def xianyu(test_folder, show=False, write_img=True):
all_imgs = glob.glob(test_folder + "/**")
for input_path_img in all_imgs:
postfix = input_path_img.split(".")[-1].lower()
if postfix not in ["jpeg", "jpg", "png"]:
continue
name = os.path.basename(input_path_img).split('.')[0]
org = cv2.imread(input_path_img)
img = utils.resize_by_height(org, resize_height=800)
compo = detect_compo(img, show=show)
text = ocr.ocr(org, resize_height=800, show=show)
compo_merge, categories = merge.incorporate(img,
compo,
text,
show=show)
utils.draw_bounding_box_class(
img,
compo_merge,
categories,
output=pjoin(test_folder,
str(name) + '_det.png'),
)
utils.save_corners_json(pjoin(test_folder,
str(name) + '_det.json'), compo_merge,
categories)
def ocr(img, resize_height=800, output_path=None, show=False):
start = time.clock()
data = pyt.image_to_data(img)
bboxes = []
# level|page_num|block_num|par_num|line_num|word_num|left|top|width|height|conf|text
for d in data.split('\n')[1:]:
d = d.split()
conf = d[10]
if int(conf) != -1:
bboxes.append([
int(d[6]),
int(d[7]),
int(d[6]) + int(d[8]),
int(d[7]) + int(d[9])
])
bboxes = merge_text(bboxes)
bboxes = resize_label(bboxes, img.shape[0], resize_height)
resize_img = utils.resize_by_height(img, resize_height)
utils.draw_bounding_box(resize_img,
bboxes,
name='ocr',
color=(255, 6, 6),
show=show)
if output_path is not None:
utils.save_corners_json(output_path + '.json', bboxes, 'Text')
# print('OCR [%.3fs] %s' % (time.clock() - start, img_path))
return bboxes
def xianyu(input_path_img, output_path, num, show=False, write_img=False):
start = time.clock()
org = cv2.imread(input_path_img)
img = utils.resize_by_height(org, resize_height=800)
compo = detect_compo(img,
show=show,
output_path=output_path.replace(
'rico_xianyu_bg_ocr', 'rico_xianyu_bg_cv'))
text = ocr.ocr(org, show=show)
compo_merge, categories = merge.incorporate(img, compo, text, show=show)
utils.draw_bounding_box_class(img, compo_merge, categories, show=show)
utils.draw_bounding_box_class(img,
compo_merge,
categories,
name='non-text',
non_text=True,
show=show)
# compo_merge = merge.merge_intersected_compo(compo_merge)
utils.draw_bounding_box(img, compo_merge, name='merged', show=show)
utils.save_corners_json(output_path + '.json', compo_merge, categories)
print('[%.3fs] %d %s' % (time.clock() - start, num, input_path_img))
def xianyu(input_img_root='E:\\Mulong\\Datasets\\rico\\combined',
output_root='E:\\Mulong\\Result\\rico\\rico_xianyu\\rico_xianyu_bg_ocr',
show=False, write_img=False):
data = json.load(open('E:\\Mulong\\Datasets\\rico\\instances_test.json', 'r'))
input_paths_img = [pjoin(input_img_root, img['file_name'].split('/')[-1]) for img in data['images']]
input_paths_img = sorted(input_paths_img, key=lambda x: int(x.split('\\')[-1][:-4])) # sorted by index
num = 0
start_index = 3762
end_index = 100000
for input_path_img in input_paths_img:
index = input_path_img.split('\\')[-1][:-4]
if int(index) < start_index:
continue
if int(index) > end_index:
break
start = time.clock()
org = cv2.imread(input_path_img)
img = utils.resize_by_height(org, resize_height=800)
compo = detect_compo(img, show=show)
text = ocr.ocr(org, show=show)
compo_merge, categories = merge.incorporate(img, compo, text, show=show)
utils.draw_bounding_box_class(img, compo_merge, categories)
utils.save_corners_json(pjoin(output_root, str(index) + '.json'), compo_merge, categories)
print('[%.3fs] %d %s' % (time.clock() - start, num, input_path_img))
num += 1
def detect_compo(org, output_path=None, show=False):
start = time.clock()
grad = gradient_laplacian(org)
rm_noise_flood_fill(grad, show=False)
compo_bbox = []
slicing(grad, compo_bbox, (0, 0), show=False)
utils.draw_bounding_box(org, compo_bbox, show=show)
if output_path is not None:
utils.save_corners_json(output_path + '.json', compo_bbox, np.full(len(compo_bbox), 'Compo'))
# print('Compo det [%.3fs]' % (time.clock() - start))
return compo_bbox
def xianyu(input_path_img, output_path, show=False):
start = time.clock()
org = cv2.imread(input_path_img)
img = utils.resize_by_height(org, resize_height=800)
compo = detect_compo(img, show=show)
text = ocr.ocr(org, show=show)
compo_merge, categories = merge.incorporate(img, compo, text, show=show)
output_path_img = output_path.split('.')[0] + '.png'
output_path_json = output_path.split('.')[0] + '.json'
utils.draw_bounding_box_class(img,
compo_merge,
categories,
output=output_path_img)
utils.save_corners_json(output_path_json, compo_merge, categories)
print('[%.3fs] %s' % (time.clock() - start, input_path_img))