Building a Deep Face Detection Model with Python and TensorFlow (Part 3)

Check out Part 1

Check out Part 2

Welcome back to the continuation of our tutorial on building a deep face detection model using Python and TensorFlow. In this part, we'll pick up where we left off and cover steps 5 through 11, including data augmentation, model building, training, and making predictions.

5. Build and Run Augmentation Pipeline

5.1 Run Augmentation Pipeline

for partition in ['train', 'test', 'val']: 
    for image in os.listdir(os.path.join('data', partition, 'images')):
        img = cv2.imread(os.path.join('data', partition, 'images', image)) …

ai augmentation building check data deeplearning detection face machinelearning part python tensorflow through tutorial