def __init__(self, inputString, type):
# todo: validate inputs
# inputString: The image encoded
# type: type of encoding (only base64 atm)
self.__sourceImage = ClairesImage(inputString, type)
class ClairesCutter:
def __init__(self, inputString, type):
# todo: validate inputs
# inputString: The image encoded
# type: type of encoding (only base64 atm)
self.__sourceImage = ClairesImage(inputString, type)
def getSourceImage(self):
return self.__sourceImage
def getPositions(self):
# Array of image positions in the form:
# {
# "red": [[[x1,y1],[x2,y2]], [[x1,y1],[x2,y2]], [[x1,y1],[x2,y2]]],
# "green": [[[x1,y1],[x2,y2]], [[x1,y1],[x2,y2]], [[x1,y1],[x2,y2]]],
# "blue": [[[x1,y1],[x2,y2]], [[x1,y1],[x2,y2]], [[x1,y1],[x2,y2]]]
# }
results = {"red": [], "green": [], "blue": []}
sourceImage = self.__sourceImage
image = sourceImage.getOpenCV()
original = image.copy()
width, height = image.shape[:2]
if width > 1000 and height > 1000:
# todo: make divider dynamic
sourceImage.shrinkImage(5)
image = sourceImage.getImage()
openCVImageBinary = sourceImage.getOpenCVBinary()
img, contours, hierarchy = cv2.findContours(
openCVImageBinary.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE
)
for contour in contours:
area = cv2.contourArea(contour)
if area < 2000:
continue
if len(contour) < 4:
continue
rect = cv2.minAreaRect(contour)
color = self.getColor(contour)
origin = (rect[0][0] * sourceImage.getDivider(), rect[0][1] * sourceImage.getDivider())
size = (rect[1][0] * sourceImage.getDivider(), rect[1][1] * sourceImage.getDivider())
rotationAngle = rect[2]
transformedRect = (origin, size, rotationAngle)
results[color].append(transformedRect)
return results
# Return the mean color on a path
def getColor(self, pathArray):
image = self.__sourceImage.getOpenCV()
mask = np.zeros(image.shape[:2], np.uint8)
cv2.drawContours(mask, pathArray, -1, 255, -1)
meanValues = cv2.mean(image, mask=mask)
maxIndex = meanValues.index(max(meanValues))
return indexToColor(maxIndex)
# Restore proportions of image
def restoreImage(self):
self.__sourceImage.restoreImage()
# Returns copy of the source image with its original proportions
# Here is a good place to optimize the memory footprint
def getOriginal(self):
sourceImage = deepcopy(self.__sourceImage)
sourceImage.restoreImage()
return sourceImage
def crop(self, rect):
sourceImage = self.getOriginal()
image = sourceImage.getOpenCV()
box = cv2.boxPoints(rect)
box = np.int0(box)
W = rect[1][0]
H = rect[1][1]
Xs = [i[0] for i in box]
Ys = [i[1] for i in box]
x1 = min(Xs)
x2 = max(Xs)
y1 = min(Ys)
y2 = max(Ys)
angle = rect[2]
# Center of rectangle in source image
center = ((x1 + x2) / 2, (y1 + y2) / 2)
# Size of the upright rectangle bounding the rotated rectangle
size = (x2 - x1, y2 - y1)
M = cv2.getRotationMatrix2D((size[0] / 2, size[1] / 2), angle, 1.0)
# Cropped upright rectangle
cropped = cv2.getRectSubPix(image, size, center)
cropped = cv2.warpAffine(cropped, M, size)
croppedRotated = cv2.getRectSubPix(cropped, (int(W), int(H)), (size[0] / 2, size[1] / 2))
return croppedRotated