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dataset padding mode

This commit is contained in:
Glenn Jocher 2020-06-03 13:55:33 -07:00
parent eb97b2e413
commit 2a0aff685a
2 changed files with 9 additions and 3 deletions
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8
test.py
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@ -56,8 +56,14 @@ def test(data,
# Dataloader # Dataloader
if dataloader is None: if dataloader is None:
fast |= conf_thres > 0.001 # enable fast mode
path = data['test'] if opt.task == 'test' else data['val'] # path to val/test images path = data['test'] if opt.task == 'test' else data['val'] # path to val/test images
dataset = LoadImagesAndLabels(path, imgsz, batch_size, rect=True, single_cls=opt.single_cls) dataset = LoadImagesAndLabels(path,
imgsz,
batch_size,
rect=True, # rectangular inference
single_cls=opt.single_cls, # single class mode
pad=0.0 if fast else 0.5) # padding
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,

4
utils/datasets.py
View File

@ -257,7 +257,7 @@ class LoadStreams: # multiple IP or RTSP cameras
class LoadImagesAndLabels(Dataset): # for training/testing class LoadImagesAndLabels(Dataset): # for training/testing
def __init__(self, path, img_size=416, batch_size=16, augment=False, hyp=None, rect=False, image_weights=False, def __init__(self, path, img_size=416, batch_size=16, augment=False, hyp=None, rect=False, image_weights=False,
cache_images=False, single_cls=False): cache_images=False, single_cls=False, pad=0.0):
try: try:
path = str(Path(path)) # os-agnostic path = str(Path(path)) # os-agnostic
parent = str(Path(path).parent) + os.sep parent = str(Path(path).parent) + os.sep
@ -322,7 +322,7 @@ class LoadImagesAndLabels(Dataset): # for training/testing
elif mini > 1: elif mini > 1:
shapes[i] = [1, 1 / mini] shapes[i] = [1, 1 / mini]
self.batch_shapes = np.round(np.array(shapes) * img_size / 32. + 1.).astype(np.int) * 32 self.batch_shapes = np.ceil(np.array(shapes) * img_size / 32. + pad).astype(np.int) * 32
# Cache labels # Cache labels
self.imgs = [None] * n self.imgs = [None] * n