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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-04-18 15:39:05 +02:00
parent 25bf9e3611
commit a4f2ad1660
1 changed files with 2 additions and 5 deletions
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7
train.py
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@ -10,7 +10,7 @@ from models import *
from utils.datasets import * from utils.datasets import *
from utils.utils import * from utils.utils import *
# Initialize hyperparameters # Hyperparameters
hyp = {'k': 6.927, # loss multiple hyp = {'k': 6.927, # loss multiple
'xy': 0.07556, # xy loss fraction 'xy': 0.07556, # xy loss fraction
'wh': 0.008074, # wh loss fraction 'wh': 0.008074, # wh loss fraction
@ -34,7 +34,6 @@ def train(
accumulate=1, accumulate=1,
multi_scale=False, multi_scale=False,
freeze_backbone=False, freeze_backbone=False,
num_workers=4,
transfer=False # Transfer learning (train only YOLO layers) transfer=False # Transfer learning (train only YOLO layers)
): ):
init_seeds() init_seeds()
@ -45,7 +44,7 @@ def train(
if multi_scale: if multi_scale:
img_size = 608 # initiate with maximum multi_scale size img_size = 608 # initiate with maximum multi_scale size
num_workers = 0 # bug https://github.com/ultralytics/yolov3/issues/174 opt.num_workers = 0 # bug https://github.com/ultralytics/yolov3/issues/174
else: else:
torch.backends.cudnn.benchmark = True # unsuitable for multiscale torch.backends.cudnn.benchmark = True # unsuitable for multiscale
@ -292,7 +291,6 @@ if __name__ == '__main__':
batch_size=opt.batch_size, batch_size=opt.batch_size,
accumulate=opt.accumulate, accumulate=opt.accumulate,
multi_scale=opt.multi_scale, multi_scale=opt.multi_scale,
num_workers=opt.num_workers
) )
# Evolve hyperparameters (optional) # Evolve hyperparameters (optional)
@ -335,7 +333,6 @@ if __name__ == '__main__':
batch_size=opt.batch_size, batch_size=opt.batch_size,
accumulate=opt.accumulate, accumulate=opt.accumulate,
multi_scale=opt.multi_scale, multi_scale=opt.multi_scale,
num_workers=opt.num_workers
) )
mutation_fitness = results[2] mutation_fitness = results[2]