def paf_to_pose_cpp(heatmaps, pafs, config):
humans = []
joint_list_per_joint_type = NMS(heatmaps,
upsampFactor=config.MODEL.DOWNSAMPLE,
config=config)
joint_list = np.array([
tuple(peak) + (joint_type, )
for joint_type, joint_peaks in enumerate(joint_list_per_joint_type)
for peak in joint_peaks
]).astype(np.float32)
if joint_list.shape[0] > 0:
joint_list = np.expand_dims(joint_list, 0)
paf_upsamp = cv2.resize(pafs,
None,
fx=config.MODEL.DOWNSAMPLE,
fy=config.MODEL.DOWNSAMPLE,
interpolation=cv2.INTER_NEAREST)
heatmap_upsamp = cv2.resize(heatmaps,
None,
fx=config.MODEL.DOWNSAMPLE,
fy=config.MODEL.DOWNSAMPLE,
interpolation=cv2.INTER_NEAREST)
pafprocess.process_paf(joint_list, heatmap_upsamp, paf_upsamp)
for human_id in range(pafprocess.get_num_humans()):
human = Human([])
is_added = False
for part_idx in range(config.MODEL.NUM_KEYPOINTS):
c_idx = int(pafprocess.get_part_cid(human_id, part_idx))
if c_idx < 0:
continue
is_added = True
human.body_parts[part_idx] = BodyPart(
'%d-%d' % (human_id, part_idx), part_idx,
float(pafprocess.get_part_x(c_idx)) /
heatmap_upsamp.shape[1],
float(pafprocess.get_part_y(c_idx)) /
heatmap_upsamp.shape[0], pafprocess.get_part_score(c_idx))
if is_added:
score = pafprocess.get_score(human_id)
human.score = score
humans.append(human)
return humans
for part_idx in range(18):
c_idx = int(pafprocess.get_part_cid(human_id, part_idx))
if c_idx < 0:
continue
is_added = True
human.body_parts[part_idx] = BodyPart(
'%d-%d' % (human_id, part_idx), part_idx,
float(pafprocess.get_part_x(c_idx)) / heatmap.shape[1],
float(pafprocess.get_part_y(c_idx)) / heatmap.shape[0],
pafprocess.get_part_score(c_idx)
)
if is_added:
score = pafprocess.get_score(human_id)
human.score = score
humans.append(human)
out = draw_humans(oriImg, humans)
# Display the resulting frame
cv2.imshow('Video', out)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# When everything is done, release the capture
video_capture.release()
cv2.destroyAllWindows()