Compare commits

...

2 Commits

3 changed files with 110 additions and 10 deletions

99
fourcell/apply_image.py Normal file
View File

@ -0,0 +1,99 @@
import sys
import cv2
import numpy as np
from json import load
from os.path import exists, basename
from common import image_resize, display, read_json
holeConstant = .0156862745 # 160/10200
# use top left, top right, bottom left
def apply_image_to_points (original, target, points) :
rows, cols, ch = original.shape
ir, ic, ich = target.shape
print('Using points: ')
print(points)
atPts = np.float32(points)
targetPts = np.float32([[0, 0], [ic, 0], [0, ir]])
M = cv2.getAffineTransform(targetPts, atPts)
dst = cv2.warpAffine(target, M, (cols, rows), borderMode=cv2.BORDER_TRANSPARENT)
output = original.copy()
output[0:rows, 0:cols] = dst
return output
def create_blank(width, height):
rgb_color=(255,255,255)
image = np.zeros((height, width, 3), np.uint8)
color = tuple(reversed(rgb_color))
image[:] = color
gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
return cv2.cvtColor(gray, cv2.COLOR_GRAY2RGB)
# get points 0, 1 and 3 = top left, top right and bottom left
def to_points (d) :
return ((d['0']['x'], d['0']['y']),(d['1']['x'], d['1']['y']),(d['3']['x'], d['3']['y']),)
if len(sys.argv) < 2 :
print('Please provide an output destination file')
exit(1)
outputFile = sys.argv[1]
if len(sys.argv) < 3:
print('Please provide a calibration template to apply images to')
exit(2)
templateFile = sys.argv[2]
if not exists(templateFile) :
print('Calibration template does not exist, please provide one that does')
exit(3)
if len(sys.argv) < 4:
print('Please provide at least one image to apply')
exit(4)
if len(sys.argv) > 7:
print('Please provide maximum four images to apply')
exit(5)
images = []
for i in range(3, len(sys.argv)):
imagePath = sys.argv[i]
if not exists(imagePath) :
print(f'Image {imagePath} does not exist, exiting...')
exit(6)
images.append(imagePath)
print('Using images: ')
for img in images:
print(f' -> {basename(img)}')
tmpl = read_json(templateFile)
print(f"Image size {tmpl['width']}x{tmpl['height']}")
hole = round(tmpl['width'] * holeConstant)
#blank = create_blank(tmpl['width'], tmpl['height'])
output = cv2.imread(templateFile.replace('.calibration.json', ''))#blank.copy()
hp = tmpl['holePunches']
for i in hp:
print(hp[i])
cv2.circle(output, (hp[i]['x'], hp[i]['y'],), hole, (0, 0, 0,), -1)
#cv2.imwrite(outputFile, output)
for i in range(0, len(images)) :
frame = cv2.imread(images[i])
output = apply_image_to_points(output, frame, to_points(tmpl[f'{i}']))
print(f'Applied {basename(images[i])}')
cv2.imwrite(outputFile, output)
print(f'Wrote {outputFile}')

View File

@ -3,8 +3,8 @@ 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,dumps
from common import image_resize, display, normalize_angle, read_json
from json import dumps
DEBUG = True
@ -12,12 +12,6 @@ DEBUG = True
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
#
@ -44,7 +38,7 @@ print(f'Calibrating to scan {basename(normalImage)}')
registrationMark = cv2.imread('./registrationMark.png', 0)
w, h = registrationMark.shape[:2]
holePunches = read_text(normalText)
holePunches = read_json(normalText)
original = cv2.imread(normalImage)
img = original.copy()
height, width = img.shape[:2]

View File

@ -1,5 +1,6 @@
import cv2
import math
from json import load
def image_resize(image, width = None, height = None, inter = cv2.INTER_AREA):
dim = None
@ -119,4 +120,10 @@ def normalize_angle (num, lower=0.0, upper=360.0, b=False):
res = num * 1.0 # Make all numbers float, to be consistent
return res
return res
def read_json (textPath) :
jsonOut = {}
with open(textPath) as json:
jsonOut = load(json)
return jsonOut