Neural network trained to make the best looking crops of images. It is described in the blog .
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Download checkpoint of Inception v4 from https://github.com/tensorflow/models/tree/master/slim#pre-trained-models and unpack it to root.
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Install all requirements by running
pip install requirements.txt -
Find some data (you have to do it on your own. AVA dataset maybe...). It is JSON containing array with objects:
{"picture":"path/to/picture","good_example":True}Method to decide if picture is good or bad is described in blog. You can take inspiration from
.
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Open
. There are several parameters at the beginning of the file.
| Parameter | Function |
|---|---|
| TRAIN | Run training or run cropping (Bool) |
| EPOCHS | How many epochs will we train? (Int) |
| BATCH_SIZE | Size of batch (Int) |
| TRAIN_ACCURACY | Do we want to evaluate accuracy on trainig set? This will make training A LOT slower. (Bool) |
| MODEL_NAME | Name of model (String) |
| RESTORE | Will we restore the model from checkpoint? (Bool) |
| CHECKPOINT | Path to checkpoint (String) |
| EPOCH | From which epoch to continue? (Int) |
| [training|validation|testing]_dataset | Path to folder with dataset and name of json file (String, String) |
| IMAGE_FOLDER | Path to folder with photos to crop (String) |
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Set parameters to train and run training by
py -3 Main.py -
Set parameters to cropping and run cropping by
py -3 Main.py
