Refactor and improve image resizing

Is your feature request related to a problem? Please describe. The function plantcv.resize could be improved in a few ways. It currently allows for resizing the x and y dimensions using scaling factors, but resizing to an exact size may be desirable also. We also use a single, fixed interpolation method that may not yield optimal results in all cases.

Describe the solution you’d like I propose a few modifications to plantcv.resize and a new function.

1. Move plantcv.resize to the transform subpackage: plantcv.transform.resize. This is both because it is a transformation of the input image and it’s consistent with scikit-image.
2. Refactor plantcv.transform.resize to resize images to an exact size.
3. In plantcv.transform.resize, if the new size is smaller than the input size, use the OpenCV interpolation method cv2.INTER_AREA. If the new size is larger than the input size, use the interpolation method cv2.INTER_CUBIC. (These are the generally recommended options, but we could point a user to the OpenCV function if they want more control than what we provide).
4. Make a new function called something like plantcv.transform.resize_factor that combines the new features proposed for plantcv.transform.resize but uses the current feature of scaling the sizes by factors rather than exact sizes.
5. To avoid redundancy, it may be useful to have a helper function set the interpolation method.

Describe alternatives you’ve considered These functions could be wrapped into one like the OpenCV function, but I think it’s simpler to have two smaller functions rather than twice the inputs to one.

[dschneiderch]

@nfahlgren probably not necessary. i can’t think of any applications for shear or skew over warp. it can always be revisited.

[nfahlgren]

Hi @DannieSheng, it did come to my mind while I was reviewing your PR! I realized that the resize function you proposed there does not use interpolation though, it either crops or pads as you said. Maybe now that I think about it, these could potentially be one function?

def resize(img, size, interpolation=True):
    # img = numpy.ndarray
    # size = tuple
    # interpolation = bool

    img_area = img.shape[0] * img.shape[1]
    new_area = size[0] * size[1]

    if interpolation:
        if new_area >= img_area:
            resized = cv2.resize(img, dsize=size, interpolation=cv2.INTER_CUBIC)
        else:
            resized = cv2.resize(img, dsize=size, interpolation=cv2.INTER_AREA)
    else:
        if new_area >= img_area:
            # pad
        else:
            # crop
    return resized