def precision_recall(num_gbboxes, tp, fp, scope=None):
"""Compute precision and recall from true positives and false
positives booleans arrays
"""
# Sort by score.
with tf.name_scope(scope, 'precision_recall'):
# Computer recall and precision.
tp = tf.reduce_sum(tf.cast(tp, tf.float32), axis=0)
fp = tf.reduce_sum(tf.cast(fp, tf.float32), axis=0)
recall = tfe_math.safe_divide(tp, tf.cast(num_gbboxes, tf.float32), 'recall')
precision = tfe_math.safe_divide(tp, tp + fp, 'precision')
return tf.tuple([precision, recall])
def bboxes_intersection(bbox_ref, bboxes, name=None):
"""Compute relative intersection between a reference box and a
collection of bounding boxes. Namely, compute the quotient between
intersection area and box area.
Args:
bbox_ref: (N, 4) or (4,) Tensor with reference bounding box(es).
bboxes: (N, 4) Tensor, collection of bounding boxes.
Return:
(N,) Tensor with relative intersection.
"""
with tf.name_scope(name, 'bboxes_intersection'):
# Should be more efficient to first transpose.
bboxes = tf.transpose(bboxes)
bbox_ref = tf.transpose(bbox_ref)
# Intersection bbox and volume.
int_ymin = tf.maximum(bboxes[0], bbox_ref[0])
int_xmin = tf.maximum(bboxes[1], bbox_ref[1])
int_ymax = tf.minimum(bboxes[2], bbox_ref[2])
int_xmax = tf.minimum(bboxes[3], bbox_ref[3])
h = tf.maximum(int_ymax - int_ymin, 0.)
w = tf.maximum(int_xmax - int_xmin, 0.)
# Volumes.
inter_vol = h * w
bboxes_vol = (bboxes[2] - bboxes[0]) * (bboxes[3] - bboxes[1])
scores = tfe_math.safe_divide(inter_vol, bboxes_vol, 'intersection')
return scores
def bboxes_jaccard(bbox_ref, bboxes, name=None):
"""Compute jaccard score between a reference box and a collection
of bounding boxes.
Args:
bbox_ref: (N, 4) or (4,) Tensor with reference bounding box(es).
bboxes: (N, 4) Tensor, collection of bounding boxes.
Return:
(N,) Tensor with Jaccard scores.
"""
with tf.name_scope(name, 'bboxes_jaccard'):
# Should be more efficient to first transpose.
bboxes = tf.transpose(bboxes)
bbox_ref = tf.transpose(bbox_ref)
# Intersection bbox and volume.
int_ymin = tf.maximum(bboxes[0], bbox_ref[0])
int_xmin = tf.maximum(bboxes[1], bbox_ref[1])
int_ymax = tf.minimum(bboxes[2], bbox_ref[2])
int_xmax = tf.minimum(bboxes[3], bbox_ref[3])
h = tf.maximum(int_ymax - int_ymin, 0.)
w = tf.maximum(int_xmax - int_xmin, 0.)
# Volumes.
inter_vol = h * w
union_vol = -inter_vol \
+ (bboxes[2] - bboxes[0]) * (bboxes[3] - bboxes[1]) \
+ (bbox_ref[2] - bbox_ref[0]) * (bbox_ref[3] - bbox_ref[1])
jaccard = tfe_math.safe_divide(inter_vol, union_vol, 'jaccard')
return jaccard
def bboxes_intersection(bbox_ref, bboxes, name=None):
"""Compute relative intersection between a reference box and a
collection of bounding boxes. Namely, compute the quotient between
intersection area and box area.
Args:
bbox_ref: (N, 4) or (4,) Tensor with reference bounding box(es).
bboxes: (N, 4) Tensor, collection of bounding boxes.
Return:
(N,) Tensor with relative intersection.
"""
with tf.name_scope(name, 'bboxes_intersection'):
# Should be more efficient to first transpose.
bboxes = tf.transpose(bboxes)
bbox_ref = tf.transpose(bbox_ref)
# Intersection bbox and volume.
int_ymin = tf.maximum(bboxes[0], bbox_ref[0])
int_xmin = tf.maximum(bboxes[1], bbox_ref[1])
int_ymax = tf.minimum(bboxes[2], bbox_ref[2])
int_xmax = tf.minimum(bboxes[3], bbox_ref[3])
h = tf.maximum(int_ymax - int_ymin, 0.)
w = tf.maximum(int_xmax - int_xmin, 0.)
# Volumes.
inter_vol = h * w
bboxes_vol = (bboxes[2] - bboxes[0]) * (bboxes[3] - bboxes[1])
scores = tfe_math.safe_divide(inter_vol, bboxes_vol, 'intersection')
return scores
def bboxes_jaccard(bbox_ref, bboxes, name=None):
"""Compute jaccard score between a reference box and a collection
of bounding boxes.
Args:
bbox_ref: (N, 4) or (4,) Tensor with reference bounding box(es).
bboxes: (N, 4) Tensor, collection of bounding boxes.
Return:
(N,) Tensor with Jaccard scores.
"""
with tf.name_scope(name, 'bboxes_jaccard'):
# Should be more efficient to first transpose.
bboxes = tf.transpose(bboxes)
bbox_ref = tf.transpose(bbox_ref)
# Intersection bbox and volume.
int_ymin = tf.maximum(bboxes[0], bbox_ref[0])
int_xmin = tf.maximum(bboxes[1], bbox_ref[1])
int_ymax = tf.minimum(bboxes[2], bbox_ref[2])
int_xmax = tf.minimum(bboxes[3], bbox_ref[3])
h = tf.maximum(int_ymax - int_ymin, 0.)
w = tf.maximum(int_xmax - int_xmin, 0.)
# Volumes.
inter_vol = h * w
union_vol = -inter_vol \
+ (bboxes[2] - bboxes[0]) * (bboxes[3] - bboxes[1]) \
+ (bbox_ref[2] - bbox_ref[0]) * (bbox_ref[3] - bbox_ref[1])
jaccard = tfe_math.safe_divide(inter_vol, union_vol, 'jaccard')
return jaccard
def bboxes_intersection(bbox_ref, bboxes, name=None):
"""Compute relative intersection between a reference box and a
collection of bounding boxes. Namely, compute the quotient between
intersection area and box area.
Args:
bbox_ref: (N, 4) or (4,) Tensor with reference bounding box(es).
bboxes: (N, 4) Tensor, collection of bounding boxes.
Return:
(N,) Tensor with relative intersection.
"""
with tf.name_scope(name, 'bboxes_intersection'):
# Should be more efficient to first transpose.
bboxes = tf.transpose(bboxes)
bbox_ref = tf.transpose(bbox_ref)
# Intersection bbox and volume.
int_ymin = tf.maximum(bboxes[0], bbox_ref[0])
int_xmin = tf.maximum(bboxes[1], bbox_ref[1])
int_ymax = tf.minimum(bboxes[2], bbox_ref[2])
int_xmax = tf.minimum(bboxes[3], bbox_ref[3])
h = tf.maximum(int_ymax - int_ymin, 0.)
w = tf.maximum(int_xmax - int_xmin, 0.)
# Volumes.
inter_vol = h * w # 各个框在[0,0,1,1]内的面积
bboxes_vol = (bboxes[2] - bboxes[0]) * (bboxes[3] - bboxes[1]) # 各个框面积
scores = tfe_math.safe_divide(inter_vol, bboxes_vol, 'intersection')
# from tensorflow.python.ops import math_ops
# 大于0的位置返回面积比，小于0的位置返回0
# tf.where(math_ops.greater(bboxes_vol, 0), # 返回bool表是否大于0
# math_ops.divide(inter_vol, bboxes_vol),
# tf.zeros_like(inter_vol), name=name)
return scores
def has_bboxes(bbox_ref=bbox_ref, bboxes=bboxes):
bboxes = tf.transpose(bboxes)
bbox_ref = tf.transpose(bbox_ref)
# Intersection bbox and volume.
int_ymin = tf.maximum(bboxes[0], bbox_ref[0])
int_xmin = tf.maximum(bboxes[1], bbox_ref[1])
int_ymax = tf.minimum(bboxes[2], bbox_ref[2])
int_xmax = tf.minimum(bboxes[3], bbox_ref[3])
h = tf.maximum(int_ymax - int_ymin, 0.)
w = tf.maximum(int_xmax - int_xmin, 0.)
# Volumes.
inter_vol = h * w
union_vol = -inter_vol \
+ (bboxes[2] - bboxes[0]) * (bboxes[3] - bboxes[1]) \
+ (bbox_ref[2] - bbox_ref[0]) * (bbox_ref[3] - bbox_ref[1])
jaccard = tfe_math.safe_divide(inter_vol, union_vol, 'jaccard')
return jaccard