add run

run.py

@@ -0,0 +1,46 @@
+import numpy as np
+import os
+from glob import glob
+import scipy.io as sio
+from skimage.io import imread, imsave
+from time import time
+
+from api import PRN
+from utils.write import write_obj
+
+# ---- init PRN
+os.environ['CUDA_VISIBLE_DEVICES'] = '0' # GPU number, -1 for CPU
+prn = PRN(is_dlib = True, is_opencv = False) 
+
+
+# ------------- load data
+image_folder = 'TestImages/'
+save_folder = 'TestImages/'
+if not os.path.exists(save_folder):
+    os.mkdir(save_folder)
+
+types = ('*.jpg', '*.png')
+image_path_list= []
+for files in types:
+    image_path_list.extend(glob(os.path.join(image_folder, files)))
+total_num = len(image_path_list)
+
+for i, image_path in enumerate(image_path_list):
+    # read image
+    image = imread(image_path)
+
+    # the core: regress position map    
+    pos = prn.process(image) # use dlib to detect face
+
+    # -- Basic Applications
+    # get landmarks
+    kpt = prn.get_landmarks(pos)
+    # 3D vertices
+    vertices = prn.get_vertices(pos)
+    # corresponding colors
+    colors = prn.get_colors(image, vertices)
+
+    # -- save
+    name = image_path.strip().split('/')[-1][:-4]
+    np.savetxt(os.path.join(save_folder, name + '.txt'), kpt) 
+    write_obj(os.path.join(save_folder, name + '.obj'), vertices, colors, prn.triangles) #save 3d face(can open with meshlab)