fix fastrcnn eval failed

model_zoo/faster_rcnn/src/dataset.py

@@ -464,27 +464,23 @@ def create_fasterrcnn_dataset(mindrecord_file, batch_size=2, repeat_num=12, devi
                         num_parallel_workers=num_parallel_workers)
             ds = ds.map(input_columns=["image", "image_shape", "box", "label", "valid_num"],
                         operations=flipped_generation, num_parallel_workers=4)
-
-        # transpose_column from python to c
-        ds = ds.map(input_columns=["image"], operations=[hwc_to_chw, type_cast1])
-        ds = ds.map(input_columns=["image_shape"], operations=[type_cast1])
-        ds = ds.map(input_columns=["box"], operations=[type_cast1])
-        ds = ds.map(input_columns=["label"], operations=[type_cast2])
-        ds = ds.map(input_columns=["valid_num"], operations=[type_cast3])
-        ds = ds.batch(batch_size, drop_remainder=True)
-        ds = ds.repeat(repeat_num)
     else:
         ds = ds.map(input_columns=["image", "annotation"],
                     output_columns=["image", "image_shape", "box", "label", "valid_num"],
                     columns_order=["image", "image_shape", "box", "label", "valid_num"],
                     operations=compose_map_func,
                     num_parallel_workers=num_parallel_workers)
-        # transpose_column from python to c
-        ds = ds.map(input_columns=["image"], operations=[hwc_to_chw, type_cast1])
-        ds = ds.map(input_columns=["image_shape"], operations=[type_cast1])
-        ds = ds.map(input_columns=["box"], operations=[type_cast1])
-        ds = ds.map(input_columns=["label"], operations=[type_cast2])
-        ds = ds.map(input_columns=["valid_num"], operations=[type_cast3])
-        ds = ds.batch(batch_size, drop_remainder=True)
-        ds = ds.repeat(repeat_num)
+
+        ds = ds.map(input_columns=["image"], operations=[normalize_op, type_cast0],
+                    num_parallel_workers=num_parallel_workers)
+
+    # transpose_column from python to c
+    ds = ds.map(input_columns=["image"], operations=[hwc_to_chw, type_cast1])
+    ds = ds.map(input_columns=["image_shape"], operations=[type_cast1])
+    ds = ds.map(input_columns=["box"], operations=[type_cast1])
+    ds = ds.map(input_columns=["label"], operations=[type_cast2])
+    ds = ds.map(input_columns=["valid_num"], operations=[type_cast3])
+    ds = ds.batch(batch_size, drop_remainder=True)
+    ds = ds.repeat(repeat_num)
+
     return ds