en2cn/Utils/main_line_e2cc.py

"""
-------------------------------------------------
# @File     :line_composition
# @Date     :2022/7/15
# @Author   :inshine
-------------------------------------------------
"""
import cv2
import numpy as np
import base64
import requests
import re
import my_config
from uuid import uuid1
from shapely.geometry import Polygon


URL_API_PREFIX = "ai_cv_hwr"
# PyTorch_REST_API_URL = "http://192.168.1.209:7015/{0}/{1}"
# PyTorch_REST_API_URL = "http://10.19.1.43:7015/{0}/{1}"
# PyTorch_REST_API_URL = "http://api.cv.zxhx.com/{0}/{1}"


def get_image_base64(image):
    """
    将各来源的图片转为base64编码，先默认为本地图片路径
    :param image:
    :return:
    """
    # print("image:", str(image))
    if re.search("^https?:", str(image)):  # 远程图片
        filebyte = requests.get(image).content
    elif re.search("^[A-H]:", str(image)):  # 本地图片
        local_img = image
        filebyte = open(local_img, 'rb').read()
    else:  # 二进制文件流
        filebyte = image.read()
    # encoded = base64.b64encode(open(local_img, 'rb').read())

    base64_data = base64.b64encode(filebyte).rstrip().decode('utf-8')
    return base64_data


def generate_uuid():
    return str(uuid1()).replace('-', '')


def get_image_url_base64(img_url):
    response = requests.get(img_url)
    base64_byte = base64.encodebytes(response.content)
    return base64_byte.decode('utf-8')


def calc_polygon_center(points):
    polygon = Polygon(points)
    point = polygon.centroid
    return point.x, point.y


def recognition_line(img_base64, img_url, img_source, line_coordinate, rec_method=0):
    """
    英译汉中文识别接口
    :param img_base64: 图片的base64编码
    :param img_url: 图片url地址
    :param img_source: 产品种类：英译汉词汇、英译汉短语
    :param line_coordinate: 是否返回坐标：OPEN/CLOSE
    :param rec_method: -1 -- baidu, 0 -- random 50%, 1 -- AI-CV, default is 0
    :return:
    """
    img_matrix = cv2.imdecode(np.frombuffer(base64.b64decode(img_base64), np.uint8), cv2.IMREAD_COLOR)
    img_shape = img_matrix.shape
    img_width, img_height = img_shape[1], img_shape[0]
    poly = np.array([[0, 0], [img_width, 0], [img_width, img_height], [0, img_height]])
    cx, cy = calc_polygon_center(poly)
    det_index_list = [[f"{cy}_{cx}"]]
    det_polygon_dict = {f"{cy}_{cx}": {"Polygon": poly.tolist(), "Confidence": 1.0}}
    det_matrix_dict = {f"{cy}_{cx}": img_base64}

    request_data = {
        "RequestID": generate_uuid(),
        "DetectionResult": {'ImageWidth': img_width, "ImageHeight": img_height,
                            "IndexList": det_index_list, "PolygonDict": det_polygon_dict,
                            "DetMatrixDict": det_matrix_dict},
        "ImageURL": img_url,
        "ImageSource": img_source,
        "LineCoordinate": line_coordinate,
        "RecMethod": rec_method,
        "AccessToken": "75ad010a0c353d1f9173db20077bb715"
    }

    print(my_config.PyTorch_REST_API_URL.format(URL_API_PREFIX, "recognitionChineseLine"))
    result = requests.post(my_config.PyTorch_REST_API_URL.format(URL_API_PREFIX, "recognitionChineseLine"),
                           headers={'Content-Type': "application/json;charset=utf-8"},
                           json=request_data)
    result = result.json()
    print(result)
    if result["errCode"] == "00":
        return result["data"]["message"]
    else:
        return None


if __name__ == '__main__':
    import time
    image_url = "http://zxhx-w-1302712961.cos.ap-chengdu.myqcloud.com/PP/CScut/601/980294985259646976/900195828017442864/36.jpg"
    t1 = time.time()
    image_base64 = get_image_url_base64(image_url)
    print(time.time() - t1)
    # data = recognition_line(image_base64, image_url, "英译汉词汇", "CLOSE")