LoRaMonitorProject/backend/test_recogn.py

from flask import Flask, request, jsonify
import base64
import io
from PIL import Image
import time

app = Flask(__name__)

@app.route('/api/pressure', methods=['POST'])
def recognize_pressure():
    try:
        # 获取文件和元数据
        image_file = request.files.get('image')
        metadata_json = request.form.get('metadata')

        if image_file is None:
            return jsonify({
                "result": 0,
                "message": "图像未上传",
                "data": None
            }), 400

        # 把上传图像数据缓存下来（避免流被读两次）
        image_bytes = image_file.read()
        image_stream = io.BytesIO(image_bytes)

        try:
            image = Image.open(image_stream);
            format = image.format
            print(f"image format is {format}")
        except Exception as e:
            print("图像格式无效:",e)

        # 读取图像内容并转为 base64
        # image_bytes = image_file.read()
        image_base64 = base64.b64encode(image_bytes).decode('utf-8')

        # 模拟生成日志
        log_content = f"处理图像: {image_file.filename}\n时间: {time.strftime('%Y-%m-%d %H:%M:%S')}\n状态: 成功"
        logs_base64 = base64.b64encode(log_content.encode('utf-8')).decode('utf-8')

        # 模拟读取的仪表值
        reading_value = 123.45  # 可以改为实际模型识别逻辑

        # response = {
        #     "result": 1,
        #     "message": "识别成功",
        #     "data": {
        #         "image": image_base64,
        #         "logs": logs_base64,
        #         "reading": reading_value
        #     }
        # }

        # response = {
        #     "result": 0,
        #     "message": "x 图像处理失败:自动旋转未找到有效角度",
        #     "data": {
        #         "image": None,
        #         "logs": "",
        #         "reading": None
        #     }
        # }

        # response = {
        #     "result": 1,
        #     "message": "成功处理",
        #     "data": {
        #         "meter_type":1,
        #         "image": image_base64,
        #         "logs": logs_base64,
        #         "reading": 123.66,
        #         "reading_unit":0.001,
        #         "reading_str": '12.34.22',
        #         "reading_str_flag":1
        #     }
        # }

        response = {
            "result": 1,
            "message": "成功处理",
            "data": {
                "meter_type":1,
                "image": image_base64,
                "logs": logs_base64,
                "reading": 123.09,
                "reading_unit":0.001
            }
        }

        # response = {
        #     "result": 1,
        #     "message": "成功处理",
        #     "data": {
        #         "meter_type":1,
        #         "image": image_base64,
        #         "logs": logs_base64,
        #         "reading": None,
        #         "reading_unit":None,
        #         "reading_str": '12.34.22',
        #         "reading_str_flag":1
        #     }
        # }

        # response = {
        #     "result": 1,
        #     "message": "成功处理",
        #     "data": {
        #         "meter_type":1,
        #         "image": image_base64,
        #         "logs": logs_base64,
        #         "reading": 123.45,
        #         "reading_unit":0.01,
        #         "reading_str": None,
        #         "reading_str_flag":None
        #     }
        # }

        # response = {
        #     "result": 0,
        #     "message": "未成功处理",
        #     "data": {
        #         "meter_type":None,
        #         "image": None,
        #         "logs": "",
        #         "reading": None,
        #         "reading_unit":None
        #     }
        # }

        return jsonify(response)

    except Exception as e:
        print(f"{e}")
        return jsonify({
            "result": 0,
            "message": f"服务端异常: {str(e)}",
            "data": None
        }), 500

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=5000)