KringleCon - Holiday Hack Challenge - 2019

Adapted from https://github.com/chrisjd20/img_rec_tf_ml_demo

Goal of the challenge: solve the CAPTEHA on the website: https://fridosleigh.com/

Installation:

git clone https://github.com/chrisjd20/img_rec_tf_ml_demo.git
cd img_rec_tf_ml_demo
sudo apt install python3 python3-pip -y
sudo python3 -m pip install --upgrade pip
sudo python3 -m pip install --upgrade setuptools
sudo python3 -m pip install --upgrade tensorflow==1.15
sudo python3 -m pip install tensorflow_hub   #this one may or may not be needed in order to run

Training the ML Model based on images from Krampus:

This will take a long time on 12000 images!

python3 retrain.py --image_dir ./capteha_images/

_{^{retrain.py is a slightly modified version of https://raw.githubusercontent.com/tensorflow/hub/master/examples/image_retraining/retrain.py}}

This will create two files we will be using at:

1. /tmp/retrain_tmp/output_graph.pb - Trained Machine Learning Model
2. /tmp/retrain_tmp/output_labels.txt - Labels for Images

Testing prediction on unknown_images using the trained Model:

chmod 755 predict_images_using_trained_model.py
./predict_images_using_trained_model.py

Solving the CAPTEHA objective:

Remember to update your email in the source code to get the code from the Frido Sleigh challenge:

python3 capteha_api.py

Remove Temp Cache Files Between Different Retrains

rm -rf /tmp/retrain_tmp /tmp/tfhub_modules