fourcell/apply_image.py

@@ -1,99 +0,0 @@
-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}')

fourcell/calibrate.py

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

fourcell/common.py

@@ -1,6 +1,5 @@
 import cv2
 import math
-from json import load
 
 def image_resize(image, width = None, height = None, inter = cv2.INTER_AREA):
     dim = None
@@ -120,10 +119,4 @@ 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
-
-def read_json (textPath) :
-    jsonOut = {}
-    with open(textPath) as json:
-        jsonOut = load(json)
-    return jsonOut
+    return res