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Getting Started

  • Download the "Kaggle Dogs and Cats Redux" dataset
  • unzip train.zip and place the cat.####.jpg and dog.####.jpg files into ./data/train/.
  • unzip test.zip and place the ####.jpg files into ./data/test.
  • Execute run.sh
  • To test your model, execute evaluate.sh

run.sh (train.py)

Ayy, It's as easy as that bay-beeeee

evaluate.sh (check.py)

TensorFlow really outdid themselves this time...

Layout

  • training.py - Executes the network training.
  • model.py - Contains the network layer definitions.
  • input_data.py - Ingresses training data and creates lists and batches.
  • check,py - Tests the created model against one image, outputs prediction.

Dependencies

train.py:

  • Python3
  • TensorFlow

check.py:

  • xvfb
  • python3-matplotlib

Kaggle Dogs and Cats Redux dataset

Additional Help

Installing TensorFlow System Wide (No Virtual Environment) (Debian/Ubuntu)

sudo apt-get install python3-pip python3-dev
sudo pip3 install -U pip
sudo pip3 install -U tensorflow

Install Xvfb and matplotlib (For headless image prediction tests (check.py)

sudo apt install python3-matplotlib
sudo apt install xvfb

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