We will use the Nanonets Image Classification API to determine from a picture of a phone whether it is damaged or not.

Note: Make sure you have python and pip installed on your system if you don't visit Python, pip

git clone https://github.com/NanoNets/nanonets-cracked-screen-detection.git
cd nanonets-cracked-screen-detection
sudo pip install requests tqdm

Get your free API Key from http://app.nanonets.com/#/keys

export NANONETS_API_KEY=YOUR_API_KEY_GOES_HERE

python ./code/create-model.py

_Note: This generates a MODEL_ID that you need for the next step

export NANONETS_MODEL_ID=YOUR_MODEL_ID

_Note: you will get YOUR_MODEL_ID from the previous step

The training data is found in the data directory

python ./code/upload-training.py

Once the Images have been uploaded, begin training the Model

python ./code/train-model.py

The model takes ~2 hours to train. You will get an email once the model is trained. In the meanwhile you check the state of the model

python ./code/model-state.py

Once the model is trained. You can make predictions using the model

python ./code/prediction.py PATH_TO_YOUR_IMAGE.jpg

Sample Usage:

python ./code/prediction.py ./data/mobile_damaged/00000028.jpg