preprocess_yolov4.py

import cv2
import numpy as np

def image_preprocess(image, target_size, gt_boxes=None):

    ih, iw = target_size
    h, w, _ = image.shape

    scale = min(iw/w, ih/h)
    nw, nh = int(scale * w), int(scale * h)
    image_resized = cv2.resize(image, (nw, nh))

    image_padded = np.full(shape=[ih, iw, 3], fill_value=128.0)
    dw, dh = (iw - nw) // 2, (ih-nh) // 2
    image_padded[dh:nh+dh, dw:nw+dw, :] = image_resized
    image_padded = image_padded / 255.

    if gt_boxes is None:
        return image_padded

    else:
        gt_boxes[:, [0, 2]] = gt_boxes[:, [0, 2]] * scale + dw
        gt_boxes[:, [1, 3]] = gt_boxes[:, [1, 3]] * scale + dh
        return image_padded, gt_boxes