import numpy as np
from PIL import Image


def crop_and_resize(image_path, bbox_path, crop_path, resize_path):
    img = Image.open(image_path)
    width, height = img.size

    with open(bbox_path, 'r') as f:
        _, x_center, y_center, _, _ = map(float, f.readline().split())
        x_center, y_center = int(x_center * width), int(y_center * height)

    x1, x2 = max(0, x_center - 128), min(width, x_center + 128)
    y1, y2 = max(0, y_center - 128), min(height, y_center + 128)

    crop = img.crop((x1, y1, x2, y2))
    assert crop.size == (256, 256)
    crop.save(crop_path)

    resize = crop.resize(size=(128, 128), resample=Image.BICUBIC)
    assert resize.size == (128, 128)
    resize.save(resize_path)


def transform_intrinsic(intrinsic_path, bbox_path, crop_path, resize_path):
    intrinsic = np.loadtxt(intrinsic_path)
    fx, fy = intrinsic[0, 0], intrinsic[1, 1]
    cx, cy = intrinsic[0, 2], intrinsic[1, 2]
    width, height = cx * 2, cy * 2

    with open(bbox_path, 'r') as f:
        _, x_center, y_center, _, _ = map(float, f.readline().split())
        x_center, y_center = int(x_center * width), int(y_center * height)
    
    x1, y1 = max(0, x_center - 128), max(0, y_center - 128)

    K = np.array([[fx, 0, cx - x1],
                  [0, fy, cy - y1],
                  [0, 0, 1]])
    np.savetxt(crop_path, K, fmt="%.5f", delimiter=" ")

    K[:2] /= 2
    np.savetxt(resize_path, K, fmt="%.5f", delimiter=" ")


if __name__ == "__main__":
    # crop and resize image
    image_path = '640x480/image/0000_00.png'
    bbox_path = '640x480/bbox/0000_00.txt'
    crop_path = '256x256/image/0000_00.png'
    resize_path = '128x128/image/0000_00.png'
    crop_and_resize(image_path, bbox_path, crop_path, resize_path)

    # transform intrinsic matrix
    intrinsic_path = '640x480/intrinsic.txt'
    bbox_path = '640x480/bbox/0000_00.txt'
    crop_path = '256x256/intrinsic/0000_00.txt'
    resize_path = '128x128/intrinsic/0000_00.txt'
    transform_intrinsic(intrinsic_path, bbox_path, crop_path, resize_path)