mirror of
https://github.com/NanjingForestryUniversity/supermachine--tomato-passion_fruit.git
synced 2025-11-09 14:54:07 +00:00
242bb9a71b
fix:修复在20240627test4中的classifier.py的analyze_tomato函数中white_defect的函数忘记传递两个阈值量的错误；修复analyze_tomato函数中的叶片实例分割存在的问题，解决由于变量污染引起的分割错误；
74 lines
2.1 KiB
Python
74 lines
2.1 KiB
Python
# -*- coding: utf-8 -*-
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# @Time : 2024/7/7 下午4:33
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# @Author : TG
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# @File : totest.py
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# @Software: PyCharm
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import time
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import cv2
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import numpy as np
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import os
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import pandas as pd
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from PIL import Image
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import re
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from to_seg import TOSEG
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def tryint(s):
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try:
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return int(s)
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except ValueError:
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return s
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def natural_sort_key(s):
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return [tryint(c) for c in re.split('([0-9]+)', s)]
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def main():
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image_dir = r'D:\project\20240714Actual_deployed\testimg'
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to = TOSEG() # 假设 TOSEG 是已定义好的类，可以处理图片分割
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# 获取所有.bmp文件，并进行自然排序
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rgb_files = [os.path.join(image_dir, f) for f in os.listdir(image_dir) if f.endswith('.bmp')]
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rgb_files.sort(key=natural_sort_key)
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# 准备保存到 Excel 的数据
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records = []
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for idx, image_path in enumerate(rgb_files):
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img = cv2.imread(image_path, cv2.IMREAD_COLOR)
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# img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
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t = time.time()
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result = to.toseg(img) # 假设 toseg 方法接受一个图片数组，并返回处理后的图片
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e = time.time()
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result = cv2.cvtColor(result, cv2.COLOR_GRAY2BGR)
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process_time = e - t
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print(f'第{idx + 1}张图时间：{process_time}')
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# 获取原始文件名并添加“mask”后缀
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original_filename = os.path.splitext(os.path.basename(image_path))[0]
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output_filename = f'{original_filename}_leaf.png'
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cv2.imwrite(os.path.join(r'D:\project\20240714Actual_deployed\leaf',
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output_filename), result)
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# 添加记录到列表
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records.append({
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"Image Index": idx + 1,
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"File Name": original_filename,
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"Processing Time (s)": process_time
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})
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# cv2.imshow('result', result)
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# cv2.waitKey(0)
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# cv2.destroyAllWindows()
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# 创建 DataFrame 并写入 Excel 文件
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df = pd.DataFrame(records)
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df.to_excel(r'D:\project\20240714Actual_deployed\leaf\leaf_processing_times.xlsx', index=False)
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if __name__ == '__main__':
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main()
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