Fix typo, refine code

.gitignore

@@ -20,4 +20,6 @@ models/shape_predictor_68_face_landmarks.dat
 .DS_Store
 
 demo_obama/
+todo.md
 
+utils/__pycacje__/

benchmark.py

@@ -15,7 +15,7 @@
 from benchmark_aflw import calc_nme as calc_nme_alfw
 from benchmark_aflw import ana as ana_aflw
 
-from ddfa_utils import ToTensorGjz, NormalizeGjz, DDFATestDataset, reconstruct_vertex
+from utils.ddfa import ToTensorGjz, NormalizeGjz, DDFATestDataset, reconstruct_vertex
 import argparse
 
 

benchmark_aflw.py

@@ -7,7 +7,7 @@
 import sys
 from glob import glob
 from math import sqrt
-from io_utils import _load
+from utils.io import _load
 
 d = 'test.configs'
 yaw_list = _load(osp.join(d, 'AFLW_GT_crop_yaws.npy'))

benchmark_aflw2000.py

@@ -4,7 +4,7 @@
 import os.path as osp
 import numpy as np
 from math import sqrt
-from io_utils import _load
+from utils.io import _load
 
 d = 'test.configs'
 yaws_list = _load(osp.join(d, 'AFLW2000-3D.pose.npy'))

main.py

@@ -18,9 +18,9 @@
 import numpy as np
 import cv2
 import dlib
-from ddfa_utils import ToTensorGjz, NormalizeGjz, str2bool
+from utils.ddfa import ToTensorGjz, NormalizeGjz, str2bool
 import scipy.io as sio
-from inference_utils import get_suffix, calc_roi_box, crop_img, predict_68pts, dump_to_ply, dump_vertex, draw_landmarks, \
+from utils.inference import get_suffix, calc_roi_box, crop_img, predict_68pts, dump_to_ply, dump_vertex, draw_landmarks, \
     predict_dense
 import argparse
 import torch.backends.cudnn as cudnn

params.py

@@ -3,7 +3,7 @@
 
 import os.path as osp
 import numpy as np
-from io_utils import _load, _numpy_to_cuda, _numpy_to_tensor, _load_gpu
+from utils.io import _load, _numpy_to_cuda, _numpy_to_tensor, _load_gpu
 
 
 def make_abs_path(d):

readme.md

@@ -76,11 +76,11 @@ In addition, I strongly recommend using Python3.6+ instead of older version for
     ```
     If you can see these output log in terminal, you run it successfully.
     ```
-    Dump tp samples/test1_0.ply
-    Dump tp samples/test1_0.mat
+    Dump to samples/test1_0.ply
+    Dump to samples/test1_0.mat
     Save 68 3d landmarks to samples/test1_0.txt
-    Dump tp samples/test1_1.ply
-    Dump tp samples/test1_1.mat
+    Dump to samples/test1_1.ply
+    Dump to samples/test1_1.mat
     Save 68 3d landmarks to samples/test1_1.txt
     Save visualization result to samples/test1_3DDFA.jpg
     ```

train.py

@@ -15,9 +15,9 @@
 import mobilenet_v1
 import torch.backends.cudnn as cudnn
 
-from ddfa_utils import DDFADataset, ToTensorGjz, NormalizeGjz
-from ddfa_utils import str2bool, AverageMeter
-from io_utils import mkdir
+from utils.ddfa import DDFADataset, ToTensorGjz, NormalizeGjz
+from utils.ddfa import str2bool, AverageMeter
+from utils.io import mkdir
 from vdc_loss import VDCLoss
 from wpdc_loss import WPDCLoss
 

ddfa_utils.py → utils/ddfa.py

@@ -10,7 +10,7 @@
 import cv2
 import pickle
 import argparse
-from io_utils import _numpy_to_tensor, _load_cpu, _load_gpu
+from .io import _numpy_to_tensor, _load_cpu, _load_gpu
 from params import *
 
 

inference_utils.py → utils/inference.py

@@ -6,7 +6,7 @@
 from math import sqrt
 import scipy.io as sio
 import matplotlib.pyplot as plt
-from ddfa_utils import reconstruct_vertex
+from .ddfa import reconstruct_vertex
 
 
 def get_suffix(filename):
@@ -97,7 +97,7 @@ def dump_to_ply(vertex, tri, wfp):
 
 def dump_vertex(vertex, wfp):
     sio.savemat(wfp, {'vertex': vertex})
-    print('Dump tp {}'.format(wfp))
+    print('Dump to {}'.format(wfp))
 
 
 def _predict_vertices(param, roi_box, dense):

vdc_loss.py

@@ -3,7 +3,7 @@
 
 import torch
 import torch.nn as nn
-from io_utils import _load, _numpy_to_cuda, _numpy_to_tensor
+from utils.io import _load, _numpy_to_cuda, _numpy_to_tensor
 from params import *
 
 _to_tensor = _numpy_to_cuda  # gpu

visualize.py

@@ -2,14 +2,12 @@
 # coding: utf-8
 
 from benchmark import extract_param
-from ddfa_utils import reconstruct_vertex
-from io_utils import _dump, _load
+from utils.ddfa import reconstruct_vertex
+from utils.io import _dump, _load
 import os.path as osp
 from skimage import io
 import matplotlib.pyplot as plt
 from benchmark_aflw2000 import convert_to_ori
-from mpl_toolkits.mplot3d import Axes3D
-import cv2
 import scipy.io as sio
 
 

wpdc_loss.py

@@ -4,7 +4,7 @@
 import torch
 import torch.nn as nn
 from math import sqrt
-from io_utils import _load, _numpy_to_cuda, _numpy_to_tensor, _load_gpu
+from utils.io import _load, _numpy_to_cuda, _numpy_to_tensor, _load_gpu
 from params import *
 
 _to_tensor = _numpy_to_cuda  # gpu