+def crop(Mat, maskfile, size=None):
+ """
+ size : if filled with a (45, 45), it will search the center of maskfile then crop by center Mat
+ """
+ xmin, ymin, xmax, ymax = minmax(maskfile)
+ if size:
+ xcenter = (xmin + xmax) / 2
+ ycenter = (ymin + ymax) / 2
+
+ # crop coords
+ ymin, xmin, ymax, xmax = roundall(xcenter - size[0], ycenter - size[0],
+ xcenter + size[1], ycenter + size[1])
+
+ return Mat[xmin:xmax, ymin:ymax]
+
+def contour(Mat, maskfiles, color, thickness=1):
+ # ---------- CONTOUR POLYGON ----------
+ # thickness = -1 => fill it
+ # = 1 => just draw the contour with color
+ #
+ # return new Mat
+ contours = [getxy(maskfile) for maskfile in maskfiles] # list of list of coords,
+ # [
+ # [ (3,43), (3,4) ],
+ # [ (33,43) ]
+ # ]
+ # print("log: contours", contours)
+ if contours is not None:
+ # print('type contours', type(contours))
+ # print('contours', contours)
+ msk = np.zeros(Mat.shape, dtype=np.int32) # init all the mask with True...
+ cv2.drawContours(msk, contours, -1, True, thickness) # affect Mat, fill the polygone with False
+ msk = msk.astype(np.bool)
+ # print('msk')
+ # print(msk)
+ # print("bool", timeit(lambda:msk, number=1000))
+ # print("normal", timeit(lambda:msk.astype(np.bool), number=1000))
+ # Mat = cv2.cvtColor(Mat, cv2.COLOR_RGB2GRAY) # apply gray
+
+ # Mat = drawcontours(Mat, contours)
+ # pass
+ Mat[msk] = color # each True in msk means 0 in Mat. msk is like a selector
+ return Mat
+
+def mask(Mat, maskfile, color=0, thickness=-1):
+ # ---------- MASK POLYGON ----------
+ # thickness = -1 => fill it
+ # = 1 => just draw the contour with color
+ #
+ # return new Mat
+ contours = getxy(maskfile)
+ # print("log: contours", contours)
+ if contours is not None:
+ # print('type contours', type(contours))
+ # print('contours', contours)
+ msk = np.ones(Mat.shape, dtype=np.int32) # init all the mask with True...
+ cv2.drawContours(msk, [contours], -1, False, thickness) # affect msk, fill the polygone with False, => further, don't touch where is False
+ msk = msk.astype(np.bool)
+ # print('msk')
+ # print(msk)
+ # print("bool", timeit(lambda:msk, number=1000))
+ # print("normal", timeit(lambda:msk.astype(np.bool), number=1000))
+ # Mat = cv2.cvtColor(Mat, cv2.COLOR_RGB2GRAY) # apply gray
+
+ # Mat = drawcontours(Mat, contours)
+ # pass
+ Mat[msk] = color # each True in msk means 0 in Mat. msk is like a selector
+ return Mat
+
+
+def hollowmask(Mat, epifile, endofile, color=0, thickness=-1):
+ # ---------- MASK POLYGON ----------
+ # thickness = -1 => fill it
+ # = 1 => just draw the contour with color
+ #
+ # return new Mat
+ epicontours = getxy(epifile)
+ endocontours = getxy(endofile)
+ if epicontours is not None and endocontours is not None:
+ msk = np.ones(Mat.shape, dtype=np.int32) # init all the mask with True...
+ cv2.drawContours(msk, [epicontours], -1, False, thickness) # affect msk, fill the polygone with False, => further, don't touch where is False
+ cv2.drawContours(msk, [endocontours], -1, True, thickness) # fill the intern polygone with True, (the holow in the larger polygon), => further, color where is True with black for example
+ msk = msk.astype(np.bool)
+
+ Mat[msk] = color # each True in msk means 0 in Mat. msk is like a selector
+ return Mat
+
+
+def sqrmask1(Mat, maskfile):
+ # ---------- SQUARE MASK 1st approach ----------
+ # print( timeit( lambda:sqrmask1(img, epimask), number=1000 ) ) # 0.48110522600000005
+ # return new Mat
+ xmin, ymin, xmax, ymax = minmax(maskfile)
+ # print("xmin, ymin, xmax, ymax", xmin, ymin, xmax, ymax)
+
+ i = 0
+ while i < ymin:# search by top
+ Mat[i].fill(0)# paint the row in black
+ i += 1
+
+ i = len(Mat) - 1
+ while i > ymax:# search by bottom
+ Mat[i].fill(0)# paint the row in black
+ i -= 1
+
+ i = 0
+ while i < xmin:# search by top
+ Mat.T[i, ymin:ymax+1].fill(0) # paint the column (row of the Transpose) in black, ymin and ymax to optimize, cause, I previously painted a part
+ i += 1
+
+ i = len(Mat.T) - 1
+ while i > xmax:# search by bottom
+ Mat.T[i, ymin:ymax+1].fill(0) # paint the column (row of the Transpose) in black, ymin and ymax to optimize, cause, I previously painted a part
+ i -= 1
+
+ return Mat
+
+def sqrmask2(Mat, maskfile):
+ # ---------- SQUARE MASK 2nd and best approach ----------
+ # print( timeit( lambda:sqrmask2(img, epimask), number=1000 ) ) # 0.3097705270000001
+ # return new Mat
+ xmin, ymin, xmax, ymax = minmax(maskfile)
+ # print("xmin, ymin, xmax, ymax", xmin, ymin, xmax, ymax)
+
+ msk = np.ones(Mat.shape, dtype=np.int32) # init all the mask with True...
+ msk = msk.astype(np.bool)
+
+ msk[ymin:ymax, xmin:xmax] = False # for after, don't touch between min and max region
+ Mat[msk] = 0
+
+ return Mat
+
