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img_utils.py
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img_utils.py
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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)
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_width=150, crop_heigth=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