diff --git a/data/coco_100img.data b/data/coco_100img.data deleted file mode 100644 index 716cf7c9..00000000 --- a/data/coco_100img.data +++ /dev/null @@ -1,6 +0,0 @@ -classes=80 -train=./data/coco_100img.txt -valid=./data/coco_100img.txt -names=data/coco.names -backup=backup/ -eval=coco diff --git a/data/coco_100img.txt b/data/coco_100img.txt deleted file mode 100644 index a39dc939..00000000 --- a/data/coco_100img.txt +++ /dev/null @@ -1,100 +0,0 @@ -../coco/images/train2014/COCO_train2014_000000000009.jpg -../coco/images/train2014/COCO_train2014_000000000025.jpg -../coco/images/train2014/COCO_train2014_000000000030.jpg -../coco/images/train2014/COCO_train2014_000000000034.jpg -../coco/images/train2014/COCO_train2014_000000000036.jpg -../coco/images/train2014/COCO_train2014_000000000049.jpg -../coco/images/train2014/COCO_train2014_000000000061.jpg -../coco/images/train2014/COCO_train2014_000000000064.jpg -../coco/images/train2014/COCO_train2014_000000000071.jpg -../coco/images/train2014/COCO_train2014_000000000072.jpg -../coco/images/train2014/COCO_train2014_000000000077.jpg -../coco/images/train2014/COCO_train2014_000000000078.jpg -../coco/images/train2014/COCO_train2014_000000000081.jpg -../coco/images/train2014/COCO_train2014_000000000086.jpg -../coco/images/train2014/COCO_train2014_000000000089.jpg -../coco/images/train2014/COCO_train2014_000000000092.jpg -../coco/images/train2014/COCO_train2014_000000000094.jpg -../coco/images/train2014/COCO_train2014_000000000109.jpg -../coco/images/train2014/COCO_train2014_000000000110.jpg -../coco/images/train2014/COCO_train2014_000000000113.jpg -../coco/images/train2014/COCO_train2014_000000000127.jpg -../coco/images/train2014/COCO_train2014_000000000138.jpg -../coco/images/train2014/COCO_train2014_000000000142.jpg -../coco/images/train2014/COCO_train2014_000000000144.jpg -../coco/images/train2014/COCO_train2014_000000000149.jpg -../coco/images/train2014/COCO_train2014_000000000151.jpg -../coco/images/train2014/COCO_train2014_000000000154.jpg -../coco/images/train2014/COCO_train2014_000000000165.jpg -../coco/images/train2014/COCO_train2014_000000000194.jpg -../coco/images/train2014/COCO_train2014_000000000201.jpg -../coco/images/train2014/COCO_train2014_000000000247.jpg -../coco/images/train2014/COCO_train2014_000000000260.jpg -../coco/images/train2014/COCO_train2014_000000000263.jpg -../coco/images/train2014/COCO_train2014_000000000307.jpg -../coco/images/train2014/COCO_train2014_000000000308.jpg -../coco/images/train2014/COCO_train2014_000000000309.jpg -../coco/images/train2014/COCO_train2014_000000000312.jpg -../coco/images/train2014/COCO_train2014_000000000315.jpg -../coco/images/train2014/COCO_train2014_000000000321.jpg -../coco/images/train2014/COCO_train2014_000000000322.jpg -../coco/images/train2014/COCO_train2014_000000000326.jpg -../coco/images/train2014/COCO_train2014_000000000332.jpg -../coco/images/train2014/COCO_train2014_000000000349.jpg -../coco/images/train2014/COCO_train2014_000000000368.jpg -../coco/images/train2014/COCO_train2014_000000000370.jpg -../coco/images/train2014/COCO_train2014_000000000382.jpg -../coco/images/train2014/COCO_train2014_000000000384.jpg -../coco/images/train2014/COCO_train2014_000000000389.jpg -../coco/images/train2014/COCO_train2014_000000000394.jpg -../coco/images/train2014/COCO_train2014_000000000404.jpg -../coco/images/train2014/COCO_train2014_000000000419.jpg -../coco/images/train2014/COCO_train2014_000000000431.jpg -../coco/images/train2014/COCO_train2014_000000000436.jpg -../coco/images/train2014/COCO_train2014_000000000438.jpg -../coco/images/train2014/COCO_train2014_000000000443.jpg -../coco/images/train2014/COCO_train2014_000000000446.jpg -../coco/images/train2014/COCO_train2014_000000000450.jpg -../coco/images/train2014/COCO_train2014_000000000471.jpg -../coco/images/train2014/COCO_train2014_000000000490.jpg -../coco/images/train2014/COCO_train2014_000000000491.jpg -../coco/images/train2014/COCO_train2014_000000000510.jpg -../coco/images/train2014/COCO_train2014_000000000514.jpg -../coco/images/train2014/COCO_train2014_000000000529.jpg -../coco/images/train2014/COCO_train2014_000000000531.jpg -../coco/images/train2014/COCO_train2014_000000000532.jpg -../coco/images/train2014/COCO_train2014_000000000540.jpg -../coco/images/train2014/COCO_train2014_000000000542.jpg -../coco/images/train2014/COCO_train2014_000000000560.jpg -../coco/images/train2014/COCO_train2014_000000000562.jpg -../coco/images/train2014/COCO_train2014_000000000572.jpg -../coco/images/train2014/COCO_train2014_000000000575.jpg -../coco/images/train2014/COCO_train2014_000000000581.jpg -../coco/images/train2014/COCO_train2014_000000000584.jpg -../coco/images/train2014/COCO_train2014_000000000595.jpg -../coco/images/train2014/COCO_train2014_000000000597.jpg -../coco/images/train2014/COCO_train2014_000000000605.jpg -../coco/images/train2014/COCO_train2014_000000000612.jpg -../coco/images/train2014/COCO_train2014_000000000620.jpg -../coco/images/train2014/COCO_train2014_000000000625.jpg -../coco/images/train2014/COCO_train2014_000000000629.jpg -../coco/images/train2014/COCO_train2014_000000000634.jpg -../coco/images/train2014/COCO_train2014_000000000643.jpg -../coco/images/train2014/COCO_train2014_000000000650.jpg -../coco/images/train2014/COCO_train2014_000000000656.jpg -../coco/images/train2014/COCO_train2014_000000000659.jpg -../coco/images/train2014/COCO_train2014_000000000670.jpg -../coco/images/train2014/COCO_train2014_000000000671.jpg -../coco/images/train2014/COCO_train2014_000000000673.jpg -../coco/images/train2014/COCO_train2014_000000000681.jpg -../coco/images/train2014/COCO_train2014_000000000684.jpg -../coco/images/train2014/COCO_train2014_000000000690.jpg -../coco/images/train2014/COCO_train2014_000000000706.jpg -../coco/images/train2014/COCO_train2014_000000000714.jpg -../coco/images/train2014/COCO_train2014_000000000716.jpg -../coco/images/train2014/COCO_train2014_000000000722.jpg -../coco/images/train2014/COCO_train2014_000000000723.jpg -../coco/images/train2014/COCO_train2014_000000000731.jpg -../coco/images/train2014/COCO_train2014_000000000735.jpg -../coco/images/train2014/COCO_train2014_000000000753.jpg -../coco/images/train2014/COCO_train2014_000000000754.jpg diff --git a/data/coco_10img.data b/data/coco_10img.data deleted file mode 100644 index ea37a698..00000000 --- a/data/coco_10img.data +++ /dev/null @@ -1,6 +0,0 @@ -classes=80 -train=./data/coco_10img.txt -valid=./data/coco_10img.txt -names=data/coco.names -backup=backup/ -eval=coco diff --git a/data/coco_10img.txt b/data/coco_10img.txt deleted file mode 100644 index 5378cc27..00000000 --- a/data/coco_10img.txt +++ /dev/null @@ -1,10 +0,0 @@ -../coco/images/train2014/COCO_train2014_000000000009.jpg -../coco/images/train2014/COCO_train2014_000000000025.jpg -../coco/images/train2014/COCO_train2014_000000000030.jpg -../coco/images/train2014/COCO_train2014_000000000034.jpg -../coco/images/train2014/COCO_train2014_000000000036.jpg -../coco/images/train2014/COCO_train2014_000000000049.jpg -../coco/images/train2014/COCO_train2014_000000000061.jpg -../coco/images/train2014/COCO_train2014_000000000064.jpg -../coco/images/train2014/COCO_train2014_000000000071.jpg -../coco/images/train2014/COCO_train2014_000000000072.jpg diff --git a/train.py b/train.py index 6e8a884c..c4f0181b 100644 --- a/train.py +++ b/train.py @@ -3,6 +3,7 @@ import time import torch.distributed as dist import torch.optim as optim +import torch.optim.lr_scheduler as lr_scheduler from torch.utils.data import DataLoader import test # Import test.py to get mAP after each epoch @@ -60,9 +61,9 @@ def train( data_cfg, img_size=416, resume=False, - epochs=273, # 500200 batches at bs 64, dataset length 117263 + epochs=68, # 500200 batches at bs 4, dataset length 117263 batch_size=16, - accumulate=1, + accumulate=4, # effective bs = 64 = batch_size * accumulate multi_scale=False, freeze_backbone=False, transfer=False # Transfer learning (train only YOLO layers) @@ -121,9 +122,10 @@ def train( # Scheduler https://github.com/ultralytics/yolov3/issues/238 # lf = lambda x: 1 - x / epochs # linear ramp to zero # lf = lambda x: 10 ** (hyp['lrf'] * x / epochs) # exp ramp - lf = lambda x: 1 - 10 ** (hyp['lrf'] * (1 - x / epochs)) # inverse exp ramp - scheduler = optim.lr_scheduler.LambdaLR(optimizer, lr_lambda=lf, last_epoch=start_epoch - 1) - # scheduler = optim.lr_scheduler.MultiStepLR(optimizer, milestones=[218, 245], gamma=0.1, last_epoch=start_epoch-1) + # lf = lambda x: 1 - 10 ** (hyp['lrf'] * (1 - x / epochs)) # inverse exp ramp + # scheduler = lr_scheduler.LambdaLR(optimizer, lr_lambda=lf) + scheduler = lr_scheduler.MultiStepLR(optimizer, milestones=[round(opt.epochs * x) for x in (0.8, 0.9)], gamma=0.1) + scheduler.last_epoch = start_epoch - 1 # # Plot lr schedule # y = [] @@ -303,9 +305,9 @@ if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('--epochs', type=int, default=273, help='number of epochs') parser.add_argument('--batch-size', type=int, default=16, help='size of each image batch') - parser.add_argument('--accumulate', type=int, default=1, help='accumulate gradient x batches before optimizing') + parser.add_argument('--accumulate', type=int, default=4, help='accumulate gradient x batches before optimizing') parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path') - parser.add_argument('--data-cfg', type=str, default='data/coco.data', help='coco.data file path') + parser.add_argument('--data-cfg', type=str, default='data/coco_64img.data', help='coco.data file path') parser.add_argument('--multi-scale', action='store_true', help='random image sizes per batch 320 - 608') parser.add_argument('--img-size', type=int, default=416, help='inference size (pixels)') parser.add_argument('--resume', action='store_true', help='resume training flag')