice Coefficient

Important Notes:

• Used Python Version: 3.6.0

• Install necessary modules with sudo pip3 install -r requirements.txt command.

• We work on 64x64 image also if you use bigger, program will automatically return to 64x64.