Intelligently split YOLOv3 file into train and test subsets.
yolov3_train_test_split.py --data_file <datafile> --train_file <trainfile> --test_file <testfile> --test_size <float> --random_state <integer> --debug <1 or 0>
python .\yolov3_train_test_split.py --data_file datasets\iris\data.txt --train_file datasets\iris\data_train.txt --test_file datasets\iris\data_test.txt --test_size 0.2 --random_state 2 --debug 1
,-------,-----------,----------,--------, | LABEL | TRAIN (%) | TEST (%) | TOTAL | |-------|-----------|----------|--------| | 0 | 73.8 | 26.2 | 271 | | 1 | 73.76 | 26.24 | 202 | | 10 | 78.26 | 21.74 | 138 | | 2 | 76.92 | 23.08 | 338 | | 3 | 75.26 | 24.74 | 190 | | 4 | 78.39 | 21.61 | 310 | | 5 | 74.71 | 25.29 | 174 | | 6 | 78.52 | 21.48 | 284 | | 7 | 74.19 | 25.81 | 217 | | 8 | 79.93 | 20.07 | 274 | | 9 | 80.65 | 19.35 | 186 | | 11 | 85.54 | 14.46 | 166 | | 12 | 80.65 | 19.35 | 124 | | 13 | 81.4 | 18.6 | 129 | | 22 | 85.19 | 14.81 | 27 | | X | 83.02 | 16.98 | 212 | | 15 | 75.0 | 25.0 | 16 | | 19 | 75.56 | 24.44 | 90 | | 14 | 84.09 | 15.91 | 44 | | 17 | 88.89 | 11.11 | 9 | | 23 | 91.67 | 8.33 | 12 | | 18 | 66.67 | 33.33 | 9 | | 20 | 75.0 | 25.0 | 24 | | 21 | 69.23 | 30.77 | 13 | | 16 | 85.71 | 14.29 | 7 | `-------'-----------'----------'--------´