def pd_postprocess(self, inference):
scores = np.array(inference.getLayerFp16("classificators"), dtype=np.float16) # 896
bboxes = np.array(inference.getLayerFp16("regressors"), dtype=np.float16).reshape((self.nb_anchors,18)) # 896x18
# Decode bboxes
self.regions = mpu.decode_bboxes(self.pd_score_thresh, scores, bboxes, self.anchors)
# Non maximum suppression
self.regions = mpu.non_max_suppression(self.regions, self.pd_nms_thresh)
if self.use_lm:
mpu.detections_to_rect(self.regions)
mpu.rect_transformation(self.regions, self.video_size, self.video_size)
def pd_postprocess(self, inference):
scores = np.squeeze(inference[self.pd_scores]) # 896
bboxes = inference[self.pd_bboxes][0] # 896x12
# Decode bboxes
self.regions = mpu.decode_bboxes(self.pd_score_thresh,
scores,
bboxes,
self.anchors,
best_only=not self.multi_detection)
# Non maximum suppression (not needed if best_only is True)
if self.multi_detection:
self.regions = mpu.non_max_suppression(self.regions,
self.pd_nms_thresh)
mpu.detections_to_rect(self.regions,
kp_pair=[0, 1] if self.full_body else [2, 3])
mpu.rect_transformation(self.regions, self.frame_size, self.frame_size)
def pd_postprocess(self, inference):
scores = np.array(inference.getLayerFp16("classificators"),
dtype=np.float16) # 896
bboxes = np.array(inference.getLayerFp16("regressors"),
dtype=np.float16).reshape(
(self.nb_anchors, 12)) # 896x12
# Decode bboxes
self.regions = mpu.decode_bboxes(self.pd_score_thresh,
scores,
bboxes,
self.anchors,
best_only=not self.multi_detection)
# Non maximum suppression (not needed if best_only is True)
if self.multi_detection:
self.regions = mpu.non_max_suppression(self.regions,
self.pd_nms_thresh)
mpu.detections_to_rect(self.regions,
kp_pair=[0, 1] if self.full_body else [2, 3])
mpu.rect_transformation(self.regions, self.frame_size, self.frame_size)