eccfixup.py

#!/usr/bin/env python3

import os
import sys
import numpy as np
import cv2 as cv

np.set_printoptions(suppress=True)


im = cv.imread("BrOry.jpg", cv.IMREAD_UNCHANGED)
(height, width) = im.shape[:2]

roi = (rx, ry, rw, rh) = (166, 158, 219, 112)

(B,G,R) = np.transpose(im, axes=(2,0,1))

cv.imshow("B", B[ry:ry+rh, rx:rx+rw])
cv.imshow("G", G[ry:ry+rh, rx:rx+rw])
cv.imshow("R", R[ry:ry+rh, rx:rx+rw])
cv.waitKey(1)

M_blue = np.eye(3, dtype=np.float32)
M_red = np.eye(3, dtype=np.float32)

if os.path.exists("M_blue.npy"):
	M_blue = np.load("M_blue.npy")

if os.path.exists("M_red.npy"):
	M_red = np.load("M_red.npy")

#termcrit = (cv.TERM_CRITERIA_COUNT | cv.TERM_CRITERIA_EPS, 50, 0.001)
termcrit = (cv.TERM_CRITERIA_COUNT | cv.TERM_CRITERIA_EPS, 20, 0.5e-3)
gaussFiltSize = 5 # default 5

motionType = cv.MOTION_HOMOGRAPHY
#motionType = cv.MOTION_AFFINE
#motionType = cv.MOTION_EUCLIDEAN

if motionType == cv.MOTION_HOMOGRAPHY:
	Mrows = 3
else:
	Mrows = 2
	M_red[2] = (0,0,1)
	M_blue[2] = (0,0,1)

print("ECC blue...", end=" ", flush=True)
(rv, res) = cv.findTransformECC(
	templateImage=G,
	inputImage=B,
	warpMatrix=M_blue[:Mrows],
	motionType=motionType,
	criteria=termcrit,
	inputMask=None,
	gaussFiltSize=gaussFiltSize
)
print(f"done. ECC = {rv:.4f}")
M_blue[:Mrows] = res
np.save("M_blue.npy", M_blue)
print(M_blue)


print("ECC red...", end=" ", flush=True)
(rv, res) = cv.findTransformECC(
	templateImage=G,
	inputImage=R,
	warpMatrix=M_red[:Mrows],
	motionType=motionType,
	criteria=termcrit,
	inputMask=None,
	gaussFiltSize=gaussFiltSize
)
print(f"done. ECC = {rv:.4f}")
M_red[:Mrows] = res
np.save("M_red.npy", M_red)
print(M_red)


#B_warped = cv.warpAffine(R, M[0:2,0:3], (width, height), flags=cv.WARP_INVERSE_MAP | cv.INTER_LINEAR)
B_warped = cv.warpPerspective(B, M_blue, (width, height), flags=cv.WARP_INVERSE_MAP | cv.INTER_CUBIC)
R_warped = cv.warpPerspective(R, M_red, (width, height), flags=cv.WARP_INVERSE_MAP | cv.INTER_CUBIC)

cv.imshow("B_warped", B_warped[ry:ry+rh, rx:rx+rw])
cv.imshow("R_warped", R_warped[ry:ry+rh, rx:rx+rw])

composite = np.dstack([B_warped, G, R_warped])
cv.imwrite("composite.png", composite)
print("composite written")

cv.waitKey(-1)
cv.destroyAllWindows()