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car-detection-bayes
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updates

This commit is contained in:
glenn-jocher 2019-07-03 15:37:04 +02:00
parent 1d0a4a3ace
commit ab141fcc1f
2 changed files with 2 additions and 14 deletions
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15
models.py
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@ -45,8 +45,7 @@ def create_modules(module_defs):
modules.add_module('maxpool_%d' % i, maxpool) modules.add_module('maxpool_%d' % i, maxpool)
elif module_def['type'] == 'upsample': elif module_def['type'] == 'upsample':
# upsample = nn.Upsample(scale_factor=int(module_def['stride']), mode='nearest') # WARNING: deprecated upsample = nn.Upsample(scale_factor=int(module_def['stride']), mode='nearest')
upsample = Upsample(scale_factor=int(module_def['stride']))
modules.add_module('upsample_%d' % i, upsample) modules.add_module('upsample_%d' % i, upsample)
elif module_def['type'] == 'route': elif module_def['type'] == 'route':
@ -87,18 +86,6 @@ class EmptyLayer(nn.Module):
return x return x
class Upsample(nn.Module):
# Custom Upsample layer (nn.Upsample gives deprecated warning message)
def __init__(self, scale_factor=1, mode='nearest'):
super(Upsample, self).__init__()
self.scale_factor = scale_factor
self.mode = mode
def forward(self, x):
return F.interpolate(x, scale_factor=self.scale_factor, mode=self.mode)
class YOLOLayer(nn.Module): class YOLOLayer(nn.Module):
def __init__(self, anchors, nc, img_size, yolo_index): def __init__(self, anchors, nc, img_size, yolo_index):
super(YOLOLayer, self).__init__() super(YOLOLayer, self).__init__()

1
train.py
View File

@ -12,6 +12,7 @@ from utils.datasets import *
from utils.utils import * from utils.utils import *
# 0.149 0.241 0.126 0.156 6.85 1.008 1.421 0.07989 16.94 6.215 10.61 4.272 0.251 0.001 -4 0.9 0.0005 320 64-1 giou # 0.149 0.241 0.126 0.156 6.85 1.008 1.421 0.07989 16.94 6.215 10.61 4.272 0.251 0.001 -4 0.9 0.0005 320 64-1 giou
# 0.111 0.27 0.132 0.131 3.96 1.276 0.3156 0.1425 21.21 6.224 11.59 8.83 0.376 0.001 -4 0.9 0.0005
hyp = {'giou': 1.008, # giou loss gain hyp = {'giou': 1.008, # giou loss gain
'xy': 1.421, # xy loss gain 'xy': 1.421, # xy loss gain
'wh': 0.07989, # wh loss gain 'wh': 0.07989, # wh loss gain