do_transforms=True,
multi_scale=model.multi_scale)
test_data = PascalDatasetYOLO(
root_dir='../../../Data/VOCdevkit/VOC2007/',
class_file='../../../Data/VOCdevkit/voc.names',
dataset='test',
batch_size=model.batch_size // model.subdivisions,
image_size=model.default_image_size,
anchors=model.anchors,
strides=model.strides,
do_transforms=False,
multi_scale=False,
return_targets=False)
model.load_weights('models/yolov2-tiny.conv.13', only_imagenet=True)
model = model.to(device)
if train:
set_random_seed(12345)
model.mini_freeze()
optimizer = optim.SGD(model.get_trainable_parameters(),
lr=model.lr,
momentum=model.momentum,
weight_decay=model.weight_decay,
nesterov=True)
scheduler = step_decay_scheduler(optimizer,
steps=model.steps,
scales=model.scales)
multi_scale=model.multi_scale)
test_data = PascalDatasetYOLO(
root_dir='../../../Data/VOCdevkit/VOC2007/',
class_file='../../../Data/VOCdevkit/voc.names',
dataset='test',
batch_size=model.batch_size // model.subdivisions,
image_size=model.default_image_size,
anchors=model.anchors,
strides=model.strides,
skip_difficult=False,
do_transforms=False,
multi_scale=False,
return_targets=False)
model.load_weights('models/yolov3-tiny.conv.11', only_imagenet=True)
model = model.to(device)
if train:
set_random_seed(12345)
model.unfreeze()
optimizer = optim.SGD(model.get_trainable_parameters(),
lr=model.lr,
momentum=model.momentum,
weight_decay=model.weight_decay,
nesterov=True)
scheduler = step_decay_scheduler(optimizer,
steps=model.steps,
scales=model.scales)
strides=model.strides,
do_transforms=False,
multi_scale=model.multi_scale)
test_data = PascalDatasetYOLO(root_dir='../../../Data/SS/',
class_file='../../../Data/SS/ss.names',
dataset='test',
batch_size=model.batch_size //
model.subdivisions,
image_size=model.default_image_size,
anchors=model.anchors,
strides=model.strides,
do_transforms=False,
multi_scale=model.multi_scale)
model.load_weights('models/darknet53_448.weights', only_imagenet=True)
model = model.to(device)
if train:
set_random_seed(12345)
model.mini_freeze()
optimizer = optim.SGD(model.get_trainable_parameters(),
lr=model.lr,
momentum=model.momentum,
weight_decay=model.weight_decay,
nesterov=True)
scheduler = step_decay_scheduler(optimizer,
steps=model.steps,
scales=model.scales)