def testImageTransformBatch(self):
file_path = "/Users/superCat/Desktop/PycharmProjectPortable/test/spam_test1.txt"
read_file_path = "/Users/superCat/Desktop/PycharmProjectPortable/test/Image_Samples/"
save_file_path = "/Users/superCat/Desktop/PycharmProjectPortable/test/Image_Filtered/"
FileIO.FileHandler.create_file_if_not_exist(save_file_path)
domain_list = FileIO.FileHandler.read_lines_from_file(file_path)
for item in domain_list:
print("doing: item:", item)
peak_scale_factor = 0.9
image_path = read_file_path + item + ".png"
matrix, width, height = read_image(image_path)
new_matrix, one_d_array, average = get_1d_array(
matrix, 255, height, width, 0.5, 0.97)
first_ref, second_ref, min_ref, min_v = find_peak(
one_d_array,
max_value=height,
average_scale=peak_scale_factor,
amplitude_scale=0.3,
min_deviation=3)
insert_line(new_matrix, first_ref, 50)
insert_line(new_matrix, second_ref, 50)
insert_line(new_matrix, min_ref, 50)
insert_line(new_matrix,
int(average * peak_scale_factor),
200,
is_vertical=False)
formated = png.from_array(new_matrix, mode='L')
new_path = save_file_path + item + ".png"
formated.save(new_path)
def testImageTransform1(self):
peak_scale_factor = 0.9
image_path = "/Users/superCat/Desktop/PycharmProjectPortable/test/Image_Samples/3xstar.net.png"
matrix, width, height = read_image(image_path)
new_matrix, one_d_array, average = get_1d_array(matrix, 255, height, width, 0.5, 0.97)
first_ref, second_ref, min_ref, min_v = find_peak(one_d_array,
max_value=height, average_scale=peak_scale_factor,
amplitude_scale=0.3, min_deviation=3)
insert_line(new_matrix, first_ref, 50)
insert_line(new_matrix, second_ref, 50)
insert_line(new_matrix, min_ref, 50)
insert_line(new_matrix, int(average*peak_scale_factor), 200, is_vertical=False)
formated = png.from_array(new_matrix, mode='L')
new_path = "/Users/superCat/Desktop/PycharmProjectPortable/test/test_filterd1.png"
formated.save(new_path)
im = Image.open(new_path)
im.show()
def testRead(self):
image_path = "/Users/superCat/Desktop/PycharmProjectPortable/test/BacklinkHistoryChart.png"
new_image_path = "/Users/superCat/Desktop/PycharmProjectPortable/test/Image/{0:d}.png"
matrix = []
reader = png.Reader(filename=image_path)
pixel_dict = {}
w, h, pixels, metadata = reader.asRGBA()
for row in pixels:
matrix.append(row)
for pixcel in row:
if pixcel in pixel_dict.keys():
v = pixel_dict[pixcel]
pixel_dict.update({pixcel: v + 1})
else:
pixel_dict.update({pixcel: 1})
height = len(matrix)
width = len(matrix[0])
print("height:", height, "width:", width)
print("variations:")
sort = [
x for x in sorted(pixel_dict.items(),
key=lambda pixel_count: pixel_count[1],
reverse=True) if 20000 > x[1] > 50
]
count = 0
for item in sort:
new_matrix = []
for row in matrix:
new_row = []
for pixel in row:
if pixel == item[0]:
new_row.append(255)
else:
new_row.append(0)
new_matrix.append(new_row)
formated = png.from_array(new_matrix, mode='L')
new_path = new_image_path.format(item[0], )
FileIO.FileHandler.create_file_if_not_exist(new_path)
formated.save(new_path)
count += 1
if count == 10:
break
def testRead(self):
image_path = "/Users/superCat/Desktop/PycharmProjectPortable/test/BacklinkHistoryChart.png"
new_image_path = "/Users/superCat/Desktop/PycharmProjectPortable/test/Image/{0:d}.png"
matrix = []
reader = png.Reader(filename=image_path)
pixel_dict = {}
w, h, pixels, metadata = reader.asRGBA()
for row in pixels:
matrix.append(row)
for pixcel in row:
if pixcel in pixel_dict.keys():
v = pixel_dict[pixcel]
pixel_dict.update({pixcel: v+1})
else:
pixel_dict.update({pixcel: 1})
height = len(matrix)
width = len(matrix[0])
print("height:", height, "width:", width)
print("variations:")
sort = [x for x in sorted(pixel_dict.items(), key=lambda pixel_count: pixel_count[1], reverse=True) if 20000> x[1] > 50]
count = 0
for item in sort:
new_matrix= []
for row in matrix:
new_row = []
for pixel in row:
if pixel == item[0]:
new_row.append(255)
else:
new_row.append(0)
new_matrix.append(new_row)
formated = png.from_array(new_matrix, mode='L')
new_path = new_image_path.format(item[0],)
FileIO.FileHandler.create_file_if_not_exist(new_path)
formated.save(new_path)
count += 1
if count == 10:
break
def testImageTransformBatch(self):
file_path = "/Users/superCat/Desktop/PycharmProjectPortable/test/spam_test1.txt"
read_file_path = "/Users/superCat/Desktop/PycharmProjectPortable/test/Image_Samples/"
save_file_path = "/Users/superCat/Desktop/PycharmProjectPortable/test/Image_Filtered/"
FileIO.FileHandler.create_file_if_not_exist(save_file_path)
domain_list = FileIO.FileHandler.read_lines_from_file(file_path)
for item in domain_list:
print("doing: item:", item)
peak_scale_factor = 0.9
image_path = read_file_path + item + ".png"
matrix, width, height = read_image(image_path)
new_matrix, one_d_array, average = get_1d_array(matrix, 255, height, width, 0.5, 0.97)
first_ref, second_ref, min_ref, min_v = find_peak(one_d_array,
max_value=height, average_scale=peak_scale_factor,
amplitude_scale=0.3, min_deviation=3)
insert_line(new_matrix, first_ref, 50)
insert_line(new_matrix, second_ref, 50)
insert_line(new_matrix, min_ref, 50)
insert_line(new_matrix, int(average*peak_scale_factor), 200, is_vertical=False)
formated = png.from_array(new_matrix, mode='L')
new_path = save_file_path + item + ".png"
formated.save(new_path)
def testImageTransform1(self):
peak_scale_factor = 0.9
image_path = "/Users/superCat/Desktop/PycharmProjectPortable/test/Image_Samples/3xstar.net.png"
matrix, width, height = read_image(image_path)
new_matrix, one_d_array, average = get_1d_array(
matrix, 255, height, width, 0.5, 0.97)
first_ref, second_ref, min_ref, min_v = find_peak(
one_d_array,
max_value=height,
average_scale=peak_scale_factor,
amplitude_scale=0.3,
min_deviation=3)
insert_line(new_matrix, first_ref, 50)
insert_line(new_matrix, second_ref, 50)
insert_line(new_matrix, min_ref, 50)
insert_line(new_matrix,
int(average * peak_scale_factor),
200,
is_vertical=False)
formated = png.from_array(new_matrix, mode='L')
new_path = "/Users/superCat/Desktop/PycharmProjectPortable/test/test_filterd1.png"
formated.save(new_path)
im = Image.open(new_path)
im.show()
