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car-detection-bayes
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update test.py

This commit is contained in:
Glenn Jocher 2020-06-20 10:02:18 -07:00
parent 207a17de31
commit ca7794ed05
1 changed files with 4 additions and 2 deletions
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6
test.py
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@ -23,6 +23,7 @@ def test(cfg,
multi_label=True): multi_label=True):
# Initialize/load model and set device # Initialize/load model and set device
if model is None: if model is None:
is_training = False
device = torch_utils.select_device(opt.device, batch_size=batch_size) device = torch_utils.select_device(opt.device, batch_size=batch_size)
verbose = opt.task == 'test' verbose = opt.task == 'test'
@ -47,6 +48,7 @@ def test(cfg,
if device.type != 'cpu' and torch.cuda.device_count() > 1: if device.type != 'cpu' and torch.cuda.device_count() > 1:
model = nn.DataParallel(model) model = nn.DataParallel(model)
else: # called by train.py else: # called by train.py
is_training = True
device = next(model.parameters()).device # get model device device = next(model.parameters()).device # get model device
verbose = False verbose = False
@ -61,7 +63,7 @@ def test(cfg,
# Dataloader # Dataloader
if dataloader is None: if dataloader is None:
dataset = LoadImagesAndLabels(path, imgsz, batch_size, rect=True, single_cls=opt.single_cls) dataset = LoadImagesAndLabels(path, imgsz, batch_size, rect=True, single_cls=opt.single_cls, pad=0.5)
batch_size = min(batch_size, len(dataset)) batch_size = min(batch_size, len(dataset))
dataloader = DataLoader(dataset, dataloader = DataLoader(dataset,
batch_size=batch_size, batch_size=batch_size,
@ -91,7 +93,7 @@ def test(cfg,
t0 += torch_utils.time_synchronized() - t t0 += torch_utils.time_synchronized() - t
# Compute loss # Compute loss
if hasattr(model, 'hyp'): # if model has loss hyperparameters if is_training: # if model has loss hyperparameters
loss += compute_loss(train_out, targets, model)[1][:3] # GIoU, obj, cls loss += compute_loss(train_out, targets, model)[1][:3] # GIoU, obj, cls
# Run NMS # Run NMS