添加api服务器
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005api测试服务.py
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005api测试服务.py
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import json
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from flask import Flask, request,jsonify
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import os
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import time
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from datetime import datetime
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import numpy as np
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import base64
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import cv2
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""" 使用说明
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一，安装
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（1）请首先确保您已经具备Python运行环境
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目前支持 Python 3.8 至 Python 3.12
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（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）
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pip install Flask==3.0.3 -i https://pypi.tuna.tsinghua.edu.cn/simple
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pip install numpy==1.26.2 -i https://pypi.tuna.tsinghua.edu.cn/simple
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pip install opencv-python==4.8.1.78 -i https://pypi.tuna.tsinghua.edu.cn/simple
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pip install openai==1.66.3 -i https://pypi.tuna.tsinghua.edu.cn/simple
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二，启动
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python api_behaviour.py
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"""
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app = Flask(__name__)
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@app.route('/', methods=['GET'])
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def index():
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return "This is the api_behaviour.py service"
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@app.route('/receiveDetectResults', methods=['POST', 'GET'])
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def receiveDetectResults():
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print("receiveDetectResults()")
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"""
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更新时间 2024/12/12
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适用于v4.503及其之后的版本
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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
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"""
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ret = False
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msg = "未知错误"
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happen = False # True表示发生了报警，False表示未发生报警
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happenScore = 0.0 # 发生报警的置信度
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result_indices = [] # 返回过滤后检测目标的序号数组
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try:
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print("request_params=", datetime.now())
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request_params = request.get_json()
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# print(request_params)
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detects = request_params.get("detects")
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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
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print("image_base64=", datetime.now(), image_base64)
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if detects:
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if len(detects) > 0:
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# 如果检测目标数大于0，只提取第一个目标的序号并返回
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result_indices = [0]
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ret = True
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msg = "success"
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except Exception as e:
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msg = str(e)
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response_data = {
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"code": 1000 if ret else 0,
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"msg": msg,
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"result": {
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"happen": happen,
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"happenScore": happenScore,
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"indices": result_indices,
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}
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}
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return jsonify(response_data)
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@app.route('/receiveDetectResults2', methods=['POST', 'GET'])
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def receiveDetectResults2():
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print("receiveDetectResults2()")
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"""
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更新时间 2025/01/08
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适用于v4.607及其之后的版本
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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
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最新一次更新说明：新增userdata自定义字段
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"""
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ret = False
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msg = "未知错误"
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happen = False # True表示发生了报警，False表示未发生报警
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happenScore = 0.0 # 发生报警的置信度
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result_detects = [] # 返回检测的目标数组
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try:
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print("request_params=", datetime.now())
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request_params = request.get_json()
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print(request_params)
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detects = request_params.get("detects")
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if detects or True:
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# 添加一个模拟产生的目标
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result_detects.append({
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"x1": 100,
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"y1": 100,
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"x2": 300,
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"y2": 300,
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"class_score": 0.93456,
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"class_id": 0,
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"class_name": "test",
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"user_data": "hahahah",
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})
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happen = True
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happenScore = 1
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ret = True
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msg = "success"
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except Exception as e:
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msg = str(e)
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response_data = {
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"code": 1000 if ret else 0,
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"msg": msg,
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"result": {
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"happen": happen,
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"happenScore": happenScore,
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"detects": result_detects
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}
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}
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return jsonify(response_data)
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@app.route('/receiveImage', methods=['POST', 'GET'])
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def receiveImage():
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print("receiveImage()")
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"""
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更新时间 2024/12/12
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适用于v4.503及其之后的版本
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适用于【模式五】的API行为算法调用示例
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"""
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ret = False
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msg = "未知错误"
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happen = False # True表示发生了报警，False表示未发生报警
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happenScore = 0.0 # 发生报警的置信度
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happenDesc = "" # 发生报警的描述（v4.635支持）
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result_detects = []
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try:
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request_params = request.get_json()
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# print("request_params=", datetime.now(), request_params)
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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
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if image_base64:
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encoded_image_byte = base64.b64decode(image_base64)
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image_array = np.frombuffer(encoded_image_byte, np.uint8)
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# image = turboJpeg.decode(image_array) # turbojpeg 解码
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image = cv2.imdecode(image_array, cv2.COLOR_RGB2BGR) # opencv 解码
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# video_height,video_width,video_channels = image.shape # 输入图像的的高，宽，channel
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print(image.shape)
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result_detects.append({
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"x1": 100,
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"y1": 100,
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"x2": 500,
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"y2": 500,
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"class_score": 0.93456,
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"class_id": 0,
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"class_name": "test",
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"region_index": 2,
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})
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happen = True # True 表示发生了报警
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happenScore = 1.0 # 发生报警的置信度
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ret = True
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msg = "success"
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except Exception as e:
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msg = str(e)
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response_data = {
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"code": 1000 if ret else 0,
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"msg": msg,
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"result": {
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"happen": happen,
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"happenScore": happenScore,
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"happenDesc": happenDesc,
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"detects": result_detects
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}
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}
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# return json.dumps(response_data)
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return jsonify(response_data)
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if __name__ == '__main__':
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# app.debug = True
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# 推荐的json格式化网页工具：https://www.sojson.com/
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# 接口列表
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# http://127.0.0.1:8070/receiveDetectResults
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# http://127.0.0.1:8070/receiveDetectResults2
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# http://127.0.0.1:8070/receiveImage
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app.run(host='0.0.0.0', port=8070, debug=False)
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