mirror of
https://github.com/NanjingForestryUniversity/supermachine--tomato-passion_fruit.git
synced 2025-11-09 06:44:02 +00:00
129 lines
4.1 KiB
Python
129 lines
4.1 KiB
Python
# -*- coding: utf-8 -*-
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# @Time : 2024/4/20 18:45
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# @Author : TG
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# @File : main.py
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# @Software: PyCharm
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# -*- coding: utf-8 -*-
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# @Time : 2024/4/12 15:04
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# @Author : TG
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# @File : main.py
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# @Software: PyCharm
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import socket
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import sys
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import numpy as np
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import cv2
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import root_dir
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import time
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import os
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from root_dir import ROOT_DIR
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import logging
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from utils import parse_protocol, create_pipes, receive_rgb_data, send_data, receive_spec_data, analyze_tomato, analyze_passion_fruit
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from collections import deque
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import time
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import io
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from PIL import Image
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import threading
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import queue
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def process_data(cmd: str, img: any) -> tuple:
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"""
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处理指令
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:param cmd: 指令类型
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:param data: 指令内容
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:param connected_sock: socket
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:param detector: 模型
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:return: 是否处理成功
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"""
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if cmd == 'TO':
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# 番茄
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long_axis, short_axis, number_defects, total_pixels, rp = analyze_tomato(img)
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elif cmd == 'PF':
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# 百香果
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long_axis, short_axis, number_defects, total_pixels, rp = analyze_passion_fruit(img)
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return long_axis, short_axis, number_defects, total_pixels, rp
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## 20240423代码
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def main(is_debug=False):
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file_handler = logging.FileHandler(os.path.join(ROOT_DIR, 'report.log'))
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file_handler.setLevel(logging.DEBUG if is_debug else logging.WARNING)
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console_handler = logging.StreamHandler(sys.stdout)
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console_handler.setLevel(logging.DEBUG if is_debug else logging.WARNING)
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logging.basicConfig(format='%(asctime)s %(filename)s[line:%(lineno)d] - %(levelname)s - %(message)s',
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handlers=[file_handler, console_handler],
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level=logging.DEBUG)
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rgb_receive_name = r'\\.\pipe\rgb_receive'
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rgb_send_name = r'\\.\pipe\rgb_send'
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spec_receive_name = r'\\.\pipe\spec_receive'
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rgb_receive, rgb_send, spec_receive = create_pipes(rgb_receive_name, rgb_send_name, spec_receive_name)
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# data_size = 15040566
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while True:
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long_axis_list = []
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short_axis_list = []
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max_defect_num = 0 # 初始化最大缺陷数量为0
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max_total_defect_area = 0 # 初始化最大总像素数为0
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rp = None
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# start_time = time.time()
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for i in range(5):
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# start_time = time.time()
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data = receive_rgb_data(rgb_receive)
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cmd, img = parse_protocol(data)
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# print(img.shape)
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# end_time = time.time()
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# elapsed_time = end_time - start_time
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# print(f'接收时间：{elapsed_time}秒')
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long_axis, short_axis, number_defects, total_pixels, rp = process_data(cmd=cmd, img=img)
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# print(long_axis, short_axis, number_defects, type(total_pixels), rp.shape)
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if i <= 2:
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long_axis_list.append(long_axis)
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short_axis_list.append(short_axis)
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# 更新最大缺陷数量和最大总像素数
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max_defect_num = max(max_defect_num, number_defects)
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max_total_defect_area = max(max_total_defect_area, total_pixels)
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if i == 1:
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rp_result = rp
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long_axis = round(sum(long_axis_list) / 3)
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short_axis = round(sum(short_axis_list) / 3)
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# print(type(long_axis), type(short_axis), type(defect_num_sum), type(total_defect_area_sum), type(rp_result))
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spec_data = receive_spec_data(spec_receive)
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cmd, spec_data = parse_protocol(spec_data)
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# print(f'光谱数据接收长度：', len(spec_data))
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response = send_data(pipe_send=rgb_send, long_axis=long_axis, short_axis=short_axis,
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defect_num=max_defect_num, total_defect_area=max_total_defect_area, rp=rp_result)
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# end_time = time.time()
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# elapsed_time = (end_time - start_time) * 1000
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# print(f'总时间：{elapsed_time}毫秒')
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#
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# print(long_axis, short_axis, defect_num_sum, total_defect_area_sum, rp_result.shape)
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if __name__ == '__main__':
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# 2个pipe管道
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# 接收到图片 n_rows * n_cols * 3， uint8
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# 发送long_axis, short_axis, defect_num_sum, total_defect_area_sum, rp_result
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main(is_debug=False)
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