import json
from flask import Flask, request,jsonify
import os
import time
from datetime import datetime
import numpy as np
import base64
import cv2
""" 使用说明

一，安装
（1）请首先确保您已经具备Python运行环境
目前支持 Python 3.8 至 Python 3.12

（2）安装Python基础依赖库（注：下面依赖库版本是Windows-Python3.10环境下的，其他环境需要自行解决可能发生的错误）
pip install Flask==3.0.3 -i https://pypi.tuna.tsinghua.edu.cn/simple
pip install numpy==1.26.2 -i https://pypi.tuna.tsinghua.edu.cn/simple
pip install opencv-python==4.8.1.78 -i https://pypi.tuna.tsinghua.edu.cn/simple
pip install openai==1.66.3 -i https://pypi.tuna.tsinghua.edu.cn/simple

二，启动
python api_behaviour.py

"""

app = Flask(__name__)

@app.route('/', methods=['GET'])
def index():
    return "This is the api_behaviour.py service"

@app.route('/receiveDetectResults', methods=['POST', 'GET'])
def receiveDetectResults():
    print("receiveDetectResults()")
    """
    更新时间 2024/12/12
    适用于v4.503及其之后的版本
    适用于【模式一】,【模式二】,【模式三】,【模式四】的API行为算法调用示例1
    """
    ret = False
    msg = "未知错误"

    happen = False # True表示发生了报警，False表示未发生报警
    happenScore = 0.0 # 发生报警的置信度
    result_indices = [] # 返回过滤后检测目标的序号数组

    try:
        print("request_params=", datetime.now())
        request_params = request.get_json()
        # print(request_params)

        detects = request_params.get("detects")
        
        image_base64 = request_params.get("image_base64", None)  # 接收base64编码的图片并转换成cv2的图片格式
        print("image_base64=", datetime.now(), image_base64)
        
        if detects:
            if len(detects) > 0:
                # 如果检测目标数大于0，只提取第一个目标的序号并返回
                result_indices = [0]

        ret = True
        msg = "success"
    except Exception as e:
        msg = str(e)

    response_data = {
        "code": 1000 if ret else 0,
        "msg": msg,
        "result": {
            "happen": happen,
            "happenScore": happenScore,
            "indices": result_indices,
        }
    }
    return jsonify(response_data)

@app.route('/receiveDetectResults2', methods=['POST', 'GET'])
def receiveDetectResults2():
    print("receiveDetectResults2()")
    """
    更新时间 2025/01/08
    适用于v4.607及其之后的版本
    适用于【模式一】,【模式二】,【模式三】,【模式四】的API行为算法调用示例2
    
    最新一次更新说明：新增userdata自定义字段
    """

    ret = False
    msg = "未知错误"

    happen = False # True表示发生了报警，False表示未发生报警
    happenScore = 0.0 # 发生报警的置信度
    result_detects = [] # 返回检测的目标数组

    try:
        print("request_params=", datetime.now())
        request_params = request.get_json()
        print(request_params)

        detects = request_params.get("detects")
        if detects or True:
            # 添加一个模拟产生的目标
            result_detects.append({
                "x1": 100,
                "y1": 100,
                "x2": 300,
                "y2": 300,
                "class_score": 0.93456,
                "class_id": 0,
                "class_name": "test",
                "user_data": "hahahah",
            })
            happen = True
            happenScore = 1

        ret = True
        msg = "success"

    except Exception as e:
        msg = str(e)

    response_data = {
        "code": 1000 if ret else 0,
        "msg": msg,
        "result": {
            "happen": happen,
            "happenScore": happenScore,
            "detects": result_detects
        }
    }
    return jsonify(response_data)

@app.route('/receiveImage', methods=['POST', 'GET'])
def receiveImage():
    print("receiveImage()")
    """
    更新时间 2024/12/12
    适用于v4.503及其之后的版本
    适用于【模式五】的API行为算法调用示例
    """

    ret = False
    msg = "未知错误"

    happen = False # True表示发生了报警，False表示未发生报警
    happenScore = 0.0 # 发生报警的置信度
    happenDesc = ""  # 发生报警的描述（v4.635支持）
    result_detects = []

    try:

        request_params = request.get_json()
        # print("request_params=", datetime.now(), request_params)

        image_base64 = request_params.get("image_base64", None)  # 接收base64编码的图片并转换成cv2的图片格式
        if image_base64:
            encoded_image_byte = base64.b64decode(image_base64)
            image_array = np.frombuffer(encoded_image_byte, np.uint8)
            # image = turboJpeg.decode(image_array)  # turbojpeg 解码
            image = cv2.imdecode(image_array, cv2.COLOR_RGB2BGR)  # opencv 解码

            # video_height,video_width,video_channels = image.shape # 输入图像的的高，宽，channel
            print(image.shape)

            result_detects.append({
                "x1": 100,
                "y1": 100,
                "x2": 500,
                "y2": 500,
                "class_score": 0.93456,
                "class_id": 0,
                "class_name": "test",
                "region_index": 2,
            })

            happen = True # True 表示发生了报警
            happenScore = 1.0 # 发生报警的置信度

        ret = True
        msg = "success"

    except Exception as e:
        msg = str(e)

    response_data = {
        "code": 1000 if ret else 0,
        "msg": msg,
        "result": {
            "happen": happen,
            "happenScore": happenScore,
            "happenDesc": happenDesc,
            "detects": result_detects
        }
    }
    # return json.dumps(response_data)
    return jsonify(response_data)


if __name__ == '__main__':
    # app.debug = True
    # 推荐的json格式化网页工具：https://www.sojson.com/

    # 接口列表
    # http://127.0.0.1:8070/receiveDetectResults
    # http://127.0.0.1:8070/receiveDetectResults2
    # http://127.0.0.1:8070/receiveImage
    app.run(host='0.0.0.0', port=8070, debug=False)