def imghTest(img_path):
image = None
image_path = img_path
# load default image if image is left blank
if not img_path:
dbg.dprintln(
INFO, "NO IMAGE PATH SPECIFIED, LOADING DEFAULT IMAGE: " +
cfg.DEFAULT_IMAGE_PATH)
image_path = cfg.DEFAULT_IMAGE_PATH
dbg.dprintln(VERBOSE, "imghTest() image_path = " + image_path, 1)
# test case 1: check if file exists (THIS CHECKS FROM OUR CURRENT PATH)
ret_val = imgh.imageExists(image_path)
dbg.dprintln(INFO,
"imghTest() image_exists() = " + rv.getRetString(ret_val), 1)
# test case 2: convert image to grayscale
if ret_val == rv.SUCCESS:
[ret_val, image] = imgh.readImageGrayscale(image_path)
elif ret_val == rv.ERROR_NO_FILE:
dbg.dprintln(INFO, "NO FILE AT SPECIFIED PATH")
elif ret_val == rv.ERROR_NO_IMAGE:
dbg.dprintln(INFO, "NO IMAGE AT SPECIFIED PATH")
return [ret_val, image]
def imghTest(img_path):
image = None
dbg.dprintln(VERBOSE, "imghTest() img_path = " + img_path, 1)
# test case 1: check if file exists (THIS CHECKS FROM OUR CURRENT PATH)
ret_val = imgh.imageExists(img_path)
dbg.dprintln(INFO,
"imghTest() image_exists() = " + rv.getRetString(ret_val), 1)
# test case 2: convert image to grayscale
if ret_val == rv.SUCCESS:
[ret_val, image] = imgh.readImageGrayscale(img_path)
return [ret_val, image]
def globalThresholding(image):
new_image = image.copy()
threshold = find_optimal_threshold(compute_histogram(new_image))
dbg.dprintln(VERBOSE, "Threshold is: " + str(threshold), 2)
for row in range(new_image.shape[0]):
for col in range(new_image.shape[1]):
if new_image[row, col] >= threshold:
new_image[row, col] = 255
else:
new_image[row, col] = 0
return [new_image, threshold]
def compute_histogram(image):
hist = [0] * 256
for row in range(image.shape[0]):
for col in range(image.shape[1]):
pixel_val = image[row, col]
if pixel_val >= 0 and pixel_val < 256:
hist[pixel_val] = hist[pixel_val] + 1
else:
dbg.dprintln(
CRITICAL, "Found erroneous pixel value: " +
str(pixel_val) + " at " + str(row) + ", " + str(col), 2)
return hist
def main():
dbg.enable()
# SET DEBUG LEVEL
dbg.setLevel(ALL)
dbg.dprintln(INFO, "test.py main() started")
#
# start test functions
#
# image handler testing
# ./image or image all works
[ret_val, image] = imghTest("./image/_raw/oscar_wilde_1.jpg")
if ret_val == rv.SUCCESS:
# TESTING GRAYSCALE DISCRETATION AND BIMODAL IMAGES
# discrete grayscale image
imgh.writeImage(imgh.BW, "test_image_discretegrayscale.jpg", image)
# inverted test
invert_image = imgh.invert(image)
imgh.writeImage(imgh.BW, "test_image_inverted_discretegrayscale.jpg",
invert_image)
# user defined threshold image + threshold value
[user_image,
user_threshold] = imgh.imageToBimodal(imgh.USER_THRESH, image, 220)
imgh.writeImage(imgh.BIN, "test_image_bimodal_user.jpg", user_image)
# global defined threshold image + global threshold value
[global_image,
global_threshold] = imgh.imageToBimodal(imgh.GLOBAL_THRESH, image)
imgh.writeImage(imgh.BIN, "test_image_bimodal_global.jpg",
global_image)
# TEST MORPHOLOGIES
# erosion
ret_image = mo.erode(user_image, 1)
imgh.writeImage(imgh.BIN, "test_image_bimodal_user_erode.jpg",
ret_image)
ret_image = mo.dilate(user_image, 1)
imgh.writeImage(imgh.BIN, "test_image_bimodal_user_dilation.jpg",
ret_image)
ret_image = mo.open(user_image, 1)
imgh.writeImage(imgh.BIN, "test_image_bimodal_user_open.jpg",
ret_image)
ret_image = mo.close(user_image, 1)
imgh.writeImage(imgh.BIN, "test_image_bimodal_user_close.jpg",
ret_image)
#
# end test functions
#
dbg.dprintln(INFO, "test.py main() ended")
def readImageGrayscale(abs_image_path, binarize=False):
if abs_image_path is not None:
# success
if imageExists(abs_image_path) == retval.SUCCESS:
image = cv2.imread(abs_image_path, cv2.IMREAD_GRAYSCALE)
return [retval.SUCCESS, image]
# bad file path
else:
dbg.dprintln(
CRITICAL,
"readImageGrayscale() invalid image path, no file found")
return [retval.ERROR_NO_FILE, None]
# bad input argument abs_image_path
else:
dbg.dprintln(CRITICAL, "readImageGrayscale() no image path defined")
return [retval.ERROR_NO_IMAGE, None]
def find_optimal_threshold(hist):
# init counters
max_lo = 0
max_hi = 0
lo_cnt = 0
hi_cnt = 0
# init threshold
threshold = len(hist) // 2
# find the avg prob val before and after threshold
for x in range(len(hist)):
if x < threshold:
max_lo = max_lo + x * hist[x]
lo_cnt = lo_cnt + hist[x]
else:
max_hi = max_hi + x * hist[x]
hi_cnt = hi_cnt + hist[x]
# calc threshold value
max_lo = max_lo // lo_cnt
max_hi = max_hi // hi_cnt
threshold = (max_lo + max_hi) // 2
dbg.dprintln(
VERBOSE, "Threshold value is: " + str(threshold) + " with maximas: " +
str(max_lo) + ", " + str(max_hi), 2)
return threshold
def writeImage(type, filename, image):
if (".jpg" in str(filename)):
if type == BW:
dbg.dprintln(INFO, "writeImage() Writing BW file " + str(filename),
1)
path = "image/bw/" + str(filename)
cv2.imwrite(path, image)
elif type == BIN:
dbg.dprintln(INFO,
"writeImage() Writing BINARY file " + str(filename),
1)
path = "image/binary/" + str(filename)
cv2.imwrite(path, image)
else:
dbg.dprintln(
INFO,
"writeImage() Type is not BW or BINARY, not writing image " +
str(filename), 1)
else:
dbg.dprintln(
INFO,
"writeImage() .JPG extension not found in filename, not writing image "
+ str(filename), 1)
def Function(): dbg.dprintln(CRITICAL, "Text from a function")
from debug import debug as dbg # These values can be used as integers, they wont change in value # if you specify an integer HIGHER than 3 then everything will show # CRITICAL = 0 # INFO = 2 # VERBOSE = 3 # ALL = 4 CRITICAL = dbg.CRITICAL INFO = dbg.INFO VERBOSE = dbg.VERBOSE ALL = dbg.ALL # # Printing with control over output # dbg.dprintln(INFO, "INFO is too high, this wont print") dbg.dprintln(VERBOSE, "Verbose is too high, this wont print") dbg.dprintln(ALL, "ALL is too high this wont print") # # Printing without a newline # has optional 3rd argument for tabs # dbg.dprintHeader(CRITICAL) dbg.dprint(CRITICAL, "Text without") dbg.dprint(CRITICAL, " a newline") dbg.dprint(CRITICAL, "and one tab ", 1) dbg.dprint(CRITICAL, "in the middle\n") #
def imageToBimodal(type, image, threshold=127):
dbg.dprintln(INFO,
"imageToBimodal(): threshold specified " + str(threshold))
# invalid threshold value, return
if threshold < 0 or threshold > 255:
dbg.dprintln(CRITICAL, "Invalid threshold value: " + str(threshold), 1)
# check for type and return the threshold
elif type == NO_THRESH:
dbg.dprintln(INFO, "No threshold, returning raw image untouched", 1)
# user specified bimodal threshold
elif type == USER_THRESH:
dbg.dprintln(INFO, "User threshold specified " + str(threshold), 1)
image = userThresholding(image, threshold)
# global threshold
elif type == GLOBAL_THRESH:
dbg.dprintln(
INFO,
"Global threshold, automatically finding optimal threshold based on histogram"
)
[image, threshold] = globalThresholding(image)
# not yet implemented
else:
dbg.dprintln(CRITICAL, "Thresholding mode has no valid implementation")
return [image, threshold]
def main():
dbg.enable()
# SET DEBUG LEVEL
dbg.setLevel(ALL)
dbg.dprintln(INFO, "test.py main() started")
#
# start test functions
#
# image handler testing
# ./image or image all works
# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", type=str, help="path to input image")
ap.add_argument(
"-c",
"--conversion",
type=aph.conversion2int,
default=cfg.CONVERSION_ARG_BW,
help="intermediate image conversion: 'bw' or 'bin'; defaults to 'bw'")
ap.add_argument(
"-t",
"--threshold",
type=int,
help="define an integer threshold for bimodal image conversion: (0-255)"
)
ap.add_argument(
"-m",
"--morph",
type=aph.morph2int,
help=
"define any number of morphological operations separated by commas: 'erode', 'dilate', 'open' or 'close'"
)
ap.add_argument("--invert",
type=aph.str2bool,
default=False,
help="invert image?:'t' or 'f'; defaults to False")
args = vars(ap.parse_args())
# load the input image
[ret_val, image] = imghTest(args["image"])
if ret_val == rv.SUCCESS:
# TESTING GRAYSCALE DISCRETATION AND BIMODAL IMAGES
intermediate_image = None
if args["conversion"] == cfg.CONVERSION_ARG_BW:
# discrete grayscale image
imgh.writeImage(imgh.BW, "test_image_discretegrayscale.jpg", image)
# inverted test
if args["invert"]:
intermediate_image = imgh.invert(image)
imgh.writeImage(imgh.BW,
"test_image_inverted_discretegrayscale.jpg",
intermediate_image)
elif args["conversion"] == cfg.CONVERSION_ARG_BIN:
if args["threshold"]:
# user defined threshold image + threshold value
[intermediate_image,
user_threshold] = imgh.imageToBimodal(imgh.USER_THRESH, image,
args["threshold"])
imgh.writeImage(imgh.BIN, "test_image_bimodal_user.jpg",
intermediate_image)
else:
# global defined threshold image + global threshold value
[intermediate_image, global_threshold
] = imgh.imageToBimodal(imgh.GLOBAL_THRESH, image)
imgh.writeImage(imgh.BIN, "test_image_bimodal_global.jpg",
intermediate_image)
# TEST MORPHOLOGIES
# erosion
if not args["morph"]:
dbg.dprintln(
INFO,
"No morphological operation defined; operation will not be applied to image"
)
else:
for morph_arg in args["morph"]:
if morph_arg == cfg.MORPH_ARG_ERODE:
ret_image = mo.erode(intermediate_image, 1)
imgh.writeImage(imgh.BIN,
"test_image_bimodal_user_erode.jpg",
ret_image)
if morph_arg == cfg.MORPH_ARG_DILATE:
ret_image = mo.dilate(intermediate_image, 1)
imgh.writeImage(imgh.BIN,
"test_image_bimodal_user_dilation.jpg",
ret_image)
if morph_arg == cfg.MORPH_ARG_OPEN:
ret_image = mo.open(intermediate_image, 1)
imgh.writeImage(imgh.BIN,
"test_image_bimodal_user_open.jpg",
ret_image)
if morph_arg == cfg.MORPH_ARG_CLOSE:
ret_image = mo.close(intermediate_image, 1)
imgh.writeImage(imgh.BIN,
"test_image_bimodal_user_close.jpg",
ret_image)
# TEST
#
# end test functions
#
dbg.dprintln(INFO, "test.py main() ended")