def select_det_ids(boxes,scores,nms_keep_ids,score_thresh,max_dets):
if nms_keep_ids is None:
nms_keep_ids = np.arange(0,scores.shape[0])
nms_keep_ids = nms_keep_ids.astype('int')
# Select non max suppressed dets
nms_scores = scores[nms_keep_ids]
nms_boxes = boxes[nms_keep_ids]
# Select dets above a score_thresh and which have area > 1
nms_ids_above_thresh = np.nonzero(nms_scores > score_thresh)[0]
nms_ids = []
for i in range(min(nms_ids_above_thresh.shape[0],max_dets)):
area = compute_area(nms_boxes[i],invalid=-1)
if area > 1:
nms_ids.append(i)
# If no dets satisfy previous criterion select the highest ranking one with area > 1
if len(nms_ids)==0:
for i in range(nms_keep_ids.shape[0]):
area = compute_area(nms_boxes[i],invalid=-1)
if area > 1:
nms_ids = [i]
break
# Convert nms ids to box ids
nms_ids = np.array(nms_ids,dtype=np.int32)
try:
ids = nms_keep_ids[nms_ids]
except:
import pdb; pdb.set_trace()
return ids
def assign_pose(human_box, pose_boxes, pose_keypoints, num_keypoints):
max_idx = -1
max_frac_inside = 0.7
found_match = False
for i, pose_box in enumerate(pose_boxes):
iou, intersection, union = compute_iou(human_box, pose_box,True)
pose_area = compute_area(pose_box)
frac_inside = intersection / pose_area
if frac_inside > max_frac_inside:
max_frac_inside = frac_inside
max_idx = i
found_match = True
if max_idx == -1:
keypoints = np.zeros([num_keypoints,3])
else:
keypoints = pose_keypoints[max_idx]
return keypoints, found_match