animation/fourcell/calibrate.py

import sys
import cv2
import numpy as np
import math
from os.path import exists, basename
from common import image_resize, display, normalize_angle
from json import load

#clockwise from top left
order = [ 0, 2, 3, 5, 4, 1 ]
matchMethods = ['cv2.TM_CCOEFF', 'cv2.TM_CCOEFF_NORMED', 'cv2.TM_CCORR',
            'cv2.TM_CCORR_NORMED', 'cv2.TM_SQDIFF', 'cv2.TM_SQDIFF_NORMED']

def read_text (textPath) :
	holePunches = {}
	with open(textPath) as json:
		holePunches = load(json)
	return holePunches

#
# CALIBRATE
#

if len(sys.argv) < 2:
	print('Please provide path of normalized scan to calibrate to')
	exit(1)

if len(sys.argv) < 3:
	print('Please provide path to output svg template')
	exit(2)

normalImage = sys.argv[-2]

if not exists(normalImage) :
	print('Normalized scan does not exist, please provide one that does')
	exit(2)

normalText = normalImage + '.json'

if not exists(normalText) :
	print('Corresponding normalized scan text does not exist, please generate one')
	exit(3)

outputTmpl = sys.argv[-1]

print(f'Calibrating to scan {basename(normalImage)}')

registrationMark = cv2.imread('./registration_mark.png', 0)
w, h = registrationMark.shape[:2]
holePunches = read_text(normalText)
original = cv2.imread(normalImage)
img = original.copy()
height, width = img.shape[:2]
orientation = height > width

if not orientation :
	print(f'Scan is not in portrait mode, exiting...')
	exit(3)

print(holePunches)

topHalf = img[holePunches['0']['y']:holePunches['1']['y']+round(height*0.1), holePunches['0']['x']:holePunches['2']['x']]
topHalfGray = cv2.cvtColor(topHalf, cv2.COLOR_BGR2GRAY)
res = cv2.matchTemplate(topHalfGray, registrationMark, cv2.TM_CCOEFF_NORMED)
threshold = 0.5
loc = np.where( res >= threshold)
for pt in zip(*loc[::-1]):
	print(f'{pt[0]},{pt[1]}')
	cv2.rectangle(topHalf, pt, (pt[0] + w, pt[1] + h), (0,0,255), 2)

display(topHalf)