helpers.py

from typing import Optional, Tuple

import cv2
import numpy as np

from pyk4a import ImageFormat


def convert_to_bgra_if_required(color_format: ImageFormat, color_image):
    # examples for all possible pyk4a.ColorFormats
    if color_format == ImageFormat.COLOR_MJPG:
        color_image = cv2.imdecode(color_image, cv2.IMREAD_COLOR)
    elif color_format == ImageFormat.COLOR_NV12:
        color_image = cv2.cvtColor(color_image, cv2.COLOR_YUV2BGRA_NV12)
        # this also works and it explains how the COLOR_NV12 color color_format is stored in memory
        # h, w = color_image.shape[0:2]
        # h = h // 3 * 2
        # luminance = color_image[:h]
        # chroma = color_image[h:, :w//2]
        # color_image = cv2.cvtColorTwoPlane(luminance, chroma, cv2.COLOR_YUV2BGRA_NV12)
    elif color_format == ImageFormat.COLOR_YUY2:
        color_image = cv2.cvtColor(color_image, cv2.COLOR_YUV2BGRA_YUY2)
    return color_image


def colorize(
    image: np.ndarray,
    clipping_range: Tuple[Optional[int], Optional[int]] = (None, None),
    colormap: int = cv2.COLORMAP_RAINBOW
) -> np.ndarray:
    invalid_mask = image == 0
    if clipping_range[0] or clipping_range[1]:
        img = image.clip(clipping_range[0], clipping_range[1])
    else:
        img = image.copy()
    img = cv2.normalize(img, None, 0, 255, cv2.NORM_MINMAX, dtype=cv2.CV_8U)

    # logarithmic colouring
    img_log = np.array(255 * np.log(img, where=np.invert(invalid_mask)) / np.log(255), dtype=np.uint8)

    img = cv2.applyColorMap(img_log, colormap)
    img[invalid_mask] = 0
    return img