from glob import glob import shutil import torch import os, sys, time from time import strftime from argparse import ArgumentParser from src.utils.preprocess import CropAndExtract from src.test_audio2coeff import Audio2Coeff from src.facerender.animate import AnimateFromCoeff from src.generate_batch import get_data from src.generate_facerender_batch import get_facerender_data from src.utils.init_path import init_path def main(args): # torch.backends.cudnn.enabled = False pic_path = args.source_image audio_path = args.driven_audio save_dir = os.path.join(args.result_dir, strftime("%Y_%m_%d_%H.%M.%S")) os.makedirs(save_dir, exist_ok=True) pose_style = args.pose_style device = args.device batch_size = args.batch_size input_yaw_list = args.input_yaw input_pitch_list = args.input_pitch input_roll_list = args.input_roll ref_eyeblink = args.ref_eyeblink ref_pose = args.ref_pose current_root_path = os.path.split(sys.argv[0])[0] sadtalker_paths = init_path( args.checkpoint_dir, os.path.join(current_root_path, "src/config"), args.size, args.old_version, args.preprocess ) # init model preprocess_model = CropAndExtract(sadtalker_paths, device) audio_to_coeff = Audio2Coeff(sadtalker_paths, device) animate_from_coeff = AnimateFromCoeff(sadtalker_paths, device) # crop image and extract 3dmm from image first_frame_dir = os.path.join(save_dir, "first_frame_dir") os.makedirs(first_frame_dir, exist_ok=True) print("3DMM Extraction for source image") first_coeff_path, crop_pic_path, crop_info = preprocess_model.generate( pic_path, first_frame_dir, args.preprocess, source_image_flag=True, pic_size=args.size ) if first_coeff_path is None: print("Can't get the coeffs of the input") return if ref_eyeblink is not None: ref_eyeblink_videoname = os.path.splitext(os.path.split(ref_eyeblink)[-1])[0] ref_eyeblink_frame_dir = os.path.join(save_dir, ref_eyeblink_videoname) os.makedirs(ref_eyeblink_frame_dir, exist_ok=True) print("3DMM Extraction for the reference video providing eye blinking") ref_eyeblink_coeff_path, _, _ = preprocess_model.generate( ref_eyeblink, ref_eyeblink_frame_dir, args.preprocess, source_image_flag=False ) else: ref_eyeblink_coeff_path = None if ref_pose is not None: if ref_pose == ref_eyeblink: ref_pose_coeff_path = ref_eyeblink_coeff_path else: ref_pose_videoname = os.path.splitext(os.path.split(ref_pose)[-1])[0] ref_pose_frame_dir = os.path.join(save_dir, ref_pose_videoname) os.makedirs(ref_pose_frame_dir, exist_ok=True) print("3DMM Extraction for the reference video providing pose") ref_pose_coeff_path, _, _ = preprocess_model.generate(ref_pose, ref_pose_frame_dir, args.preprocess, source_image_flag=False) else: ref_pose_coeff_path = None # audio2ceoff batch = get_data(first_coeff_path, audio_path, device, ref_eyeblink_coeff_path, still=args.still) coeff_path = audio_to_coeff.generate(batch, save_dir, pose_style, ref_pose_coeff_path) # 3dface render if args.face3dvis: from src.face3d.visualize import gen_composed_video gen_composed_video(args, device, first_coeff_path, coeff_path, audio_path, os.path.join(save_dir, "3dface.mp4")) # coeff2video data = get_facerender_data( coeff_path, crop_pic_path, first_coeff_path, audio_path, batch_size, input_yaw_list, input_pitch_list, input_roll_list, expression_scale=args.expression_scale, still_mode=args.still, preprocess=args.preprocess, size=args.size, ) result = animate_from_coeff.generate( data, save_dir, pic_path, crop_info, enhancer=args.enhancer, background_enhancer=args.background_enhancer, preprocess=args.preprocess, img_size=args.size, ) shutil.move(result, save_dir + ".mp4") print("The generated video is named:", save_dir + ".mp4") if not args.verbose: shutil.rmtree(save_dir) if __name__ == "__main__": parser = ArgumentParser() parser.add_argument("--driven_audio", default="./examples/driven_audio/bus_chinese.wav", help="path to driven audio") parser.add_argument("--source_image", default="./examples/source_image/full_body_1.png", help="path to source image") parser.add_argument("--ref_eyeblink", default=None, help="path to reference video providing eye blinking") parser.add_argument("--ref_pose", default=None, help="path to reference video providing pose") parser.add_argument("--checkpoint_dir", default="./checkpoints", help="path to checkpoints") parser.add_argument("--result_dir", default="./results", help="path to output results") parser.add_argument("--pose_style", type=int, default=0, help="input pose style from [0, 46)") parser.add_argument("--batch_size", type=int, default=2, help="batch size của facerender") parser.add_argument("--size", type=int, default=256, help="kích thước ảnh đầu vào") parser.add_argument("--expression_scale", type=float, default=1.0, help="tỉ lệ biểu cảm khuôn mặt") parser.add_argument("--input_yaw", nargs="+", type=int, default=None, help="yaw độ xoay đầu") parser.add_argument("--input_pitch", nargs="+", type=int, default=None, help="pitch độ xoay đầu") parser.add_argument("--input_roll", nargs="+", type=int, default=None, help="roll độ xoay đầu") parser.add_argument("--enhancer", type=str, default=None, help="face enhancer, [gfpgan, RestoreFormer]") parser.add_argument("--background_enhancer", type=str, default=None, help="nâng cao background, [realesrgan]") parser.add_argument("--cpu", dest="cpu", action="store_true", help="ép dùng CPU thay vì GPU") parser.add_argument("--face3dvis", action="store_true", help="xuất landmark & face 3D các bước") parser.add_argument("--still", action="store_true", help="giữ đầu tĩnh, chỉ miệng chuyển động") parser.add_argument( "--preprocess", default="crop", choices=["crop", "extcrop", "resize", "full", "extfull"], help="cách tiền xử lý ảnh" ) parser.add_argument("--verbose", action="store_true", help="lưu các ảnh trung gian debug") parser.add_argument("--old_version", action="store_true", help="dùng model .pth (version cũ)") # net structure and parameters parser.add_argument( "--net_recon", type=str, default="resnet50", choices=["resnet18", "resnet34", "resnet50"], help="backbone reconstruction (ít dùng)" ) parser.add_argument("--init_path", type=str, default=None, help="path init model (ít dùng)") parser.add_argument("--use_last_fc", action="store_true", help="zero-initialize last fc layer") parser.add_argument("--bfm_folder", type=str, default="./checkpoints/BFM_Fitting/", help="thư mục BFM") parser.add_argument("--bfm_model", type=str, default="BFM_model_front.mat", help="tên file model BFM") # default renderer parameters parser.add_argument("--focal", type=float, default=1015.0, help="tiêu cự camera ảo") parser.add_argument("--center", type=float, default=112.0, help="trung tâm camera") parser.add_argument("--camera_d", type=float, default=10.0, help="khoảng cách camera") parser.add_argument("--z_near", type=float, default=5.0, help="gần nhất") parser.add_argument("--z_far", type=float, default=15.0, help="xa nhất") args = parser.parse_args() # Chọn thiết bị if torch.cuda.is_available() and not args.cpu: args.device = "cuda" else: args.device = "cpu" main(args)