# Import FastAPI Libs
from pydantic import BaseModel

# Import Qcloud OCR Service Libs
from tencentcloud.common import credential
from tencentcloud.common.profile.client_profile import ClientProfile
from tencentcloud.common.profile.http_profile import HttpProfile
from tencentcloud.common.exception.tencent_cloud_sdk_exception import TencentCloudSDKException
from tencentcloud.ocr.v20181119 import ocr_client, models

# Import Other Common Libs
import json
import base64
import os

# ------------------------------------------------
# Define constants
# ------------------------------------------------
c_ret_code_success = 0
c_ret_code_error = 1

region = 'ap-shanghai'
user_name = 'ocr-program'
credential_file = '/home/oracle/python/apex/credential/credential.json'
# credential_file = 'C://PyCharmProjects//qcloud-service//config//credential.json'


# ------------------------------------------------
# Define OCR Request Service Request and Response
# ------------------------------------------------
class ocr_req_basemodel(BaseModel):
    ocr_tool: str # Q: Qcloud, LP: Local PaddleOCR
    dir: str
    file_name: str

class ocr_res_basemodel(BaseModel):
    result: int
    result_message: str
    detected_text: list


# ------------------------------------------------
# Get credentials
# ------------------------------------------------
def get_credentials(file: str, user_name: str) -> tuple:

    try:
        # Open and read the JSON file
        with open(file, "r") as credential_file:
            data = json.load(credential_file)

        # Access data from the JSON
        secret_id = data['ocr'][user_name]['secret_id']
        secret_key = data['ocr'][user_name]['secret_key']

        return secret_id, secret_key

    except Exception as e:

        print(e)
        return None, None


# ------------------------------------------------
# Function of OCR request to Qcloud COS
# ------------------------------------------------
def get_detected_text(ocr_req: ocr_req_basemodel) -> tuple:

    ret_code = c_ret_code_success
    err_msg = ""

    try:
        secret_id, secret_key = get_credentials(credential_file, user_name)
        # 实例化一个认证对象，入参需要传入腾讯云账户 SecretId 和 SecretKey，此处还需注意密钥对的保密
        # 代码泄露可能会导致 SecretId 和 SecretKey 泄露，并威胁账号下所有资源的安全性。以下代码示例仅供参考，建议采用更安全的方式来使用密钥，请参见：https://cloud.tencent.com/document/product/1278/85305
        # 密钥可前往官网控制台 https://console.cloud.tencent.com/cam/capi 进行获取
        cred = credential.Credential(secret_id, secret_key)
        # 实例化一个http选项，可选的，没有特殊需求可以跳过
        httpProfile = HttpProfile()
        httpProfile.endpoint = "ocr.tencentcloudapi.com"

        # 实例化一个client选项，可选的，没有特殊需求可以跳过
        clientProfile = ClientProfile()
        clientProfile.httpProfile = httpProfile
        # 实例化要请求产品的client对象,clientProfile是可选的
        client = ocr_client.OcrClient(cred, region, clientProfile)

        # 打开文件
        file_location = os.path.normpath(os.path.join(ocr_req.dir, ocr_req.file_name))
        with open(file_location, "rb") as image_file:
            encoded_string = base64.b64encode(image_file.read()).decode('utf-8')
            # print(encoded_string)
        # Remove file
        os.remove(file_location)

        # 实例化一个请求对象,每个接口都会对应一个request对象
        req = models.GeneralHandwritingOCRRequest()
        params = {
            "ImageBase64": encoded_string
        }
        req.from_json_string(json.dumps(params))

        # 返回的resp是一个GeneralHandwritingOCRResponse的实例，与请求对象对应
        resp = client.GeneralHandwritingOCR(req)
        # 输出json格式的字符串回包
        # print(resp.to_json_string())

        list_detected_text = []

        for text_detection in (json.loads(resp.to_json_string()))['TextDetections']:
            # print(text_detection['DetectedText'])
            list_detected_text.append(text_detection['DetectedText'])

        ocr_res = ocr_res_basemodel(
            result          = ret_code,
            result_message  = err_msg,
            detected_text   = list_detected_text
        )

        return ocr_res

    except TencentCloudSDKException as err:

        ret_code = c_ret_code_error
        err_msg = str(err)

        ocr_res = ocr_res_basemodel(
            result          = ret_code,
            result_message  = err_msg,
            detected_text   = []
        )

        return ocr_res