Potential to update utils.resize and edge-pixel corner case

[rossbar]

utils.resize branches internally calling cv2.resize for single-channel data and skimage.transforms.resize for multichannel data. Comments indicate this was done because cv2 didn't support multichannel input, but it does now. There are two potential paths for improvement:

1. Refactor utils.resize to always use cv2, which is 50-100x faster.
2. Refactor utils.resize to always use skimage, which would remove the opencv dependency from the deepcell libraries.

If utils.resize is used frequently in pre/post processing, then option 1 makes the most sense.

While digging around I also noticed that there is a discrepancy in the values of boundary pixels between the two methods:

from skimage import transform
import cv2
rng = np.random.default_rng()
img = rng.random((32, 32))
out_shape = (40, 40)
# These parameters generally match the defaults of `utils.resize`
rs_cv = cv2.resize(img, out_shape, interpolation=cv2.INTER_LINEAR)
rs_sk = transform.resize(
    img, out_shape, mode="constant", preserve_range=True, order=1, anti_aliasing=True
)
plt.imshow(rs_cv - rs_sk)
plt.colorbar()

There's no difference (within floating point precision) for the central pixels, but the discrepancy for edge pixels is significant. This may affect any workflows where single-channel and multi-channel images are used together.