def decodeMultiplePoses(
scores,
offsets,
displacementsFwd,
displacementsBwd,
width_factor,
height_factor,
outputStride=16,
maxPoseDetections=5,
scoreThreshold=0.5,
nmsRadius=30,
):
poses = []
squaredNmsRadius = nmsRadius * nmsRadius
scoresBuffer = np.squeeze(scores)
offsetsBuffer = np.squeeze(offsets)
displacementsBwdBuffer = np.squeeze(displacementsBwd)
displacementsFwdBuffer = np.squeeze(displacementsFwd)
height, width, numKeypoints = scoresBuffer.shape
queue = MaxHeap(height * width * numKeypoints, scoresBuffer)
buildPartWithScoreQueue(scoreThreshold, kLocalMaximumRadius, scoresBuffer,
queue)
while len(poses) < maxPoseDetections and queue.empty() is False:
root = queue.dequeue()
rootImageCoords = getImageCoords(root["part"], outputStride,
offsetsBuffer)
if (withinNmsRadiusOfCorrespondingPoint(
poses, squaredNmsRadius, rootImageCoords, root["part"]["id"])
is True):
continue
# Start a new detection instance at the position of the root.
keypoints = decodePose(
root,
scoresBuffer,
offsetsBuffer,
outputStride,
displacementsFwdBuffer,
displacementsBwdBuffer,
)
for keypoint in keypoints:
keypoint["position"]["y"] *= height_factor
keypoint["position"]["x"] *= width_factor
score = getInstanceScore(poses, squaredNmsRadius, keypoints)
poses.append({"keypoints": keypoints, "score": score})
return poses
def decodeMultiplePoses(scores, offsets, displacementsFwd, displacementsBwd, \
width_factor, height_factor, \
outputStride=16, maxPoseDetections=5, scoreThreshold= 0.5,
nmsRadius= 30):
poses = []
squaredNmsRadius = nmsRadius * nmsRadius
scoresBuffer = np.squeeze(scores)
offsetsBuffer = np.squeeze(offsets)
displacementsBwdBuffer = np.squeeze(displacementsBwd)
displacementsFwdBuffer = np.squeeze(displacementsFwd)
height, width, numKeypoints = scoresBuffer.shape
queue = MaxHeap(height * width * numKeypoints, scoresBuffer)
buildPartWithScoreQueue(scoreThreshold, kLocalMaximumRadius, scoresBuffer,
queue)
while len(poses) < maxPoseDetections and queue.empty() is False:
root = queue.dequeue()
rootImageCoords = getImageCoords(root['part'], outputStride,
offsetsBuffer)
if withinNmsRadiusOfCorrespondingPoint(poses, \
squaredNmsRadius, \
rootImageCoords, \
root['part']['id']) is True:
continue
#Start a new detection instance at the position of the root.
keypoints = decodePose(root, \
scoresBuffer, \
offsetsBuffer, \
outputStride, \
displacementsFwdBuffer, \
displacementsBwdBuffer)
for keypoint in keypoints:
keypoint['position']['y'] *= (height_factor)
keypoint['position']['x'] *= (width_factor)
score = getInstanceScore(poses, squaredNmsRadius, keypoints)
poses.append({'keypoints': keypoints, 'score': score})
return poses
