Chengfang Lu
7c43b44c57
Huaxu Sentinel Active Safety Platform with embedded algorithm code, Docker Compose setup, and vendored dataset scaffolds for clone-and-run. Co-authored-by: Cursor <cursoragent@cursor.com>
138 lines
5.2 KiB
Python
Executable File
138 lines
5.2 KiB
Python
Executable File
import os
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import random
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import glob
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import argparse
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from pathlib import Path
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import shutil
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import sys
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from PIL import Image
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import cv2
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import csv
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from itertools import islice
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FILE = Path(__file__).resolve()
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ROOT = FILE.parents[0] # YOLOv5 root directory
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print("-------------------ROOT=",ROOT)
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# test_rate=0.05
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# src_data_path = "./isa_class/src_data"
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def process_img(src_data_path, test_rate):
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dst_data_path = src_data_path.replace('src_data','dst_data')
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# if not os.path.exists(dst_data_path):
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# print("create dst_data = ", dst_data_path)
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# os.mkdir(dst_data_path)
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list = glob.glob(os.path.join(src_data_path,"*/*.jpg"))
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print("len list = ",len(list))
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test_cout = int(test_rate*len(list))
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print("test_cout = ",test_cout)
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test_list=random.sample(list, test_cout)
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print("test_list len = ",len(test_list))
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# print("test_list = ",test_list)
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dst_train_path=os.path.join(dst_data_path,'train')
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dst_test_path=os.path.join(dst_data_path,'test')
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print("dst_train_path={} , dst_test_path={}".format(dst_train_path,dst_test_path))
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if not os.path.exists(dst_train_path):
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os.makedirs(dst_train_path)
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if not os.path.exists(dst_test_path):
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os.makedirs(dst_test_path)
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class_name_list = []
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for x in glob.glob(os.path.join(src_data_path, '*')):
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class_name_list.append(os.path.split(x)[-1])
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print("class_name_list = ",class_name_list)
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data_set_type = ['train','test']
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for class_name in class_name_list:
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for set in data_set_type:
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dst_class_dir = os.path.join(dst_data_path,set,class_name)
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if not os.path.exists(dst_class_dir):
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os.makedirs(dst_class_dir)
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print("create dst_class_dir = ",dst_class_dir)
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for class_name in class_name_list:
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sub_src_path = os.path.join(src_data_path, class_name)
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img_list = glob.glob(os.path.join(sub_src_path,'*.jpg'))
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total_len = len(img_list)
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test_cout = int(test_rate*len(img_list))
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if test_cout < 1:
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test_cout = 1
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print("test_cout = ",test_cout)
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print("class_name = ",class_name)
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test_list=random.sample(img_list, test_cout)
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print("test_list len = ",len(test_list))
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for src_img in img_list:
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img_name = os.path.split(src_img)[-1]
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# for date_set in data_set_type:
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dst_train_img_path=os.path.join(dst_train_path, class_name, img_name)
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dst_test_img_path=os.path.join(dst_test_path, class_name, img_name)
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# if src_img in test_list:
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# else:
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# dst_img_path=os.path.join(dst_train_path, class_name, img_name)
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print("src_img={},dst_train_img_path={},dst__test_img_path={}".format(src_img, dst_train_img_path, dst_test_img_path))
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if src_img in test_list:
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shutil.copy(src_img, dst_test_img_path)
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if total_len < 2:
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shutil.copy(src_img, dst_train_img_path)
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else:
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shutil.copy(src_img, dst_train_img_path)
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def parse_opt():
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parser=argparse.ArgumentParser()
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parser.add_argument('--src-data',type=str,default=ROOT / "src_data",help='src dir')
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parser.add_argument('--test-rate',type=float,default=0.1,help='test_rate')
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# parser.add_argument('--src-test',type=str,default=ROOT / "src_test",help='src dir')
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parser.add_argument('--dst-data',type=str,default=ROOT / "dst_data",help='dst dir')
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# parser.add_argument('--prefix',type=str,default="dst",help='prefix name ')
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opt=parser.parse_args()
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print("src_data=%s" % (opt.src_data))
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print("test_rate=%s" % (opt.test_rate))
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# print("src_test=%s" % (opt.src_test))
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print("dst_data=%s" % (opt.dst_data))
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# print("prefix=%s" % (opt.prefix))
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return opt
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# python isa_preprocess.py --src-data ./isa_class_tsrd_gtsrb_eureg_cctsdb_tt100k/src_data
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# python isa_preprocess.py --src-data ./isa_class_tsrd_gtsrb_eureg_cctsdb_tt100k_speed/src_data
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# python isa_preprocess.py --src-data ./isa_class_1020/src_data
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# python isa_preprocess.py --src-data ./isa_class_1023/src_data
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# python isa_preprocess.py --src-data ./isa_class_1025/src_data
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# python isa_preprocess.py --src-data ./isa_class_1026/src_data
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# python isa_preprocess.py --src-data ./isa_class_1102/src_data
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# python isa_preprocess.py --src-data ./isa_class_1120/src_data
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# python isa_preprocess.py --src-data ./isa_class_1212/src_data
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# python isa_preprocess.py --src-data ./isa_class_1221/src_data
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# python isa_preprocess.py --src-data ./isa_class_1222/src_data
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# python isa_preprocess.py --src-data ./isa_class_1224/src_data
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# python isa_preprocess.py --src-data ./isa_class_1229/src_data
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# python isa_preprocess.py --src-data ./isa_class_0103/src_data
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# python isa_preprocess.py --src-data ./isa_class_0104/src_data
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# python isa_preprocess.py --src-data ./isa_class_0108/src_data
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# python isa_preprocess.py --src-data ./isa_class_0112/src_data
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# python isa_preprocess.py --src-data ./isa_class_0116/src_data
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def main(opt):
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if opt.src_data and opt.dst_data:
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# train_ppm_to_jpg(opt.src_train, opt.dst_data)
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process_img(opt.src_data, opt.test_rate)
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if __name__ == "__main__":
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opt = parse_opt()
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main(opt) |