59 lines
2.4 KiB
Python
59 lines
2.4 KiB
Python
def general_text_recognize(image) -> str:
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"""
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通用文本识别
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:param image: 影像件
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:return: 识别文本
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"""
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# 请求深圳快瞳通用文本识别接口
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response = http_client.post(
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url=(url := "https://ai.inspirvision.cn/s/api/ocr/general"),
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headers={
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"X-RequestId-Header": image["影像件唯一标识"]
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}, # 以影像件唯一标识作为请求唯一标识，用于双方联查
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data={
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"token": authenticator.get_token(servicer="szkt"), # 获取深圳快瞳访问令牌
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"imgBase64": f"data:image/{image["影像件格式"].lstrip(".")};base64,{image["影像件BASE64编码"]}",
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},
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guid=md5((url + image["影像件唯一标识"]).encode("utf-8")).hexdigest().upper(),
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)
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# TODO: 若响应非成功则流转至人工处理
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if not (response.get("status") == 200 and response.get("code") == 0):
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raise RuntimeError("请求深圳快瞳通用文本识别接口发生异常")
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blocks = []
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for block in response["data"]:
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# noinspection PyTypeChecker
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blocks.append(
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[
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int(block["itemPolygon"]["x"]), # 文本块左上角的X坐标
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int(block["itemPolygon"]["y"]), # 文本块左上角的Y坐标
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int(block["itemPolygon"]["height"]), # 文本块左上角的高度
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block["value"], # 文本块的文本内容
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]
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)
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# 使用俄罗斯方块方法整理文本块，先按照文本块的Y坐标升序（从上到下）
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blocks.sort(key=lambda x: x[1])
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lines = []
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for idx, block in enumerate(blocks[1:]):
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if idx == 0:
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line = [blocks[0]]
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continue
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# 若当前文本块的Y坐标和当前文本行的平均Y坐标差值小于阈值则归为同一文本行，否则另起一文本行（分行）
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if (
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block[1] - numpy.array([e[1] for e in line]).mean()
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< numpy.array([e[2] for e in line]).mean()
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):
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line.append(block)
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else:
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lines.append(line)
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line = [block]
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lines.append(line)
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blocks = []
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for line in lines:
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blocks.extend(
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[re.sub(r"\s", "", x[3]) for x in sorted(line, key=lambda x: x[0])]
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) # 按照文本块的X坐标升序（从左到右）并去除文本块的文本内容中所有空字符
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return "\n".join(blocks)
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