def load_meta_data(cfg):
"""
Set the meta directories:
|--self._opt.output_dir:
|--models:
|--self._opt.model_id:
|--opt_train.txt or opt_test.txt
Returns:
meta_data (EasyDict): the meta directories, it contains the followings:
--checkpoints_dir:
"""
output_dir = cfg.output_dir
meta_data = EasyDict()
meta_data["checkpoints_dir"] = mkdir(
os.path.join(output_dir, "models", cfg.model_id))
meta_data["personalized_ckpt_path"] = os.path.join(
meta_data["checkpoints_dir"], "personalized.pth")
meta_data["root_primitives_dir"] = mkdir(
os.path.join(cfg.output_dir, "primitives"))
meta_data["opt_path"] = os.path.join(meta_data["checkpoints_dir"],
"opts.txt")
if "src_path" in cfg:
src_inputs = parse_src_input(cfg.src_path)
root_primitives_dir = meta_data["root_primitives_dir"]
meta_src = []
for meta_inp in src_inputs:
meta_proc = MetaProcess(meta_inp, root_primitives_dir)
meta_src.append(meta_proc)
meta_data["meta_src"] = meta_src
if "ref_path" in cfg:
ref_inputs = parse_ref_input(cfg.ref_path)
root_primitives_dir = meta_data["root_primitives_dir"]
meta_ref = []
for meta_inp in ref_inputs:
meta_proc = MetaProcess(meta_inp, root_primitives_dir)
meta_ref.append(meta_proc)
meta_data["meta_ref"] = meta_ref
return meta_data
def _setup_dirs(self, meta_src, meta_ref):
src_name = meta_src.meta_input["name"]
ref_name = meta_ref.meta_input["name"]
src_ref_name = f"{src_name}-{ref_name}"
synthesized_dir = mkdir(os.path.join(meta_src.primitives_dir, "synthesis"))
out_img_dir = mkdir(os.path.join(synthesized_dir, "imitations", f"{src_ref_name}"))
self.src_name = src_name
self.ref_name = ref_name
self.src_ref_name = src_ref_name
self.synthesized_dir = synthesized_dir
self.out_img_dir = out_img_dir
self.out_mp4 = out_img_dir + ".mp4"
def __init__(self, meta_input: MetaInputInfo, root_primitives_dir: str):
"""
Args:
meta_input (MetaInputInfo):
root_primitives_dir:
"""
primitives_dir = mkdir(os.path.join(root_primitives_dir, meta_input.name))
processed_dir = mkdir(os.path.join(primitives_dir, "processed"))
meta_input = self.update_meta_input(meta_input, processed_dir)
self.meta_input = meta_input.get_info()
self.primitives_dir = primitives_dir
self.processed_dir = processed_dir
self.vid_info_path = os.path.join(processed_dir, "vid_info.pkl")
def __init__(self, meta_src):
"""
Args:
meta_src (MetaProcess):
"""
src_name = meta_src.meta_input["name"]
synthesized_dir = mkdir(os.path.join(meta_src.primitives_dir, "synthesis"))
out_img_dir = mkdir(os.path.join(synthesized_dir, "viewers"))
self.src_name = src_name
self.out_img_dir = out_img_dir
self.out_mp4 = out_img_dir + ".mp4"
def format_imgs_dir(src_path, imgs_dir):
if not osp.exists(src_path):
raise FileNotFoundError(f"{src_path} does not exist. Please provide a existing path.")
if is_image_file(src_path):
# if `src_path` is a image path, the the image will be copied to `output_dir/frames`.
imgs_dir = mkdir(imgs_dir)
dst_path = osp.join(imgs_dir, osp.split(src_path)[-1])
# create a symbolic link
if src_path != dst_path and not osp.exists(dst_path):
# TODO, handle the Privilege Error (WinError 1314) of os.symlink in Windows? Need help.
if platform.system().lower() == "windows":
shutil.copy(src_path, dst_path)
else:
os.symlink(osp.abspath(src_path), osp.abspath(dst_path))
elif is_video_file(src_path):
imgs_dir = mkdir(imgs_dir)
# * if `src_path` is a video path, then use `ffmpeg` to extract the frames into `output_dir/frames`.
video2frames(src_path, imgs_dir)
elif osp.isdir(src_path):
# * if `src_path` is a directory that contains multiple images, then these images will
# be copied to `output_dir/frames`.
if src_path != imgs_dir and not osp.exists(imgs_dir):
# TODO, handle the Privilege Error (WinError 1314) of os.symlink in Windows? Need help.
if platform.system().lower() == "windows":
if osp.exists(imgs_dir):
shutil.rmtree(imgs_dir)
shutil.copytree(src_path, imgs_dir)
else:
os.symlink(osp.abspath(src_path), osp.abspath(imgs_dir))
else:
raise ValueError("imgs_dir {} is not image path, video path and image directory.".format(imgs_dir))
return imgs_dir
def __init__(self, meta_src, meta_ref):
"""
Args:
meta_src (MetaProcess):
meta_ref (MetaProcess):
"""
src_name = meta_src.meta_input["name"]
ref_name = meta_ref.meta_input["name"]
synthesized_dir = mkdir(
os.path.join(meta_src.primitives_dir, "synthesis"))
src_ref_name = f"{src_name}-{ref_name}"
imitation_dir = mkdir(
os.path.join(synthesized_dir, "imitations", f"{src_ref_name}"))
swapper_dir = mkdir(
os.path.join(synthesized_dir, "swappers", f"{src_ref_name}"))
viewer_dir = mkdir(os.path.join(synthesized_dir, "viewers"))
self.src_name = src_name
self.ref_name = ref_name
self.audio = meta_ref.meta_input["audio"]
self.fps = meta_ref.meta_input["fps"]
self.pose_fc = meta_ref.meta_input["pose_fc"]
self.cam_fc = meta_ref.meta_input["cam_fc"]
self.src_ref_name = src_ref_name
self.synthesized_dir = synthesized_dir
self.imitation_dir = imitation_dir
self.imitation_mp4 = imitation_dir + ".mp4"
self.swapper_dir = swapper_dir
self.swapper_mp4 = swapper_dir + ".mp4"
self.viewer_dir = viewer_dir
self.viewer_mp4 = viewer_dir + ".mp4"
def _setup_dirs(self, meta_src_or_list, meta_ref):
all_src_name = []
for meta_src in meta_src_or_list:
all_src_name.append(meta_src.meta_input["name"])
src_name = "+".join(all_src_name)
# get the primary meta_src
meta_src = meta_src_or_list[0]
ref_name = meta_ref.meta_input["name"]
src_ref_name = f"{src_name}-{ref_name}"
synthesized_dir = mkdir(os.path.join(meta_src.primitives_dir, "synthesis"))
out_img_dir = mkdir(os.path.join(synthesized_dir, "swappers", f"{src_ref_name}"))
self.src_name = src_name
self.ref_name = ref_name
self.src_ref_name = src_ref_name
self.synthesized_dir = synthesized_dir
self.out_img_dir = out_img_dir
self.out_mp4 = out_img_dir + ".mp4"
help="the root directory of iPER dataset.")
parser.add_argument("--gpu_ids", type=str, default="9", help="the gpu ids.")
args = parser.parse_args()
# the render image size
IMAGE_SIZE = 1080
MotionSynthetic_root_dir = args.output_dir
MotionSynthetic_video_dir = os.path.join(MotionSynthetic_root_dir, "videos")
MotionSynthetic_poses_dir = os.path.join(MotionSynthetic_root_dir, "poses")
MotionSynthetic_train_txt = os.path.join(MotionSynthetic_root_dir, "train.txt")
MotionSynthetic_val_txt = os.path.join(MotionSynthetic_root_dir, "val.txt")
MotionSynthetic_video_zip = os.path.join(MotionSynthetic_root_dir,
"videos.zip")
MotionSynthetic_poses_zip = os.path.join(MotionSynthetic_root_dir, "poses.zip")
MotionSynthetic_processed_dir = mkdir(
os.path.join(MotionSynthetic_root_dir, "primitives"))
# MotionSynthetic URLs
MotionSynthetic_url = "http://download.impersonator.org:20086/datasets/motionSynthetic"
MotionSynthetic_poses_url = os.path.join(MotionSynthetic_url, "poses.zip")
MotionSynthetic_videos_url = os.path.join(MotionSynthetic_url, "videos.zip")
MotionSynthetic_train_txt_url = os.path.join(MotionSynthetic_url, "train.txt")
MotionSynthetic_val_txt_url = os.path.join(MotionSynthetic_url, "val.txt")
def get_video_dirs(txt_file):
vid_names = []
with open(txt_file, "r") as reader:
for line in reader:
line = line.rstrip()
vid_names.append(line)
def __init__(self, meta_process):
"""
Args:
meta_process (MetaProcess):
"""
processed_dir = meta_process.processed_dir
self.vid_infos = {
"input_info":
meta_process.get_info(),
"src_img_dir":
os.path.join(processed_dir, "orig_images"),
"src_num_imgs":
0,
"out_img_dir":
mkdir(os.path.join(processed_dir, "images")),
"out_bg_dir":
mkdir(os.path.join(processed_dir, "background")),
"out_actual_bg_dir":
mkdir(os.path.join(processed_dir, "actual_background")),
"out_parse_dir":
mkdir(os.path.join(processed_dir, "parse")),
"out_visual_path":
os.path.join(processed_dir, "visual.mp4"),
"has_run_detector":
False,
"has_run_cropper":
False,
"has_run_3dpose":
False,
"has_find_front":
False,
"has_run_parser":
False,
"has_run_inpaintor":
False,
"has_run_deform":
False,
"has_finished":
False,
"orig_shape": (),
"valid_img_info": {
"names": [],
"ids": [],
"stage": ""
},
"processed_pose2d": {
"boxes_XYXY": [],
"keypoints": []
},
"processed_cropper": {
"crop_shape": (),
"active_boxes_XYXY": [],
"crop_boxes_XYXY": [],
"crop_keypoints": []
},
"processed_pose3d": {
"cams": [],
"pose": [],
"shape": [],
"init_pose": [],
"init_shape": []
},
"processed_front_info": {
"ft": {
"body_num": [],
"face_num": [],
"ids": []
},
"bk": {
"body_num": [],
"face_num": [],
"ids": []
}
},
"processed_parse": {
"mask_suffix": "mask.png",
"alpha_suffix": "alpha.png"
},
"processed_background": {
"inpainted_suffix": "_inpainted.png",
"replaced_suffix": "_replaced.png",
"replace": False,
},
"processed_deform": {
"links": None,
"offsets": None
}
}
type=str,
default="FashionVideo_Preprocess",
help="the renamed model.")
parser.add_argument("--Preprocess.Cropper.src_crop_factor",
type=float,
default=0,
help="directly resize on iPER.")
parser.add_argument("--ref_path",
type=str,
default="",
help="set this empty when preprocessing training dataset.")
args = parser.parse_args()
args.cfg_path = os.path.join("./assets", "configs", "deploy.toml")
FashionVideo_root_dir = mkdir(args.output_dir)
FashionVideo_video_dir = mkdir(os.path.join(FashionVideo_root_dir, "videos"))
FashionVideo_train_url_txt = os.path.join(FashionVideo_root_dir,
"fashion_train.txt")
FashionVideo_test_url_txt = os.path.join(FashionVideo_root_dir,
"fashion_test.txt")
TRAIN_list_txt = os.path.join(FashionVideo_root_dir, "train.txt")
TEST_list_txt = os.path.join(FashionVideo_root_dir, "val.txt")
TRAIN_URL = "https://vision.cs.ubc.ca/datasets/fashion/resources/fashion_dataset/fashion_train.txt"
TEST_URL = "https://vision.cs.ubc.ca/datasets/fashion/resources/fashion_dataset/fashion_test.txt"
def raise_error(msg):
instruction_url = "https://vision.cs.ubc.ca/datasets/fashion/resources/fashion_dataset"
print(
type=str,
default="iPER_Preprocess",
help="the renamed model.")
parser.add_argument("--Preprocess.Cropper.src_crop_factor",
type=float,
default=0,
help="directly resize on iPER.")
parser.add_argument("--ref_path",
type=str,
default="",
help="set this empty when preprocessing training dataset.")
args = parser.parse_args()
args.cfg_path = os.path.join("./assets", "configs", "deploy.toml")
iPER_root_dir = mkdir(args.output_dir)
iPER_images_dir = mkdir(os.path.join(iPER_root_dir, "images_HD"))
iPER_images_splits_dir = mkdir(os.path.join(iPER_root_dir, "splits"))
iPER_images_merged_tar_gz = os.path.join(iPER_root_dir, "images_HD.tar.gz")
iPER_smpls_dir = os.path.join(iPER_root_dir, "smpls")
iPER_train_txt = os.path.join(iPER_root_dir, "train.txt")
iPER_val_txt = os.path.join(iPER_root_dir, "val.txt")
iPER_images_HD_split_txt = os.path.join(iPER_root_dir, "images_HD_splits.txt")
DOWNLOAD_URL = "http://download.impersonator.org:20086/"
iPER_url = "http://download.impersonator.org:20086/datasets/iPER"
iPER_images_HD_url = os.path.join(iPER_url, "images_HD")
iPER_images_HD_split_txt_url = os.path.join(iPER_url, "images_HD_splits.txt")
iPER_train_txt_url = os.path.join(iPER_url, "train.txt")
iPER_val_txt_url = os.path.join(iPER_url, "val.txt")