fix: tensorflow methods + numpy array

demo.py

@@ -65,7 +65,7 @@ def demo():
 		opt.batch_size = 1
 		opt.pretrain_weights = args.pretrain_weights
 		FaceReconstructor = Face3D()
-		images = tf.placeholder(name = 'input_imgs', shape = [opt.batch_size,224,224,3], dtype = tf.float32)
+		images = tf.compat.v1.placeholder(name = 'input_imgs', shape = [opt.batch_size,224,224,3], dtype = tf.float32)
 
 		if args.use_pb and os.path.isfile('network/FaceReconModel.pb'):
 			print('Using pre-trained .pb file.')
@@ -88,7 +88,7 @@ def demo():
 		tri = FaceReconstructor.facemodel.face_buf
 
 
-		with tf.Session() as sess:
+		with tf.compat.v1.Session() as sess:
 			if not args.use_pb :
 				restore_weights(sess,opt)
 

face_decoder.py

@@ -116,7 +116,7 @@ def Compute_norm(self,face_shape,facemodel):
 		v3 = tf.gather(shape,face_id[:,2], axis = 1)
 		e1 = v1 - v2
 		e2 = v2 - v3
-		face_norm = tf.cross(e1,e2)
+		face_norm = tf.compat.v1.cross(e1,e2)
 
 		face_norm = tf.nn.l2_normalize(face_norm, dim = 2) # normalized face_norm first
 		face_norm = tf.concat([face_norm,tf.zeros([tf.shape(face_shape)[0],1,3])], axis = 1)

options.py

@@ -27,7 +27,7 @@ def __init__(self,model_name=None,is_train=True):
 		self.val_summary_path = os.path.join(self.summary_dir, 'val')
 		#---------------------------------------------------------------------------------------
 		# visible gpu settings
-		self.config = tf.ConfigProto()
+		self.config = tf.compat.v1.ConfigProto()
 		self.config.gpu_options.visible_device_list = '0'
 		self.use_pb = True
 		#---------------------------------------------------------------------------------------
@@ -49,7 +49,7 @@ def __init__(self,model_name=None,is_train=True):
 		self.boundaries = [100000]
 		lr = [1e-4,2e-5]
 		self.global_step = tf.Variable(0,name='global_step',trainable = False)
-		self.lr = tf.train.piecewise_constant(self.global_step,self.boundaries,lr)
+		self.lr = tf.compat.v1.train.piecewise_constant(self.global_step,self.boundaries,lr)
 		self.augment = True
 		self.train_maxiter = 200000
 		self.train_summary_iter = 50

preprocess_img.py

@@ -71,7 +71,9 @@ def align_img(img,lm,lm3D):
 	# processing the image
 	img_new,lm_new = resize_n_crop_img(img,lm,t,s)
 	lm_new = np.stack([lm_new[:,0],223 - lm_new[:,1]], axis = 1)
-	trans_params = np.array([w0,h0,102.0/s,t[0],t[1]])
+	trans_params = np.array([w0,h0,102.0/s])
+	trans_params = np.append(trans_params, t[0])
+	trans_params = np.append(trans_params, t[1])
 
 	return img_new,lm_new,trans_params
 
@@ -148,4 +150,4 @@ def preprocessing():
 			lm_bin.tofile(os.path.join(save_path,'lm_bin',name+'.bin'))	
 
 if __name__ == '__main__':
-	preprocessing()
+	preprocessing()

utils.py

@@ -130,8 +130,8 @@ def save_obj(path,v,f,c):
 
 # load .pb file into tensorflow graph
 def load_graph(graph_filename):
-	with tf.gfile.GFile(graph_filename,'rb') as f:
-		graph_def = tf.GraphDef()
+	with tf.compat.v1.gfile.GFile(graph_filename,'rb') as f:
+		graph_def = tf.compat.v1.GraphDef()
 		graph_def.ParseFromString(f.read())
 
-	return graph_def
+	return graph_def