百度控制台地址：https://console./ai/#/ai/ocr/overview/index
直接通过urllib去按照API文档调用接口便可，唯一需要注意的是API文档里要求image在base64编码后进行urlencode，但是实际上只需要base64编码便可
# !/user/bin/env Python3# -*- coding:utf-8 -*-"""file：baidu_api.pycreate time:/4/10 15:14author:Loong Xudesc: 调用百度OCRapi实现文本识别"""import base64from urllib import parse, requestimport jsondef GetAccessToken(ak, sk):'''获取access_token代码:param ak:控制台应用API Key:param sk:控制台应用Secret Key:return:返回接口调用的access_token参数以及token的有效期（单位为秒）'''# client_id 为官网获取的AK， client_secret 为官网获取的SKhost = '/oauth/2.0/token?grant_type=client_credentials&client_id=%s&client_secret=%s' % (ak, sk)headers = {'Content-Type': 'application/json; charset=UTF-8'}req = request.Request(method='GET', url=host, headers=headers)response = request.urlopen(req)if (response.status == 200):data = json.loads(response.read().decode())access_token = data['access_token']expires_in = data['expires_in']return access_token, expires_indef RecogniseForm(access_token, image, templateSign=None, classifierId=None):"""自定义模板文字识别:param access_token::param image:图像数据（string），base64编码，注意大小不超过4M，最短边至少15px，最长边最大4096px，支持jpg/png/bmp格式:param templateSign:模板ID（string）:param classifierId:分类器ID（int），这个参数与templateSign至少存在一个，优先使用templateSign，存在templateSign时，使用指定模板；如果没有templateSign而有classifierld，表示使用分类器去判断使用模板:return:返回识别结果"""host = '/rest/2.0/solution/v1/iocr/recognise?access_token=%s' % access_tokenheaders = {'Content-Type': 'application/x-www-form-urlencoded'}formdata = {'image': image}if templateSign is not None:formdata['templateSign'] = templateSignif classifierId is not None:formdata['classifierId'] = classifierIddata = parse.urlencode(formdata).encode('utf8')req = request.Request(method='POST', url=host, headers=headers, data=data)response = request.urlopen(req)if (response.status == 200):jobj = json.loads(response.read().decode())datas = jobj['data']recognise = {}for obj in datas['ret']:recognise[obj['word_name']] = obj['word']return recognisedef RecogniseGeneral(access_token, image=None, url=None, recognize_granularity='big', language_type='CHN_ENG',detect_direction=False, detect_language=False, vertexes_location=False, probability=False):'''通用文字识别（含位置信息）:param access_token:URL参数，需要拼接到接口URL上:param image:图像数据，base64编码，要求base64编码后大小不超过4M，最短边至少15px，最长边最大4096px,支持jpg/png/bmp格式，当image字段存在时url字段失效:param url:图片完整URL，URL长度不超过1024字节，URL对应的图片base64编码后大小不超过4M，最短边至少15px，最长边最大4096px,支持jpg/png/bmp格式，当image字段存在时url字段失效，不支持https的图片链接:param recognize_granularity:是否定位单字符位置，big：不定位单字符位置，默认值；small：定位单字符位置:param language_type:识别语言类型，默认为CHN_ENG。可选值包括：- CHN_ENG：中英文混合；- ENG：英文；- POR：葡萄牙语；- FRE：法语；- GER：德语；- ITA：意大利语；- SPA：西班牙语；- RUS：俄语；- JAP：日语；- KOR：韩语:param detect_direction:是否检测图像朝向，默认不检测，即：false。朝向是指输入图像是正常方向、逆时针旋转90/180/270度。可选值包括:- true：检测朝向；- false：不检测朝向。:param detect_language:是否检测语言，默认不检测。当前支持（中文、英语、日语、韩语）:param vertexes_location:是否返回文字外接多边形顶点位置，不支持单字位置。默认为false:param probability:是否返回识别结果中每一行的置信度:return:'''host = '/rest/2.0/ocr/v1/general?access_token=%s' % access_tokenheaders = {'Content-Type': 'application/x-www-form-urlencoded'}formdata = {'recognize_granularity': recognize_granularity, 'language_type': language_type,'detect_direction': detect_direction, 'detect_language': detect_language,'vertexes_location': vertexes_location, 'probability': probability}if image is not None:formdata['image'] = imageelif url is not None:formdata['url'] = urldata = parse.urlencode(formdata).encode('utf8')req = request.Request(method='POST', url=host, headers=headers, data=data)response = request.urlopen(req)if (response.status == 200):jobj = json.loads(response.read().decode())datas = jobj['words_result']recognise = {}for obj in datas:recognise[obj['words']] = obj['location']return recognisedef Recognise(img_path):access_token, expires_in = GetAccessToken(ak, sk) # 将此ak与sk替换成自己应用的值with open(file=img_path, mode='rb') as file:base64_data = base64.b64encode(file.read())# 调用iOCR自定义模板文字识别接口# recognise = RecogniseForm(access_token=access_token, image=base64_data,templateSign=templateSign) # 将此templateSign替换成自己设置的模板值recognise = RecogniseGeneral(access_token=access_token, image=base64_data)for k, v in recognise.items():print(k, v)Recognise(r'C:\Users\Administrator\Desktop\1.jpg')
