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Cats vs dogs classification using tensorflow

Learning image recognition using sentdexs' tutorial which you can find here: https://pythonprogramming.net/convolutional-neural-network-kats-vs-dogs-machine-learning-tutorial/
This is my simple attempt to learn about image recognition using tensorflow. After much effort, I did understand what happens in the background.

Feel free to try out the codes
Here are the steps:

  1. Make sure you have all the required packages mentioned in Pipfile
  2. You first need to preprocess your data. Ensure you've downloaded the images from https://www.kaggle.com/c/dogs-vs-cats-redux-kernels-edition/data , Now:
    1. Run python process_train_data.py to create the train_data.npy file
    2. Then run python process_test_data.py to create the test_data.npy file
  3. Finally, you are ready to create and train your model. Ensure you've uncommented the create_model and train_model function calls in create_n_train.py and then run python create_n_train.py. If you have a slow PC (like I do), this may take a while.
  4. Now you are ready to start the classification. Run python make_classification.py

Of course, if you are not an absolute beginner and have some understanding of tensorflow, you can use the model.meta file I've provided.

Do note: please keep the downloaded images and all the code files from this repository into a single directory. You can ignore this if you plan to tweak the path in the code yourself.

I managed to obtain around 96% accuracy. Some results are here:
Result2:

Not the best, but good enough for a beginner!