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import numpy as np
class FasterRcnnBoxCoder:
"""Faster RCNN box coder.
Notes:
boxes should be in cxcywh format.
"""
def __init__(self, stddevs=None):
"""Constructor for FasterRcnnBoxCoder.
Args:
stddevs: List of 4 positive scalars to scale ty, tx, th and tw.
If set to None, does not perform scaling. For Faster RCNN,
the open-source implementation recommends using [0.1, 0.1, 0.2, 0.2].
"""
if stddevs:
assert len(stddevs) == 4
for scalar in stddevs:
assert scalar > 0
self.stddevs = stddevs
def encode(self, boxes, reference_boxes, copy=True):
"""Encode boxes with respect to reference boxes.
"""
if copy:
boxes = boxes.copy()
boxes[..., 2:4] += 1e-8
reference_boxes[..., 2:4] += 1e-8
boxes[..., 0:2] -= reference_boxes[..., 0:2]
boxes[..., 0:2] /= reference_boxes[..., 2:4]
boxes[..., 2:4] /= reference_boxes[..., 2:4]
boxes[..., 2:4] = np.log(boxes[..., 2:4], boxes[..., 2:4])
if self.stddevs:
boxes[..., 0:4] /= self.stddevs
return boxes
def decode(self, rel_boxes, reference_boxes, copy=True):
"""Decode relative codes to boxes.
"""
if copy:
rel_boxes = rel_boxes.copy()
if self.stddevs:
rel_boxes[..., 0:4] *= self.stddevs
rel_boxes[..., 0:2] *= reference_boxes[..., 2:4]
rel_boxes[..., 0:2] += reference_boxes[..., 0:2]
rel_boxes[..., 2:4] = np.exp(rel_boxes[..., 2:4], rel_boxes[..., 2:4])
rel_boxes[..., 2:4] *= reference_boxes[..., 2:4]
return rel_boxes
def decode_points(self, rel_points, reference_boxes, copy=True):
"""Decode relative codes to points.
"""
if copy:
rel_points = rel_points.copy()
if self.stddevs:
rel_points[..., 0::2] *= self.stddevs[0]
rel_points[..., 1::2] *= self.stddevs[1]
rel_points[..., 0::2] *= reference_boxes[..., 2:3]
rel_points[..., 1::2] *= reference_boxes[..., 3:4]
rel_points[..., 0::2] += reference_boxes[..., 0:1]
rel_points[..., 1::2] += reference_boxes[..., 1:2]
return rel_points
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