add layout

Author: horcham

configs/cls/mobilenetv3/cls_mv3.yaml

@@ -146,7 +146,7 @@ eval:
 predict:
   backend: MindSpore
   deive_target: Ascend
-  device_id: 0
+  device_id: 1
   max_device_memory: 8GB
   amp_level: O0
   mode: 0

configs/layout/yolov8/yolov8n.yaml

@@ -151,3 +151,42 @@ eval:
     drop_remainder: False
     max_rowsize: 12
     num_workers: 8
+
+predict:
+  backend: MindSpore
+  deive_target: Ascend
+  device_id: 3
+  max_device_memory: 8GB
+  amp_level: O0
+  mode: 0
+  ckpt_load_path: /root/.mindspore/models/dbnet_resnet50-c3a4aa24.ckpt
+  dataset_sink_mode: False
+  dataset:
+    type: PublayNetDataset
+    dataset_path: publaynet/val.txt
+    annotations_path: *annotations_path
+    img_size: 800
+    transform_pipeline:
+      - func_name: letterbox
+        scaleup: False
+      - func_name: label_norm
+        xyxy2xywh_: True
+      - func_name: label_pad
+        padding_size: 160
+        padding_value: -1
+      - func_name: image_norm
+        scale: 255.
+      - func_name: image_transpose
+        bgr2rgb: True
+        hwc2chw: True
+    batch_size: &refine_batch_size 13
+    stride: 64
+    output_columns: ['image', 'labels', 'image_ids', 'hw_ori', 'hw_scale', 'pad']
+    net_input_column_index: [ 0 ]  # input indices for network forward func in output_columns
+    meta_data_column_index: [ 2, 3, 4, 5 ]  # input indices marked as label
+  loader:
+    shuffle: False
+    batch_size: *refine_batch_size
+    drop_remainder: False
+    max_rowsize: 12
+    num_workers: 8

configs/rec/crnn/crnn_resnet34.yaml

@@ -152,7 +152,7 @@ eval:
 predict:
   backend: MindSpore
   deive_target: Ascend
-  device_id: 0
+  device_id: 2
   max_device_memory: 8GB
   amp_level: O3
   mode: 0

mindocr/postprocess/det_db_postprocess.py

@@ -222,8 +222,8 @@ def __init__(
 
     def __call__(
         self,
-        pred: Union[ms.Tensor, Tuple[ms.Tensor], np.ndarray],
-        shape_list: Union[np.ndarray, ms.Tensor] = None,
+        pred: Union[Tensor, Tuple[Tensor], np.ndarray],
+        shape_list: Union[np.ndarray, Tensor] = None,
         **kwargs,
     ) -> dict:
         if isinstance(shape_list, Tensor):