# -*- coding: utf-8 -*- # @Time : 2024/4/20 18:45 # @Author : TG # @File : main.py # @Software: PyCharm # -*- coding: utf-8 -*- # @Time : 2024/4/12 15:04 # @Author : TG # @File : main.py # @Software: PyCharm import socket import sys import numpy as np import cv2 import root_dir import time import os from root_dir import ROOT_DIR import logging from utils import threshold_segmentation, largest_connected_component, draw_tomato_edge, bitwise_and_rgb_with_binary, \ extract_s_l, get_tomato_dimensions, get_defect_info, create_pipes, receive_rgb_data, send_data, receive_spec_data from collections import deque import time import io from PIL import Image import threading import queue def process_data(img: any) -> tuple: """ 处理指令 :param cmd: 指令类型 :param data: 指令内容 :param connected_sock: socket :param detector: 模型 :return: 是否处理成功 """ # start_time = time.time() # if cmd == 'IM': threshold_s_l = 180 # threshold_r_b = 15 s_l = extract_s_l(img) thresholded_s_l = threshold_segmentation(s_l, threshold_s_l) new_bin_img = largest_connected_component(thresholded_s_l) edge, mask = draw_tomato_edge(img, new_bin_img) org_defect = bitwise_and_rgb_with_binary(edge, new_bin_img) # filled_img, defect = fill_holes(new_bin_img) long_axis, short_axis = get_tomato_dimensions(mask) number_defects, total_pixels = get_defect_info(new_bin_img) rp = org_defect rp = cv2.cvtColor(rp, cv2.COLOR_BGR2RGB) # cv2.imwrite('rp1.bmp', rp) # else: # logging.error(f'错误指令，指令为{cmd}') # response = False # end_time = time.time() # elapsed_time = end_time - start_time # print(f'处理时间：{elapsed_time}秒') return long_axis, short_axis, number_defects, total_pixels, rp ## 20240423代码 def main(is_debug=False): file_handler = logging.FileHandler(os.path.join(ROOT_DIR, 'report.log')) file_handler.setLevel(logging.DEBUG if is_debug else logging.WARNING) console_handler = logging.StreamHandler(sys.stdout) console_handler.setLevel(logging.DEBUG if is_debug else logging.WARNING) logging.basicConfig(format='%(asctime)s %(filename)s[line:%(lineno)d] - %(levelname)s - %(message)s', handlers=[file_handler, console_handler], level=logging.DEBUG) rgb_receive_name = r'\\.\pipe\rgb_receive' rgb_send_name = r'\\.\pipe\rgb_send' spec_receive_name = r'\\.\pipe\spec_receive' rgb_receive, rgb_send, spec_receive = create_pipes(rgb_receive_name, rgb_send_name, spec_receive_name) # data_size = 15040566 while True: long_axis_list = [] short_axis_list = [] defect_num_sum = 0 total_defect_area_sum = 0 rp = None start_time = time.time() for i in range(5): # start_time = time.time() img_data = receive_rgb_data(rgb_receive) image = Image.open(io.BytesIO(img_data)) img = np.array(image) print(img.shape) # end_time = time.time() # elapsed_time = end_time - start_time # print(f'接收时间：{elapsed_time}秒') long_axis, short_axis, number_defects, total_pixels, rp = process_data(img=img) # print(long_axis, short_axis, number_defects, type(total_pixels), rp.shape) if i <= 2: long_axis_list.append(long_axis) short_axis_list.append(short_axis) if i == 1: rp_result = rp defect_num_sum += number_defects total_defect_area_sum += total_pixels long_axis = round(sum(long_axis_list) / 3) short_axis = round(sum(short_axis_list) / 3) # print(type(long_axis), type(short_axis), type(defect_num_sum), type(total_defect_area_sum), type(rp_result)) spec_data = receive_spec_data(spec_receive) print(f'光谱数据接收长度：', len(spec_data)) response = send_data(pipe_send=rgb_send, long_axis=long_axis, short_axis=short_axis, defect_num=defect_num_sum, total_defect_area=total_defect_area_sum, rp=rp_result) end_time = time.time() elapsed_time = (end_time - start_time) * 1000 print(f'总时间：{elapsed_time}毫秒') print(long_axis, short_axis, defect_num_sum, total_defect_area_sum, rp_result.shape) if __name__ == '__main__': # 2个pipe管道 # 接收到图片 n_rows * n_cols * 3， uint8 # 发送long_axis, short_axis, defect_num_sum, total_defect_area_sum, rp_result main(is_debug=False) ### 多线程版本 # def receive_spec_data_thread(spec_receive, spec_queue): # while True: # spec_data = receive_spec_data(spec_receive) # spec_queue.put(spec_data) # # def receive_process_rgb_data_thread(rgb_receive, img_queue, result_queue): # while True: # # long_axis_list = [] # short_axis_list = [] # defect_num_sum = 0 # total_defect_area_sum = 0 # rp = None # # for i in range(5): # img_data = receive_rgb_data(rgb_receive) # image = Image.open(io.BytesIO(img_data)) # img = np.array(image) # # long_axis, short_axis, number_defects, total_pixels, rp = process_data(img=img) # # if i <= 2: # long_axis_list.append(long_axis) # short_axis_list.append(short_axis) # if i == 1: # rp_result = rp # # defect_num_sum += number_defects # total_defect_area_sum += total_pixels # # long_axis = round(sum(long_axis_list) / 3) # short_axis = round(sum(short_axis_list) / 3) # # result = (long_axis, short_axis, defect_num_sum, total_defect_area_sum, rp_result) # result_queue.put(result) # # def main(is_debug=False): # file_handler = logging.FileHandler(os.path.join(ROOT_DIR, 'report.log')) # file_handler.setLevel(logging.DEBUG if is_debug else logging.WARNING) # console_handler = logging.StreamHandler(sys.stdout) # console_handler.setLevel(logging.DEBUG if is_debug else logging.WARNING) # logging.basicConfig(format='%(asctime)s %(filename)s[line:%(lineno)d] - %(levelname)s - %(message)s', # handlers=[file_handler, console_handler], # level=logging.DEBUG) # rgb_receive_name = r'\\.\pipe\rgb_receive' # rgb_send_name = r'\\.\pipe\rgb_send' # spec_receive_name = r'\\.\pipe\spec_receive' # rgb_receive, rgb_send, spec_receive = create_pipes(rgb_receive_name, rgb_send_name, spec_receive_name) # # spec_queue = queue.Queue() # img_queue = queue.Queue() # result_queue = queue.Queue() # # # 创建并启动线程 # spec_thread = threading.Thread(target=receive_spec_data_thread, args=(spec_receive, spec_queue)) # rgb_thread = threading.Thread(target=receive_process_rgb_data_thread, args=(rgb_receive, img_queue, result_queue)) # spec_thread.start() # rgb_thread.start() # # while True: # spec_data = spec_queue.get() # print(f'spec_data长度：', len(spec_data)) # long_axis, short_axis, defect_num_sum, total_defect_area_sum, rp_result = result_queue.get() # # response = send_data(pipe_send=rgb_send, long_axis=long_axis, short_axis=short_axis, # defect_num=defect_num_sum, total_defect_area=total_defect_area_sum, rp=rp_result) # # print(long_axis, short_axis, defect_num_sum, total_defect_area_sum, rp_result.shape) # # if __name__ == '__main__': # main(is_debug=False)