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
# Get results of original image
multiplier = get_multiplier(oriImg)
with torch.no_grad():
paf, heatmap = get_outputs(
multiplier, oriImg, model, 'rtpose')
heatmap_peaks = np.zeros_like(heatmap)
for i in range(19):
heatmap_peaks[:,:,i] = find_peaks(heatmap[:,:,i])
heatmap_peaks = heatmap_peaks.astype(np.float32)
heatmap = heatmap.astype(np.float32)
paf = paf.astype(np.float32)
#C++ postprocessing
pafprocess.process_paf(heatmap_peaks, heatmap, paf)
humans = []
for human_id in range(pafprocess.get_num_humans()):
human = Human([])
is_added = False
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],