mirror of
https://github.com/NanjingForestryUniversity/supermachine--tomato-passion_fruit.git
synced 2025-11-09 14:54:07 +00:00
229 lines
7.6 KiB
Python
229 lines
7.6 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 threshold_segmentation, largest_connected_component, draw_tomato_edge, bitwise_and_rgb_with_binary, \
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extract_s_l, get_tomato_dimensions, get_defect_info, create_pipes, receive_rgb_data, send_data, receive_spec_data
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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(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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# start_time = time.time()
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# if cmd == 'IM':
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threshold_s_l = 180
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# threshold_r_b = 15
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s_l = extract_s_l(img)
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thresholded_s_l = threshold_segmentation(s_l, threshold_s_l)
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new_bin_img = largest_connected_component(thresholded_s_l)
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edge, mask = draw_tomato_edge(img, new_bin_img)
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org_defect = bitwise_and_rgb_with_binary(edge, new_bin_img)
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# filled_img, defect = fill_holes(new_bin_img)
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long_axis, short_axis = get_tomato_dimensions(mask)
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number_defects, total_pixels = get_defect_info(new_bin_img)
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rp = org_defect
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rp = cv2.cvtColor(rp, cv2.COLOR_BGR2RGB)
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# cv2.imwrite('rp1.bmp', rp)
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# else:
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# logging.error(f'错误指令，指令为{cmd}')
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# response = False
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# end_time = time.time()
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# elapsed_time = end_time - start_time
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# print(f'处理时间：{elapsed_time}秒')
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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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defect_num_sum = 0
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total_defect_area_sum = 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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img_data = receive_rgb_data(rgb_receive)
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image = Image.open(io.BytesIO(img_data))
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img = np.array(image)
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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(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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if i == 1:
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rp_result = rp
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defect_num_sum += number_defects
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total_defect_area_sum += total_pixels
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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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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=defect_num_sum, total_defect_area=total_defect_area_sum, 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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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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### 多线程版本
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# def receive_spec_data_thread(spec_receive, spec_queue):
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# while True:
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# spec_data = receive_spec_data(spec_receive)
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# spec_queue.put(spec_data)
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#
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# def receive_process_rgb_data_thread(rgb_receive, img_queue, result_queue):
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# while True:
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#
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# long_axis_list = []
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# short_axis_list = []
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# defect_num_sum = 0
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# total_defect_area_sum = 0
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# rp = None
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#
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# for i in range(5):
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# img_data = receive_rgb_data(rgb_receive)
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# image = Image.open(io.BytesIO(img_data))
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# img = np.array(image)
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#
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# long_axis, short_axis, number_defects, total_pixels, rp = process_data(img=img)
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#
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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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# if i == 1:
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# rp_result = rp
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#
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# defect_num_sum += number_defects
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# total_defect_area_sum += total_pixels
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#
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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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#
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# result = (long_axis, short_axis, defect_num_sum, total_defect_area_sum, rp_result)
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# result_queue.put(result)
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#
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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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#
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# spec_queue = queue.Queue()
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# img_queue = queue.Queue()
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# result_queue = queue.Queue()
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#
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# # 创建并启动线程
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# spec_thread = threading.Thread(target=receive_spec_data_thread, args=(spec_receive, spec_queue))
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# rgb_thread = threading.Thread(target=receive_process_rgb_data_thread, args=(rgb_receive, img_queue, result_queue))
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# spec_thread.start()
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# rgb_thread.start()
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#
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# while True:
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# spec_data = spec_queue.get()
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# print(f'spec_data长度：', len(spec_data))
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# long_axis, short_axis, defect_num_sum, total_defect_area_sum, rp_result = result_queue.get()
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#
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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=defect_num_sum, total_defect_area=total_defect_area_sum, rp=rp_result)
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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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#
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# if __name__ == '__main__':
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# main(is_debug=False)
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