fix infer (#2707)

PaddleCV/PaddleGAN/README.md

@@ -237,7 +237,7 @@ STGAN的网络结构[9]
 
 **Q:** 为什么STGAN和ATTGAN中变男性得到的预测结果是变女性呢？  
 **A:** 这是由于预测时标签的设置，目标标签是基于原本的标签进行改变，比如原本图片是男生，预测代码对标签进行转变的时候会自动变成相对立的标签，即女
-性，所以得到的结果是女生。如果想要原本是男生，转变之后还是男生，可以参考模型库中预测代码的StarGAN的标签设置。
+性，所以得到的结果是女生。如果想要原本是男生，转变之后还是男生，保持要转变的标签不变即可。
 
 
 ## 参考论文

PaddleCV/PaddleGAN/infer.py

@@ -122,6 +122,8 @@ def infer(args):
     if not os.path.exists(args.output):
         os.makedirs(args.output)
 
+    attr_names = args.selected_attrs.split(',')
+
     if args.model_net == 'AttGAN' or args.model_net == 'STGAN':
         test_reader = celeba_reader_creator(
             image_dir=args.dataset_dir,
@@ -133,7 +135,6 @@ def infer(args):
             args, shuffle=False, return_name=True)
         for data in zip(reader_test()):
             real_img, label_org, name = data[0]
-            attr_names = args.selected_attrs.split(',')
             print("read {}".format(name))
             label_trg = copy.deepcopy(label_org)
             tensor_img = fluid.LoDTensor()
@@ -189,10 +190,11 @@ def infer(args):
             real_img_temp = np.squeeze(real_img).transpose([0, 2, 3, 1])
             images = [real_img_temp]
             for i in range(args.c_dim):
-                label_trg = np.zeros(
-                    [len(label_org), args.c_dim]).astype("float32")
+                label_trg_tmp = copy.deepcopy(label_org)
                 for j in range(len(label_org)):
-                    label_trg[j][i] = 1
+                    label_trg_tmp[j][i] = 1.0 - label_trg_tmp[j][i]
+                    label_trg = check_attribute_conflict(
+                        label_trg_tmp, attr_names[i], attr_names)
                 tensor_label_trg = fluid.LoDTensor()
                 tensor_label_trg.set(label_trg, place)
                 out = exe.run(

PaddleCV/PaddleGAN/util/utility.py

@@ -104,6 +104,7 @@ def save_test_image(epoch,
     elif cfg.model_net == "StarGAN":
         for data in zip(A_test_reader()):
             real_img, label_org, name = data[0]
+            attr_names = cfg.selected_attrs.split(',')
             tensor_img = fluid.LoDTensor()
             tensor_label_org = fluid.LoDTensor()
             tensor_img.set(real_img, place)
@@ -111,8 +112,10 @@ def save_test_image(epoch,
             real_img_temp = np.squeeze(real_img).transpose([1, 2, 0])
             images = [real_img_temp]
             for i in range(cfg.c_dim):
-                label_trg = np.zeros([1, cfg.c_dim]).astype("float32")
-                label_trg[0][i] = 1
+                label_trg_tmp = copy.deepcopy(label_org)
+                label_trg_tmp[0][i] = 1.0 - label_trg_tmp[j][i]
+                label_trg = check_attribute_conflict(
+                    label_trg_tmp, attr_names[i], attr_names)
                 tensor_label_trg = fluid.LoDTensor()
                 tensor_label_trg.set(label_trg, place)
                 fake_temp, rec_temp = exe.run(