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add stride to datasets.py

pull/215/head
Glenn Jocher 2020-06-24 13:02:27 -07:00
parent 3b062254a6
commit b8557f87e3
3 changed files with 7 additions and 4 deletions
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1
test.py
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@ -73,6 +73,7 @@ def test(data,
batch_size, batch_size,
rect=True, # rectangular inference rect=True, # rectangular inference
single_cls=opt.single_cls, # single class mode single_cls=opt.single_cls, # single class mode
stride=int(max(model.stride)), # model stride
pad=0.5) # padding pad=0.5) # padding
batch_size = min(batch_size, len(dataset)) batch_size = min(batch_size, len(dataset))
nw = min([os.cpu_count(), batch_size if batch_size > 1 else 0, 8]) # number of workers nw = min([os.cpu_count(), batch_size if batch_size > 1 else 0, 8]) # number of workers

6
train.py
View File

@ -160,7 +160,8 @@ def train(hyp):
hyp=hyp, # augmentation hyperparameters hyp=hyp, # augmentation hyperparameters
rect=opt.rect, # rectangular training rect=opt.rect, # rectangular training
cache_images=opt.cache_images, cache_images=opt.cache_images,
single_cls=opt.single_cls) single_cls=opt.single_cls,
stride=gs)
mlc = np.concatenate(dataset.labels, 0)[:, 0].max() # max label class mlc = np.concatenate(dataset.labels, 0)[:, 0].max() # max label class
assert mlc < nc, 'Label class %g exceeds nc=%g in %s. Correct your labels or your model.' % (mlc, nc, opt.cfg) assert mlc < nc, 'Label class %g exceeds nc=%g in %s. Correct your labels or your model.' % (mlc, nc, opt.cfg)
@ -179,7 +180,8 @@ def train(hyp):
hyp=hyp, hyp=hyp,
rect=True, rect=True,
cache_images=opt.cache_images, cache_images=opt.cache_images,
single_cls=opt.single_cls), single_cls=opt.single_cls,
stride=gs),
batch_size=batch_size, batch_size=batch_size,
num_workers=nw, num_workers=nw,
pin_memory=True, pin_memory=True,

4
utils/datasets.py
View File

@ -258,7 +258,7 @@ 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, pad=0.0): cache_images=False, single_cls=False, stride=32, 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
@ -325,7 +325,7 @@ 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.ceil(np.array(shapes) * img_size / 32. + pad).astype(np.int) * 32 self.batch_shapes = np.ceil(np.array(shapes) * img_size / stride + pad).astype(np.int) * stride
# Cache labels # Cache labels
self.imgs = [None] * n self.imgs = [None] * n