def prepare_test_data_RGB(img_dir, out_dir):
mtcnn_dir = os.path.join(out_dir, "mtcnn_result/")
lmk3D_ori_txt_path = os.path.join(out_dir, "lmk_3D_86pts_ori.txt")
lmk2D_ori_txt_path = os.path.join(out_dir, "lmk_2D_68pts_ori.txt")
lmk3D_crop_txt_path = os.path.join(out_dir, "lmk_3D_86pts.txt")
lmk2D_crop_txt_path = os.path.join(out_dir, "lmk_2D_68pts.txt")
crop_dir = out_dir
seg_dir = out_dir
print("start MTCNN")
pb_path = os.path.join(FLAGS.pb_path, "mtcnn_model.pb")
names_list = detect_face_with_mtcnn.detect_with_MTCNN(img_dir, mtcnn_dir, pb_path)
print("start detect 86pt 3D lmk")
tf.reset_default_graph()
pb_path = os.path.join(FLAGS.pb_path, "lmk3D_86_model.pb")
detect_3D_landmark.detect_lmk86(
img_dir, mtcnn_dir, lmk3D_ori_txt_path, names_list, pb_path
)
print("start detect 68pt 2D lmk") # need to transfer RGB in the function
tf.reset_default_graph()
pb_path = os.path.join(FLAGS.pb_path, "lmk2D_68_model.pb")
detect_2Dlmk_all_imgs(
pb_path, img_dir, lmk3D_ori_txt_path, lmk2D_ori_txt_path
) # N x 68 x 2
print("start crop by 3D lmk")
crop_img_by_lmk(
lmk2D_ori_txt_path,
lmk3D_ori_txt_path,
lmk2D_crop_txt_path,
lmk3D_crop_txt_path,
img_dir,
crop_dir,
orig=True,
)
print("start face seg") # need to transfer RGB in the function
tf.reset_default_graph()
pb_path = os.path.join(FLAGS.pb_path, "faceseg_model.pb")
face_seg(pb_path, lmk3D_crop_txt_path, crop_dir, seg_dir)
print("finish RGB data preparation")
def prepare_test_data_RGBD(img_dir, out_dir):
mtcnn_dir = os.path.join(out_dir, "mtcnn_result/")
lmk3D_ori_txt_path = os.path.join(out_dir, "lmk_3D_86pts_ori.txt")
lmk2D_ori_txt_path = os.path.join(out_dir, "lmk_2D_68pts_ori.txt")
lmk3D_crop_txt_path = os.path.join(out_dir, "lmk_3D_86pts.txt")
lmk2D_crop_txt_path = os.path.join(out_dir, "lmk_2D_68pts.txt")
out_img_names_path = os.path.join(out_dir, "img_names.txt")
crop_dir = out_dir
seg_dir = out_dir
print("check RGBD data")
files = glob.glob(osp.join(img_dir, "*.jpg"))
files.extend(glob.glob(osp.join(img_dir, "*.JPG")))
dep_files = glob.glob(osp.join(img_dir, "*.png"))
dep_files.extend(glob.glob(osp.join(img_dir, "*.PNG")))
files.sort()
dep_files.sort()
if len(files) == len(dep_files) is False:
raise Exception("The number of depth img is not same with RGB img.")
for index in range(0, len(files)):
img = cv2.imread(files[index])
dep_img = cv2.imread(dep_files[index])
if img.shape[0] < img.shape[1]:
img = cv2.transpose(img)
dep_img = cv2.transpose(dep_img)
cv2.imwrite(img_dir + files[index].split("/")[-1], img)
cv2.imwrite(img_dir + dep_files[index].split("/")[-1], dep_img)
print("start MTCNN")
pb_path = os.path.join(FLAGS.pb_path, "mtcnn_model.pb")
names_list, dep_name_list = detect_face_with_mtcnn.detect_with_MTCNN(
img_dir, mtcnn_dir, pb_path, "depth"
)
print("start detect 86pt 3D lmk")
tf.reset_default_graph()
pb_path = os.path.join(FLAGS.pb_path, "lmk3D_86_model.pb")
detect_3D_landmark.detect_lmk86(
img_dir, mtcnn_dir, lmk3D_ori_txt_path, names_list, pb_path
)
print("start detect 68pt 2D lmk") # need to transfer RGB in the function
tf.reset_default_graph()
pb_path = os.path.join(FLAGS.pb_path, "lmk2D_68_model.pb")
detect_2Dlmk_all_imgs(
pb_path, img_dir, lmk3D_ori_txt_path, lmk2D_ori_txt_path
) # N x 68 x 2
print("start crop by 3D lmk")
crop_img_by_lmk(
lmk2D_ori_txt_path,
lmk3D_ori_txt_path,
lmk2D_crop_txt_path,
lmk3D_crop_txt_path,
img_dir,
crop_dir,
orig=False,
)
print("start face seg") # need to transfer RGB in the function
tf.reset_default_graph()
pb_path = os.path.join(FLAGS.pb_path, "faceseg_model.pb")
face_seg(pb_path, lmk3D_crop_txt_path, crop_dir, seg_dir)
fopen = open(out_img_names_path, "w")
for i in range(0, len(names_list)):
text = names_list[i] + "," + dep_name_list[i] + "\n"
fopen.write(text)
fopen.close()
print("finish RGBD data preparation")