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[fix] PoseAndFaceDetection's key_frame_body_points output value #12

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[fix] PoseAndFaceDetection's key_frame_body_points output value #12

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23 changes: 13 additions & 10 deletions nodes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -188,22 +188,25 @@ def process(self, model, images, width, height, retarget_image=None):
key_frame_index_list = list(range(0, len(pose_metas), key_frame_step))

key_points_index = [0, 1, 2, 5, 8, 11, 10, 13]

points_dict_list = []
for key_frame_index in key_frame_index_list:
keypoints_body_list = []
body_key_points = pose_metas[key_frame_index]['keypoints_body']
for each_index in key_points_index:
each_keypoint = body_key_points[each_index]
if None is each_keypoint:
if each_keypoint is None or len(each_keypoint) != 3:
continue
keypoints_body_list.append(each_keypoint)

keypoints_body = np.array(keypoints_body_list)[:, :2]
wh = np.array([[pose_metas[0]['width'], pose_metas[0]['height']]])
points = (keypoints_body * wh).astype(np.int32)
points_dict_list = []
for point in points:
points_dict_list.append({"x": int(point[0]), "y": int(point[1])})
if each_keypoint[2] > 0.6: # only consider keypoints with confidence > 0.6
keypoints_body_list.append(each_keypoint)
if len(keypoints_body_list) < 2: #too few keypoints, skip this frame
continue
else:
keypoints_body = np.array(keypoints_body_list)[:, :2]
wh = np.array([[pose_metas[key_frame_index]['width'], pose_metas[key_frame_index]['height']]])
points = (keypoints_body * wh).astype(np.int32)
for point in points:
points_dict_list.append({"x": int(point[0]), "y": int(point[1])})
break # only use the first valid key frame

pose_data = {
"retarget_image": refer_img if retarget_image is not None else None,
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