[to #42322933] add license header

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10231619

modelscope/metrics/image_instance_segmentation_metric.py

@@ -1,3 +1,5 @@
+# Part of the implementation is borrowed and modified from MMDetection, publicly available at
+# https://github.com/open-mmlab/mmdetection/blob/master/mmdet/datasets/coco.py
 import os.path as osp
 import tempfile
 from collections import OrderedDict

modelscope/models/cv/image_instance_segmentation/backbones/swin_transformer.py

@@ -1,5 +1,5 @@
-# Modified from: https://github.com/microsoft/Swin-Transformer/blob/main/models/swin_transformer.py
-
+# The implementation is adopted from Swin Transformer, made publicly available under the MIT License at
+# https://github.com/microsoft/Swin-Transformer/blob/main/models/swin_transformer.py
 import numpy as np
 import torch
 import torch.nn as nn

modelscope/models/cv/image_instance_segmentation/cascade_mask_rcnn_swin.py

@@ -1,3 +1,5 @@
+# Part of the implementation is borrowed and modified from MMDetection, publicly available at
+# https://github.com/open-mmlab/mmdetection/blob/master/mmdet/models/detectors/two_stage.py
 import os
 from collections import OrderedDict
 

modelscope/models/cv/image_instance_segmentation/datasets/__init__.py

@@ -1 +1,2 @@
+# Copyright (c) Alibaba, Inc. and its affiliates.
 from .transforms import build_preprocess_transform

modelscope/models/cv/image_instance_segmentation/datasets/transforms.py

@@ -1,3 +1,4 @@
+# Copyright (c) Alibaba, Inc. and its affiliates.
 import os.path as osp
 
 import numpy as np
@@ -51,9 +52,9 @@ class LoadImageFromFile:
     """Load an image from file.
 
     Required keys are "img_prefix" and "img_info" (a dict that must contain the
-    key "filename"). Added or updated keys are "filename", "img", "img_shape",
-    "ori_shape" (same as `img_shape`), "pad_shape" (same as `img_shape`),
-    "scale_factor" (1.0) and "img_norm_cfg" (means=0 and stds=1).
+    key "filename", "ann_file", and "classes"). Added or updated keys are
+    "filename", "ori_filename", "img", "img_shape", "ori_shape" (same as `img_shape`),
+    "img_fields", "ann_file" (path to annotation file) and "classes".
 
     Args:
         to_float32 (bool): Whether to convert the loaded image to a float32
@@ -73,7 +74,7 @@ class LoadImageFromFile:
         """Call functions to load image and get image meta information.
 
         Args:
-            results (dict): Result dict from :obj:`ImageInstanceSegmentationDataset`.
+            results (dict): Result dict from :obj:`ImageInstanceSegmentationCocoDataset`.
 
         Returns:
             dict: The dict contains loaded image and meta information.

modelscope/models/cv/image_instance_segmentation/model.py

@@ -1,3 +1,4 @@
+# Copyright (c) Alibaba, Inc. and its affiliates.
 import os
 from typing import Any, Dict
 

modelscope/models/cv/image_instance_segmentation/postprocess_utils.py

@@ -1,3 +1,5 @@
+# Part of the implementation is borrowed and modified from MMDetection, publicly available at
+# https://github.com/open-mmlab/mmdetection/blob/master/mmdet/core/visualization/image.py
 import itertools
 
 import cv2

modelscope/msdatasets/task_datasets/image_instance_segmentation_coco_dataset.py

@@ -1,3 +1,5 @@
+# Part of the implementation is borrowed and modified from MMDetection, publicly available at
+# https://github.com/open-mmlab/mmdetection/blob/master/mmdet/datasets/coco.py
 import os.path as osp
 
 import numpy as np

modelscope/pipelines/cv/image_instance_segmentation_pipeline.py

@@ -1,3 +1,4 @@
+# Copyright (c) Alibaba, Inc. and its affiliates.
 import os
 from typing import Any, Dict, Optional, Union
 

modelscope/trainers/cv/image_instance_segmentation_trainer.py

@@ -1,3 +1,4 @@
+# Copyright (c) Alibaba, Inc. and its affiliates.
 from modelscope.metainfo import Trainers
 from modelscope.trainers.builder import TRAINERS
 from modelscope.trainers.trainer import EpochBasedTrainer