img_utils.py

import cv2
import numpy as np



def load_img(path, grayscale=False, target_size=None, crop_size=None):
    """
    Load an image.
    
    # Arguments
        path: Path to image file.
        grayscale: Boolean, whether to load the image as grayscale.
        target_size: Either `None` (default to original size)
            or tuple of ints `(img_width, img_height)`.
        crop_size: Either `None` (default to original size)
            or tuple of ints `(img_width, img_height)`.
        
    # Returns
        Image as numpy array.
    """

    img = cv2.imread(path)
    if grayscale:
        if len(img.shape) != 2:
            img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    if target_size:
        if (img.shape[0], img.shape[1]) != target_size:
            img = cv2.resize(img, (target_size[1],target_size[0]))

    if crop_size:
        img = central_image_crop(img, crop_size[0], crop_size[1])


    if grayscale:
        img = img.reshape((img.shape[0], img.shape[1], 1))

    return np.asarray(img, dtype=np.float32)



def central_image_crop(img, crop_heigth=150, crop_width=150):
    """
    Crop the input image centered in width and starting from the bottom
    in height.

    # Arguments:
        crop_width: Width of the crop.
        crop_heigth: Height of the crop.

    # Returns:
        Cropped image.
    """
    half_the_width = int(img.shape[1] / 2)
    img = img[img.shape[0] - crop_heigth: img.shape[0],
              half_the_width - int(crop_width / 2):
              half_the_width + int(crop_width / 2)]
    return img