# Overlay two input images

"""
Created on Tue. September 01 21:00:01 2020
A function
@author: hudanyunsheng
"""

import os
import cv2
import numpy as np
from skimage import img_as_ubyte
from plantcv.plantcv import fatal_error
from plantcv.plantcv._debug import _debug
from plantcv.plantcv import params
from plantcv.plantcv.transform import rescale


def _preprocess_img_dtype(img):
    """ Transform the input image such that the datatype after transformation is uint8, ready for opencv functions
    :param img: inut image array
    :return:
    """
    debug_mode = params.debug
    params.debug = None
    try:
        img_ = rescale(img)
    except:
        img_ = skimage.img_as_ubyte(img)
    params.debug = debug_mode
    return img_


def overlay_two_imgs(img1, img2, alpha=0.5):
    """Overlay two images with a given alpha value.

    Inputs:
    img1     - RGB or grayscale image data
    img2     - RGB or grayscale image data
    alpha    - Desired opacity of 1st image, range: (0,1), default value=0.5

    Returns:
    out_img  - Blended RGB image

    :param img1: numpy.ndarray
    :param img2: numpy.ndarray
    :param alpha: float
    :return: out_img: numpy.ndarray
    """
    # Validate alpha
    if alpha > 1 or alpha < 0:
        fatal_error("The value of alpha should be in the range of (0,1)!")

    # Validate image sizes are the same
    size_img1 = img1.shape[0:2]
    size_img2 = img2.shape[0:2]
    if size_img1 != size_img2:
        fatal_error(f"The height/width of img1 ({size_img1}) needs to match img2 ({size_img2}).")

    # Convert the datatype of the image such that
    img1 = _preprocess_img_dtype(img1)
    img2 = _preprocess_img_dtype(img2)

    # Copy the input images
    img1_ = np.copy(img1)
    img2_ = np.copy(img2)

    # If the images are grayscale convert to BGR
    if len(img1_.shape) == 2:
        img1_ = cv2.cvtColor(img1_, cv2.COLOR_GRAY2BGR)
    if len(img2_.shape) == 2:
        img2_ = cv2.cvtColor(img2_, cv2.COLOR_GRAY2BGR)

    # initialize the output image
    out_img = np.zeros(size_img1 + (3,), dtype=np.uint8)

    # blending
    out_img[:, :, :] = (alpha * img1_[:, :, :]) + ((1 - alpha) * img2_[:, :, :])

    params.device += 1
    _debug(visual=out_img, filename=os.path.join(params.debug_outdir, str(params.device) + '_overlay.png'))

    return out_img

# Overlay two input images

"""
Created on Tue. September 01 21:00:01 2020
A function
@author: hudanyunsheng
"""

import os
import cv2
import numpy as np
from skimage import img_as_ubyte
from plantcv.plantcv import fatal_error
from plantcv.plantcv._debug import _debug
from plantcv.plantcv import params
from plantcv.plantcv.transform import rescale


def _preprocess_img_dtype(img):
    """ Transform the input image such that the datatype after transformation is uint8, ready for opencv functions
    :param img: inut image array
    :return:
    """
    debug_mode = params.debug
    params.debug = None
    try:
        img_ = rescale(img)
    except:
        img_ = img_as_ubyte(img)
    params.debug = debug_mode
    return img_


def overlay_two_imgs(img1, img2, alpha=0.5):
    """Overlay two images with a given alpha value.

    Inputs:
    img1     - RGB or grayscale image data
    img2     - RGB or grayscale image data
    alpha    - Desired opacity of 1st image, range: (0,1), default value=0.5

    Returns:
    out_img  - Blended RGB image

    :param img1: numpy.ndarray
    :param img2: numpy.ndarray
    :param alpha: float
    :return: out_img: numpy.ndarray
    """
    # Validate alpha
    if alpha > 1 or alpha < 0:
        fatal_error("The value of alpha should be in the range of (0,1)!")

    # Validate image sizes are the same
    size_img1 = img1.shape[0:2]
    size_img2 = img2.shape[0:2]
    if size_img1 != size_img2:
        fatal_error(f"The height/width of img1 ({size_img1}) needs to match img2 ({size_img2}).")

    # Convert the datatype of the image such that
    img1 = _preprocess_img_dtype(img1)
    img2 = _preprocess_img_dtype(img2)

    # Copy the input images
    img1_ = np.copy(img1)
    img2_ = np.copy(img2)

    # If the images are grayscale convert to BGR
    if len(img1_.shape) == 2:
        img1_ = cv2.cvtColor(img1_, cv2.COLOR_GRAY2BGR)
    if len(img2_.shape) == 2:
        img2_ = cv2.cvtColor(img2_, cv2.COLOR_GRAY2BGR)

    # initialize the output image
    out_img = np.zeros(size_img1 + (3,), dtype=np.uint8)

    # blending
    out_img[:, :, :] = (alpha * img1_[:, :, :]) + ((1 - alpha) * img2_[:, :, :])

    params.device += 1
    _debug(visual=out_img, filename=os.path.join(params.debug_outdir, str(params.device) + '_overlay.png'))

    return out_img

Update plantcv/plantcv/visualize/overlay_two_imgs.py