def main():
pixel = read_image('txt.jpg') / 255
bbox = BboxGeneratorV2(pixel, is_corrected=True).gen_bboxes()
for box in bbox:
img = read_image('txt.jpg')
area = get_text_area_from_bbox(img, box)
write_image('area.jpg', area)
def main():
for i in range(10):
start_time = time.time()
text_area = read_image('imgs/txt.jpg')
gap_area = read_image('imgs/gap.jpg')
bbox_generator = ContainerBboxGenerate(text_area / 255, gap_area / 255)
bbox_generator.gen_bbox()
print(time.time() - start_time)
def main():
img = read_image('1.jpg')
shape = img.shape
# img = cv2.resize(img, (int(shape[1] / 2), int(shape[0] / 2)))
color_extractor = ColorExtractor(img)
res = color_extractor.extract_color()
write_image('2.jpg', res * 255)
def main():
img = read_image('2.jpg') / 255
img[np.where(img > 0.6)] = 1
img[np.where(img <= 0.6)] = 0
connected_domains = get_connected_domains_list(img)
for index, domain in enumerate(connected_domains):
write_image('cont' + str(index) + '.jpg', domain * 255)
def main():
original_pixel = cv2.imread('pxl.jpg')[:, :, 0] / 255
bbox_gen = ObliqueBBOXGenerator(original_pixel)
oblique_bbox = bbox_gen.get_oblique_bbox()
img = read_image('imgs/1.jpg')
areas = bbox_gen.get_transparent_text_area(img, oblique_bbox)
for area in areas:
write_image('ar.jpg', area)
def __load_char_mapping():
"""
"""
char_mapping = {}
char_paths = get_all_files_under_directory(CHAR_DIR)
for p in char_paths:
_, name = os.path.split(p)
label = name.split('_')[0]
img = read_image(p)
if label not in char_mapping:
char_mapping[label] = []
char_mapping[label] = img
return char_mapping
def save_image(image_str, i, file_name):
if enlarge_radio == 1:
image_path = TRAINING_DATA_DIR + file_name.replace('.json',
'') + '.jpg'
else:
image_path = TRAINING_DATA_DIR + file_name.replace('.json', '') + \
str(enlarge_radio).replace('.', '_') + '.jpg'
fh = open(image_path, "wb")
fh.write(base64.b64decode(image_str))
fh.close()
img = read_image(image_path)
shape = img.shape
img = cv2.resize(
img, (int(shape[1] * enlarge_radio), int(shape[0] * enlarge_radio)))
write_image(image_path, img)
def main():
# img = to_gray(img)
# mean_value = img.mean()
# print(mean_value)
# paths = get_all_files_under_directory('E:/qianfen_area')
# for path in paths:
# img = read_image(path)
# img = enlighten_image_np(111, img)
# _, name = os.path.split(path)
# write_image('E:/new_area/' + name, img)
""""""
img = read_image('1.jpg')
img = lpls_enlighten(img)
write_image('2.jpg', img)
def main():
txt_and_image_paths = 'D:/label_result_2020_3_10/label_result/箱门中文字识别/txt'
des_line_dir = 'D:/label_result_2020_3_10/label_result/箱门中文字识别/line/'
paths = get_all_file_from_dir(txt_and_image_paths)
try:
for i, p in enumerate(paths):
if '.jpg' not in p:
continue
img_name = os.path.split(p)[1].replace('.jpg', '')
img = read_image(p)
txt_path = p.replace('.jpg', '.txt')
points, is_error = get_points(txt_path)
if is_error:
print(p)
draw_image = get_detect_result(points, img)
write_image(des_line_dir + img_name + '.jpg', draw_image)
except Exception as e:
print(e)
def main():
mask = read_image('text.jpg') / 255
gap = read_image('gap.jpg') / 255
new_mask = mask * gap * 255
write_image('new_mask.jpg', new_mask)
def main():
pixel = read_image('imgs/pixl.jpg') / 255
bbox = BboxGeneratorV5(pixel, is_corrected=True).gen_bboxes()
print(bbox)
def main():
pixel = read_image('imgs/1.jpg') / 255
pass
# -*- coding: utf-8 -*-
"""
-------------------------------------------------
File Name： get_all_file_path
Description :
Author : 'li'
date： 2020/1/18
-------------------------------------------------
Change Activity:
2020/1/18:
-------------------------------------------------
"""
import os
from llib.cv_utility.image_opt_utility import read_image, write_image
from utility.file_path_utility import get_all_files_under_directory
img_dir = 'J:/BaiduNetdiskDownload/0506'
des_path = 'J:/BaiduNetdiskDownload/plate_recognize/img/'
paths = get_all_files_under_directory(img_dir)
for path in paths:
_, name = os.path.split(path)
image = read_image(path)
write_image(des_path + name, image)
def main():
points = [[642, 592], [724, 658], [724, 692], [652, 628]]
img = read_image('imgs/1.jpg')
res = draw_points(points, img)
write_image('imgs/ll.jpg', res)
