def __init__(self,
MAX_HORIZONTAL_GAP=30,
MIN_V_OVERLAPS=0.6,
MIN_SIZE_SIM=0.6):
"""
pass
"""
self.text_proposal_connector = TextProposalConnector(
MAX_HORIZONTAL_GAP, MIN_V_OVERLAPS, MIN_SIZE_SIM)
class TextDetector:
"""
Detect text from an image
"""
def __init__(self,
MAX_HORIZONTAL_GAP=30,
MIN_V_OVERLAPS=0.6,
MIN_SIZE_SIM=0.6):
"""
pass
"""
self.text_proposal_connector = TextProposalConnector(
MAX_HORIZONTAL_GAP, MIN_V_OVERLAPS, MIN_SIZE_SIM)
def detect(self,
text_proposals,
scores,
size,
TEXT_PROPOSALS_MIN_SCORE=0.7,
TEXT_PROPOSALS_NMS_THRESH=0.3,
TEXT_LINE_NMS_THRESH=0.3,
MIN_RATIO=1.0,
LINE_MIN_SCORE=0.8,
TEXT_PROPOSALS_WIDTH=5,
MIN_NUM_PROPOSALS=1):
"""
Detecting texts from an image
:return: the bounding boxes of the detected texts
@@param:TEXT_PROPOSALS_MIN_SCORE:TEXT_PROPOSALS_MIN_SCORE=0.7##过滤字符box阀值
@@param:TEXT_PROPOSALS_NMS_THRESH:TEXT_PROPOSALS_NMS_THRESH=0.3##nms过滤重复字符box
@@param:TEXT_LINE_NMS_THRESH:TEXT_LINE_NMS_THRESH=0.3##nms过滤行文本重复过滤阀值
@@param:MIN_RATIO:MIN_RATIO=1.0#0.01 ##widths/heights宽度与高度比例
@@param:LINE_MIN_SCORE:##行文本置信度
@@param:TEXT_PROPOSALS_WIDTH##每个字符的默认最小宽度
@@param:MIN_NUM_PROPOSALS,MIN_NUM_PROPOSALS=1##最小字符数
"""
#text_proposals, scores=self.text_proposal_detector.detect(im, cfg.MEAN)
keep_inds = np.where(scores > TEXT_PROPOSALS_MIN_SCORE)[0] ###
text_proposals, scores = text_proposals[keep_inds], scores[keep_inds]
sorted_indices = np.argsort(scores.ravel())[::-1]
text_proposals, scores = text_proposals[sorted_indices], scores[
sorted_indices]
# nms for text proposals
if len(text_proposals) > 0:
keep_inds = nms(np.hstack((text_proposals, scores)),
TEXT_PROPOSALS_NMS_THRESH) ##nms 过滤重复的box
text_proposals, scores = text_proposals[keep_inds], scores[
keep_inds]
scores = normalize(scores)
text_lines = self.text_proposal_connector.get_text_lines(
text_proposals, scores, size) ##合并文本行
return text_lines
else:
return []
class TextDetector:
"""
Detect text from an image
"""
def __init__(self,
MAX_HORIZONTAL_GAP=30,
MIN_V_OVERLAPS=0.6,
MIN_SIZE_SIM=0.6):
"""
pass
"""
self.text_proposal_connector = TextProposalConnector(
MAX_HORIZONTAL_GAP, MIN_V_OVERLAPS, MIN_SIZE_SIM)
def detect(self,
text_proposals,
scores,
size,
TEXT_PROPOSALS_MIN_SCORE=0.3,
TEXT_PROPOSALS_NMS_THRESH=0.3,
TEXT_LINE_NMS_THRESH=0.3,
MIN_RATIO=1.0,
LINE_MIN_SCORE=0.8,
TEXT_PROPOSALS_WIDTH=5,
MIN_NUM_PROPOSALS=1):
"""
:param text_proposals:
:param scores:
:param size:
:param TEXT_PROPOSALS_MIN_SCORE 过滤字符box阀值
:param TEXT_PROPOSALS_NMS_THRESH: nms过滤重叠box
:param TEXT_LINE_NMS_THRESH: nms过滤行文本重复过滤阀值
:param MIN_RATIO: widths/heights宽度与高度比例
:param LINE_MIN_SCORE: 行文本置信度
:param TEXT_PROPOSALS_WIDTH: 每个文本框的默认最小宽度
:param MIN_NUM_PROPOSALS: 最小bbox数
:return: the bounding boxes of the detected texts after some filter
"""
sorted_index = np.argsort(scores.ravel())[::-1]
text_proposals, scores = text_proposals[sorted_index], scores[
sorted_index]
# nms for text proposals
if len(text_proposals) > 0:
keep_inds = nms(np.hstack((text_proposals, scores)),
TEXT_PROPOSALS_NMS_THRESH) ##nms 过滤重复的box
text_proposals, scores = text_proposals[keep_inds], scores[
keep_inds]
scores = normalize(scores)
text_boxes = self.text_proposal_connector.get_text_lines(
text_proposals, scores, size) ##合并文本行
return text_boxes
else:
return []