diff --git a/configs/rec/rec_benchmark_reader.yml b/configs/rec/rec_benchmark_reader.yml
index 44cc0567906f6ed29f8a868ea9a4b45814d9efb0..3d1e3e0b22ce04573c73f51cbef26133415b9aa3 100755
--- a/configs/rec/rec_benchmark_reader.yml
+++ b/configs/rec/rec_benchmark_reader.yml
@@ -10,4 +10,4 @@ EvalReader:
 TestReader:
   reader_function: ppocr.data.rec.dataset_traversal,LMDBReader
   lmdb_sets_dir: ./train_data/data_lmdb_release/evaluation/
-  infer_img: ./infer_img
\ No newline at end of file
+  infer_img: ./infer_img
diff --git a/ppocr/data/rec/dataset_traversal.py b/ppocr/data/rec/dataset_traversal.py
index c45273e00566f75809c1c23bf47ba3c8b96613e5..357a89fbe53689177b34ef95f03fb532a9bae9d0 100755
--- a/ppocr/data/rec/dataset_traversal.py
+++ b/ppocr/data/rec/dataset_traversal.py
@@ -42,9 +42,11 @@ class LMDBReader(object):
         self.mode = params['mode']
         if params['mode'] == 'train':
             self.batch_size = params['train_batch_size_per_card']
-        else:
+        elif params['mode'] == "eval":
             self.batch_size = params['test_batch_size_per_card']
-
+        elif params['mode'] == "test":
+            self.batch_size = 1
+            self.infer_img = params["infer_img"]
     def load_hierarchical_lmdb_dataset(self):
         lmdb_sets = {}
         dataset_idx = 0
@@ -97,34 +99,42 @@ class LMDBReader(object):
             process_id = 0
 
         def sample_iter_reader():
-            lmdb_sets = self.load_hierarchical_lmdb_dataset()
-            if process_id == 0:
-                self.print_lmdb_sets_info(lmdb_sets)
-            cur_index_sets = [1 + process_id] * len(lmdb_sets)
-            while True:
-                finish_read_num = 0
-                for dataset_idx in range(len(lmdb_sets)):
-                    cur_index = cur_index_sets[dataset_idx]
-                    if cur_index > lmdb_sets[dataset_idx]['num_samples']:
-                        finish_read_num += 1
-                    else:
-                        sample_info = self.get_lmdb_sample_info(
-                            lmdb_sets[dataset_idx]['txn'], cur_index)
-                        cur_index_sets[dataset_idx] += self.num_workers
-                        if sample_info is None:
-                            continue
-                        img, label = sample_info
-                        outs = process_image(img, self.image_shape, label,
-                                             self.char_ops, self.loss_type,
-                                             self.max_text_length)
-                        if outs is None:
-                            continue
-                        yield outs
-
-                if finish_read_num == len(lmdb_sets):
-                    break
-            self.close_lmdb_dataset(lmdb_sets)
-
+            if self.mode == 'test':
+                image_file_list = get_image_file_list(self.infer_img)
+                for single_img in image_file_list:
+                    img = cv2.imread(single_img)
+                    if img.shape[-1]==1 or len(list(img.shape))==2:
+                        img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
+                    norm_img = process_image(img, self.image_shape)
+                    yield norm_img
+            else:
+                lmdb_sets = self.load_hierarchical_lmdb_dataset()
+                if process_id == 0:
+                    self.print_lmdb_sets_info(lmdb_sets)
+                cur_index_sets = [1 + process_id] * len(lmdb_sets)
+                while True:
+                    finish_read_num = 0
+                    for dataset_idx in range(len(lmdb_sets)):
+                        cur_index = cur_index_sets[dataset_idx]
+                        if cur_index > lmdb_sets[dataset_idx]['num_samples']:
+                            finish_read_num += 1
+                        else:
+                            sample_info = self.get_lmdb_sample_info(
+                                lmdb_sets[dataset_idx]['txn'], cur_index)
+                            cur_index_sets[dataset_idx] += self.num_workers
+                            if sample_info is None:
+                                continue
+                            img, label = sample_info
+                            outs = process_image(img, self.image_shape, label,
+                                                 self.char_ops, self.loss_type,
+                                                 self.max_text_length)
+                            if outs is None:
+                                continue
+                            yield outs
+
+                    if finish_read_num == len(lmdb_sets):
+                        break
+                self.close_lmdb_dataset(lmdb_sets)
         def batch_iter_reader():
             batch_outs = []
             for outs in sample_iter_reader():
@@ -135,7 +145,9 @@ class LMDBReader(object):
             if len(batch_outs) != 0:
                 yield batch_outs
 
-        return batch_iter_reader
+        if self.mode != 'test':
+            return batch_iter_reader
+        return sample_iter_reader
 
 
 class SimpleReader(object):