animation/fourcell/calibrate.py

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Python
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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)