def __init__(self,
ann_fnames,
img_dir,
labels,
batch_size,
anchors=COCO_ANCHORS,
min_net_size=320,
max_net_size=608,
jitter=True,
shuffle=True):
self.ann_fnames = ann_fnames
self.img_dir = img_dir
self.lable_names = labels
self.min_net_size = (min_net_size //
DOWNSAMPLE_RATIO) * DOWNSAMPLE_RATIO
self.max_net_size = (max_net_size //
DOWNSAMPLE_RATIO) * DOWNSAMPLE_RATIO
self.jitter = jitter
self.anchors = create_anchor_boxes(anchors)
self.batch_size = batch_size
self.shuffle = shuffle
self.steps_per_epoch = int(len(ann_fnames) / batch_size)
self._epoch = 0
self._end_epoch = False
self._index = 0
self._initial_net_size()
def __init__(self,
ann_fnames,
img_dir,
labels,
batch_size,
anchors=[
23, 121, 30, 241, 40, 174, 42, 273, 53, 316, 56, 230, 66,
303, 81, 318, 104, 337
],
min_net_size=224,
max_net_size=224,
jitter=True,
shuffle=True):
self.ann_fnames = ann_fnames
self.img_dir = img_dir
self.lable_names = labels
self.min_net_size = (min_net_size //
DOWNSAMPLE_RATIO) * DOWNSAMPLE_RATIO
self.max_net_size = (max_net_size //
DOWNSAMPLE_RATIO) * DOWNSAMPLE_RATIO
# self.min_net_size = min_net_size
# self.max_net_size = max_net_size
self.jitter = jitter
self.anchors = create_anchor_boxes(anchors)
self.batch_size = batch_size
self.shuffle = shuffle
self.steps_per_epoch = int(len(ann_fnames) / batch_size)
self._epoch = 0
self._end_epoch = False
self._index = 0
self._initial_net_size()
def __init__(self,
ann_fnames,
img_dir,
labels,
batch_size,
anchors=COCO_ANCHORS,
min_net_size=320,
max_net_size=608,
data_augmentation=True,
shuffle=True,
keep_image_ratio=False):
self.ann_fnames = ann_fnames
self.img_dir = img_dir
self.lable_names = labels
self.min_net_size = (min_net_size //
DOWNSAMPLE_RATIO) * DOWNSAMPLE_RATIO
self.max_net_size = (max_net_size //
DOWNSAMPLE_RATIO) * DOWNSAMPLE_RATIO
self.data_augmentation = data_augmentation
self.anchors = create_anchor_boxes(anchors)
self.batch_size = batch_size
self.shuffle = shuffle
self.keep_image_ratio = keep_image_ratio
self.steps_per_epoch = int(len(ann_fnames) / batch_size)
self._epoch = -1
self._new_epoch = True
self._index = 0
self._net_size = self.min_net_size
def __init__(self,
dataDirectories,
labelNames,
batch_size,
anchors=COCO_ANCHORS,
image_size=320,
shuffleData=True,
augmentations=None,
normalizeImage=True):
self.annotationObjects = AnnotationObject.loadFromDirectories(
dataDirectories, labelNames, shuffleData)
self._numOfLabels = len(labelNames)
self.image_size = image_size
self.anchors = create_anchor_boxes(anchors)
self.batch_size = batch_size
self.augmentations = self._composeAugmentations(augmentations)
self.normalizeImage = normalizeImage
def __init__(self,
ann_fnames,
img_dir,
labels,
anchors,
min_net_size=320,
max_net_size=608,
jitter=True):
self.ann_fnames = ann_fnames
self.img_dir = img_dir
self.lable_names = labels
self.min_net_size = (min_net_size //
DOWNSAMPLE_RATIO) * DOWNSAMPLE_RATIO
self.max_net_size = (max_net_size //
DOWNSAMPLE_RATIO) * DOWNSAMPLE_RATIO
self.jitter = jitter
self.anchors = create_anchor_boxes(anchors)
self.net_size = DEFAULT_NETWORK_SIZE
def __init__(
self,
annotations,
anchors,
max_box_per_image=30,
batch_size=2,
min_net_size=320,
max_net_size=608,
shuffle=True,
jitter=True,
):
self.annotations = annotations
self._batch_size = batch_size
self.max_box_per_image = max_box_per_image
self.min_net_size = (min_net_size //
DOWNSAMPLE_RATIO) * DOWNSAMPLE_RATIO
self.max_net_size = (max_net_size //
DOWNSAMPLE_RATIO) * DOWNSAMPLE_RATIO
self.shuffle = shuffle
self.jitter = jitter
self.anchors = create_anchor_boxes(anchors)
self.net_size = DEFAULT_NETWORK_SIZE
if shuffle: np.random.shuffle(self.annotations)
# image = image / 255.
list_ys = _create_empty_xy(image_size, numOfLabels)
for original_box, label in zip(boxes, coded_labels):
max_anchor, scale_index, box_index = _find_match_anchor(
original_box, anchors)
_coded_box = _encode_box(list_ys[scale_index], original_box,
max_anchor, image_size, image_size)
_assign_box(list_ys[scale_index], box_index, _coded_box, label)
return image, list_ys[2], list_ys[1], list_ys[0]
anchors = create_anchor_boxes([
10, 13, 16, 30, 33, 23, 30, 61, 62, 45, 59, 119, 116, 90, 156, 198, 373,
326
])
labels = [*range(10)]
numOfLabels = len(labels)
net_size = 288
image_size = net_size
def makeImage(value):
return np.full([image_size, image_size, 3], value, np.uint8)
def main():
annObjects = [(makeImage(1), np.array([(10, 10, 20, 20)]), [1]),
(makeImage(2), np.array([(10, 10, 20, 20),
(10, 10, 60, 60)]), [2, 3])]
def __init__(self, net_size, nClasses, anchors):
self.net_size = net_size
self.nClasses = nClasses
self.anchorBoxes = create_anchor_boxes(anchors)