import os
from os.path import isdir, join
from os import mkdir
+from timeit import timeit
import pydicom
from pprint import pprint
import numpy as np
import pathlib
import json
+from scipy import ndimage
+from scipy import misc
+
+
from decimal import Decimal as d, ROUND_HALF_UP as rhu
+# locals
+from helpers import drawcontours
+
+np.set_printoptions(edgeitems=372, linewidth=1200)# hey numpy, take advantage of my large screen
+
PNG16_MAX = pow(2, 16) - 1 # here if thinks the heaviest weight bit is for transparency or something not in use with dicom imgs
PNG8_MAX = pow(2, 8+1) - 1 # heaviest weight bit is 8 => 2**8, but dont forget the others: the reason of +1
INPUT_DIR = '../../Data/Images_anonymous/Case_0002/'
OUT_DIR = './generated/'
-#os.mkdir(outdir)
+
+CROP_SIZE = (45, 45) # (width, height)
+RED_COLOR = 100
def roundall(*l):
- return (round(e) for e in l)
+ return (int(round(e)) for e in l)
def ftrim(Mat):
+ # ---------- FTRIM ----------
# private func to trim the Matrix, but in one direction, vertically | horizontally
# return the slice, don't affect the Matrix
- # y | : for column, x -> : for rows
+ # y | : for (top to bottom), x -> : for (left to right)
# v
# not my fault, numpy architecture
+
y1 = y2 = i = 0
+
while i < len(Mat):# search by top
if Mat[i].max() > 0:
y1 = i
break
i += 1
+
i = len(Mat) - 1
while i >= 0:# search by bottom
if Mat[i].max() > 0:
# print('horizontal:vertical', horizontal, vertical)
return Mat[horizontal, vertical]
-def mask(Mat, maskfile):
- # return
- xmin, ymin, xmax, ymax = minmax(Mat, maskfile)
-
- y1 = y2 = i = 0
- while i < len(Mat):# search by top
- if i < ymin:
- Mat[i].fill(0)# paint the row in black
- else: break
- i += 1
-
- i = len(Mat) - 1
- while i >= 0:# search by bottom
- if i > ymax:
- Mat[i].fill(0)# paint the row in black
- else: break
- i -= 1
- # print('y1, y2', y1, y2)
- # return slice(y1, y2+1)# +1 to stop at y2
-
-
-def minmax(Mat, file):
+def getxy(file):
"""
{
'Image00001': [{
]
}]
}
- return xmin, ymin, xmax, ymax
+ return [(94.377, 137.39), ...]
"""
with open(file) as jsonfile:
data = json.load(jsonfile)
- pprint(data)
-
- for imgXXX in data:pass # get the value of key ~= "Image00001", cause it's dynamic
-
- for obj in data[imgXXX]:pass # get the object that contains the points, cause it's a list
- points = obj['points']
+ # pprint(data)
+
+ for imgXXX in data: pass # get the value of key ~= "Image00001", cause it's dynamic
+ for obj in data[imgXXX]: pass # get the object that contains the points, cause it's a list
+ points = obj['points']
# print("print, ", data)
# print("imgXXX, ", imgXXX)
# print("points, ", points)
# print("imgXXX, ", obj['points'])
- tmp = [(pt['x'], pt['y']) for pt in points ] # extract x,y. {'x': 94.377, 'y': 137.39} => (94.377, 137.39)
- r = np.array(tmp)
-
- print(r) # log
-
+ tmp = [np.array( (round(pt['x']), round(pt['y'])) ).astype(np.int32) for pt in
+ points] # extract x,y. {'x': 94.377, 'y': 137.39} => (94.377, 137.39)
+ return np.array(tmp, dtype=np.int32)
+ # return tmp
+
+def minmax(file):
+ r = getxy(file)
+ if r is not None:
+ # print(r) # log
xmin, ymin = np.min(r, axis=0)
xmax, ymax = np.max(r, axis=0)
- print('xmax, ymax', xmax, ymax)
- print('xmin, ymin', xmin, ymin)
+ # print('xmax, ymax', xmax, ymax)
+ # print('xmin, ymin', xmin, ymin)
return roundall(xmin, ymin, xmax, ymax)
+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
+
def map16(array):# can be useful in future
return array * 16
def getdir(filepath):
return '/'.join(filepath.split('/')[:-1]) + '/'
-def topng(inputfile, outfile=None, overwrite=True, verbose=False):
+def readpng(inputfile):# just a specific func to preview a "shape = (X,Y,3)" image
+ image = misc.imread(inputfile)
+
+ print("image")
+ print("image.shape", image.shape)
+
+ for tab in image:
+ for i, row in enumerate(tab):
+ print(row[0]*65536 + row[0]*256 + row[0], end=" " if i % image.shape[0] != 0 else "\n")
+
+def topng(inputfile, outfile=None, overwrite=True, verbose=False, epimask='', endomask='', centercrop=None, blackmask=False, square=False, redcontour=False):
"""
(verbose) return (64, 64) : the width and height
(not verbose) return (img, dicimg) : the image and the dicimg objects
+ centercrop : it's a size (45, 45), to mention I want to crop by center of epimask and by size.
+ blackmask : draw the outside with black
+
"""
try:
dicimg = pydicom.read_file(inputfile) # read dicom image
except pydicom.errors.InvalidDicomError as e:
# @TODO: log, i can't read this file
return
- img = trim(dicimg.pixel_array)# get image array (12bits)
+ # img = trim(dicimg.pixel_array)# get image array (12bits), Don't trim FOR THE MOMENT
+ img = dicimg.pixel_array# get image array (12bits)
# test <<
# return img.shape # $$ COMMENT OR REMOVE THIS LINE
# affine transfo to png 16 bits, func affects img variable
maxdepth = pow(2, dicimg.BitsStored) - 1
- print('dicimg.BitsStored, (img.min(), img.max())', dicimg.BitsStored, (img.min(), img.max())) # testing..
+ # print('dicimg.BitsStored, (img.min(), img.max())', dicimg.BitsStored, (img.min(), img.max())) # testing..
+ if int(dicimg.BitsStored) < 12:
+ print("\n\n\n-----{} Bits-----\n\n\n\n".format(dicimg.BitsStored))
affine(img,
(0, maxdepth), # img.min() replace 0 may be, but not sure it would be good choice
(0, PNG16_MAX if maxdepth > PNG8_MAX else PNG8_MAX)
)
- mask(img, '/Users/user/Desktop/Master/Stage/Data/json/json_GT/0_Case_0002/contours/1.2.3.4.5.6/31/-85.9968/Epicardic.json')
+ # test <<
+ # imgray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
+ # ret,thresh = cv2.threshold(img,127,255,0)
+ # im2, contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
+ # print("im2, contours, hierarchy", im2, contours, hierarchy)
+ # test >>
+
+ # return img
+
+ # print("log: epimask", epimask)
+
+ if epimask:
+ if redcontour:
+
+ contours = [epimask] # list of list of coords
+ if endomask:contours.append(endomask)
+ img = contour(img, contours, color=RED_COLOR, thickness=1)
+
+ if blackmask:# if is there a mask => apply
+ if square:
+ img = sqrmask2(img, epimask)
+ else:
+ if endomask:
+ img = hollowmask(img, epimask, endomask)
+ else:
+ img = mask(img, epimask)
+
+ if centercrop:
+ img = crop(img, epimask, centercrop)
+
+
+ # return
+ # test
+ # if verbose:
+ # return img, dicimg, minmax(epimask)
+ # else:
+ # return img.shape
savepath = (outfile or inputfile) + '.png'
savedir = getdir(savepath)
# np.savetxt(savepath + '.npy', img)
# test >>
- cv2.imwrite(savepath, img, [cv2.IMWRITE_PNG_COMPRESSION, 0]) # write png image
+ if np.count_nonzero(img) > 0: # matrix not full of zero
+ cv2.imwrite(savepath, img, [cv2.IMWRITE_PNG_COMPRESSION, 0]) # write png image
+
+ # print("ndimage.imread(savepath)", ndimage.imread(savepath).shape)
+ # print( ndimage.imread(savepath) )
+ # print("np.expand_dims(ndimage.imread(savepath), 0)", np.expand_dims(ndimage.imread(savepath), 0).shape)
+ # print(np.expand_dims(ndimage.imread(savepath), 0))
# test
if verbose:
- return img, dicimg
+ return img, dicimg, minmax(epimask)
else:
return img.shape
if __name__ == '__main__':
# topngs( INPUT_DIR, join(OUT_DIR, INPUT_DIR.split('/')[-2]) )
- topng(INPUT_DIR+'Image00003', OUT_DIR + INPUT_DIR.split('/')[-2] +'-Image00003')
+ readpng(OUT_DIR+'aug_circle.png')
+ # topng(INPUT_DIR+'Image00003', OUT_DIR + INPUT_DIR.split('/')[-2] +'-Image00003', epimask="/Users/user/Desktop/Master/Stage/Data/json/json_GT/0_Case_0002/contours/1.2.3.4.5.6/31/-85.9968/Epicardic.json")
