Face Crop App

This Application involves Training a RetinaNet to instinctively crop out scale and position-variant face(s) from pictures and save as a new image file.

If you want to know about the RetinaNet - I'd suggest you check this kernel, it's pretty intuitive

I used a pre-trained RetinaNet with Resnet50 as the backbone and then fine-tuned it to classify and detect (to draw a bounding box around a human face). The bounding box output was used to crop out the specific object(s) in the image.

This Model is very pretty scale and pose invariant

Images from flickr and shutterstock constituted of the training dataset

The workflow are outlined as follows:

Use labelimg to annotate (label and specify the bounding box cordinates) all the objects in the image in a Pascal VOC format
Run a xml script to convert the Pascal VOC format (xml) to csv as that's what a RetinaNet expects
Load the Pretrained RetinaNet from keras and all it's dependencies and navigate to the main file directory
Train the Pretrained RetinaNet by specifying a backbone (I used Retina50) and save the learned parameters after each epochs
Convert the saved model to an inference graph to test on unseeen data
Save the results as a Pandas DataFrame using the corresponding datapoints after testing on the test data
Use OpenCV's imwrite function to save the cropped image to a folder