[Feature] File I/O migration and reconstruction

configs/_base_/datasets/dior.py

@@ -1,10 +1,10 @@
 # dataset settings
 dataset_type = 'DIORDataset'
 data_root = 'data/DIOR/'
-file_client_args = dict(backend='disk')
+backend_args = None
 
 train_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.LoadAnnotations', with_bbox=True, box_type='qbox'),
     dict(type='ConvertBoxType', box_type_mapping=dict(gt_bboxes='rbox')),
     dict(type='mmdet.Resize', scale=(800, 800), keep_ratio=True),
@@ -15,7 +15,7 @@
     dict(type='mmdet.PackDetInputs')
 ]
 val_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.Resize', scale=(800, 800), keep_ratio=True),
     # avoid bboxes being resized
     dict(type='mmdet.LoadAnnotations', with_bbox=True, box_type='qbox'),
@@ -26,7 +26,7 @@
                    'scale_factor'))
 ]
 test_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.Resize', scale=(800, 800), keep_ratio=True),
     dict(
         type='mmdet.PackDetInputs',
@@ -56,7 +56,8 @@
                 ann_file='ImageSets/Main/val.txt',
                 data_prefix=dict(img_path='JPEGImages-trainval'),
                 filter_cfg=dict(filter_empty_gt=True),
-                pipeline=train_pipeline)
+                pipeline=train_pipeline,
+                backend_args=backend_args)
         ]))
 val_dataloader = dict(
     batch_size=1,
@@ -70,7 +71,8 @@
         ann_file='ImageSets/Main/test.txt',
         data_prefix=dict(img_path='JPEGImages-test'),
         test_mode=True,
-        pipeline=val_pipeline))
+        pipeline=val_pipeline,
+        backend_args=backend_args))
 test_dataloader = val_dataloader
 
 val_evaluator = dict(type='DOTAMetric', metric='mAP')

configs/_base_/datasets/dota.py

@@ -1,10 +1,10 @@
 # dataset settings
 dataset_type = 'DOTADataset'
 data_root = 'data/split_ss_dota/'
-file_client_args = dict(backend='disk')
+backend_args = None
 
 train_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.LoadAnnotations', with_bbox=True, box_type='qbox'),
     dict(type='ConvertBoxType', box_type_mapping=dict(gt_bboxes='rbox')),
     dict(type='mmdet.Resize', scale=(1024, 1024), keep_ratio=True),
@@ -15,7 +15,7 @@
     dict(type='mmdet.PackDetInputs')
 ]
 val_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.Resize', scale=(1024, 1024), keep_ratio=True),
     # avoid bboxes being resized
     dict(type='mmdet.LoadAnnotations', with_bbox=True, box_type='qbox'),
@@ -26,7 +26,7 @@
                    'scale_factor'))
 ]
 test_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.Resize', scale=(1024, 1024), keep_ratio=True),
     dict(
         type='mmdet.PackDetInputs',

configs/_base_/datasets/dota_coco.py

@@ -1,10 +1,10 @@
 # dataset settings
 dataset_type = 'mmdet.CocoDataset'
 data_root = 'data/split_ms_dota/'
-file_client_args = dict(backend='disk')
+backend_args = None
 
 train_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(
         type='mmdet.LoadAnnotations',
         with_bbox=True,
@@ -19,7 +19,7 @@
     dict(type='mmdet.PackDetInputs')
 ]
 val_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.Resize', scale=(1024, 1024), keep_ratio=True),
     # avoid bboxes being resized
     dict(
@@ -34,7 +34,7 @@
                    'scale_factor', 'instances'))
 ]
 test_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.Resize', scale=(1024, 1024), keep_ratio=True),
     dict(
         type='mmdet.PackDetInputs',
@@ -61,7 +61,8 @@
         ann_file='train/train.json',
         data_prefix=dict(img='train/images/'),
         filter_cfg=dict(filter_empty_gt=True),
-        pipeline=train_pipeline))
+        pipeline=train_pipeline,
+        backend_args=backend_args))
 val_dataloader = dict(
     batch_size=1,
     num_workers=2,
@@ -75,10 +76,15 @@
         ann_file='val/val.json',
         data_prefix=dict(img='val/images/'),
         test_mode=True,
-        pipeline=val_pipeline))
+        pipeline=val_pipeline,
+        backend_args=backend_args))
 test_dataloader = val_dataloader
 
-val_evaluator = dict(type='RotatedCocoMetric', metric='bbox', classwise=True)
+val_evaluator = dict(
+    type='RotatedCocoMetric',
+    metric='bbox',
+    classwise=True,
+    backend_args=backend_args)
 
 test_evaluator = val_evaluator
 

configs/_base_/datasets/dota_ms.py

@@ -1,10 +1,10 @@
 # dataset settings
 dataset_type = 'DOTADataset'
 data_root = 'data/split_ms_dota/'
-file_client_args = dict(backend='disk')
+backend_args = None
 
 train_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.LoadAnnotations', with_bbox=True, box_type='qbox'),
     dict(type='ConvertBoxType', box_type_mapping=dict(gt_bboxes='rbox')),
     dict(type='mmdet.Resize', scale=(1024, 1024), keep_ratio=True),
@@ -20,7 +20,7 @@
     dict(type='mmdet.PackDetInputs')
 ]
 val_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.Resize', scale=(1024, 1024), keep_ratio=True),
     # avoid bboxes being resized
     dict(type='mmdet.LoadAnnotations', with_bbox=True, box_type='qbox'),
@@ -31,7 +31,7 @@
                    'scale_factor'))
 ]
 test_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.Resize', scale=(1024, 1024), keep_ratio=True),
     dict(
         type='mmdet.PackDetInputs',

configs/_base_/datasets/dota_qbox.py

@@ -1,10 +1,10 @@
 # dataset settings
 dataset_type = 'DOTADataset'
 data_root = 'data/split_ss_dota/'
-file_client_args = dict(backend='disk')
+backend_args = None
 
 train_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.LoadAnnotations', with_bbox=True, box_type='qbox'),
     dict(type='mmdet.Resize', scale=(1024, 1024), keep_ratio=True),
     dict(
@@ -14,7 +14,7 @@
     dict(type='mmdet.PackDetInputs')
 ]
 val_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.Resize', scale=(1024, 1024), keep_ratio=True),
     # avoid bboxes being resized
     dict(type='mmdet.LoadAnnotations', with_bbox=True, box_type='qbox'),
@@ -24,7 +24,7 @@
                    'scale_factor'))
 ]
 test_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.Resize', scale=(1024, 1024), keep_ratio=True),
     dict(
         type='mmdet.PackDetInputs',

configs/_base_/datasets/dotav15.py

@@ -1,10 +1,10 @@
 # dataset settings
 dataset_type = 'DOTAv15Dataset'
 data_root = 'data/split_ss_dota1_5/'
-file_client_args = dict(backend='disk')
+backend_args = None
 
 train_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.LoadAnnotations', with_bbox=True, box_type='qbox'),
     dict(type='ConvertBoxType', box_type_mapping=dict(gt_bboxes='rbox')),
     dict(type='mmdet.Resize', scale=(1024, 1024), keep_ratio=True),
@@ -15,7 +15,7 @@
     dict(type='mmdet.PackDetInputs')
 ]
 val_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.Resize', scale=(1024, 1024), keep_ratio=True),
     # avoid bboxes being resized
     dict(type='mmdet.LoadAnnotations', with_bbox=True, box_type='qbox'),
@@ -26,7 +26,7 @@
                    'scale_factor'))
 ]
 test_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.Resize', scale=(1024, 1024), keep_ratio=True),
     dict(
         type='mmdet.PackDetInputs',

configs/_base_/datasets/dotav2.py

@@ -1,10 +1,10 @@
 # dataset settings
 dataset_type = 'DOTAv2Dataset'
 data_root = 'data/split_ss_dota2_0/'
-file_client_args = dict(backend='disk')
+backend_args = None
 
 train_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.LoadAnnotations', with_bbox=True, box_type='qbox'),
     dict(type='ConvertBoxType', box_type_mapping=dict(gt_bboxes='rbox')),
     dict(type='mmdet.Resize', scale=(1024, 1024), keep_ratio=True),
@@ -15,7 +15,7 @@
     dict(type='mmdet.PackDetInputs')
 ]
 val_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.Resize', scale=(1024, 1024), keep_ratio=True),
     # avoid bboxes being resized
     dict(type='mmdet.LoadAnnotations', with_bbox=True, box_type='qbox'),
@@ -26,7 +26,7 @@
                    'scale_factor'))
 ]
 test_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.Resize', scale=(1024, 1024), keep_ratio=True),
     dict(
         type='mmdet.PackDetInputs',

configs/_base_/datasets/hrsc.py

@@ -1,10 +1,10 @@
 # dataset settings
 dataset_type = 'HRSCDataset'
 data_root = 'data/hrsc/'
-file_client_args = dict(backend='disk')
+backend_args = None
 
 train_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.LoadAnnotations', with_bbox=True, box_type='qbox'),
     dict(type='ConvertBoxType', box_type_mapping=dict(gt_bboxes='rbox')),
     dict(type='mmdet.Resize', scale=(800, 512), keep_ratio=True),
@@ -15,7 +15,7 @@
     dict(type='mmdet.PackDetInputs')
 ]
 val_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.Resize', scale=(800, 512), keep_ratio=True),
     # avoid bboxes being resized
     dict(type='mmdet.LoadAnnotations', with_bbox=True, box_type='qbox'),
@@ -26,7 +26,7 @@
                    'scale_factor'))
 ]
 test_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.Resize', scale=(800, 512), keep_ratio=True),
     dict(
         type='mmdet.PackDetInputs',
@@ -45,7 +45,8 @@
         ann_file='ImageSets/trainval.txt',
         data_prefix=dict(sub_data_root='FullDataSet/'),
         filter_cfg=dict(filter_empty_gt=True),
-        pipeline=train_pipeline))
+        pipeline=train_pipeline,
+        backend_args=backend_args))
 val_dataloader = dict(
     batch_size=1,
     num_workers=2,
@@ -58,7 +59,8 @@
         ann_file='ImageSets/test.txt',
         data_prefix=dict(sub_data_root='FullDataSet/'),
         test_mode=True,
-        pipeline=val_pipeline))
+        pipeline=val_pipeline,
+        backend_args=backend_args))
 test_dataloader = val_dataloader
 
 val_evaluator = dict(type='DOTAMetric', metric='mAP')

configs/_base_/datasets/hrsid.py

@@ -1,10 +1,10 @@
 # dataset settings
 dataset_type = 'mmdet.CocoDataset'
 data_root = 'data/HRSID_JPG/'
-file_client_args = dict(backend='disk')
+backend_args = None
 
 train_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(
         type='mmdet.LoadAnnotations',
         with_bbox=True,
@@ -20,7 +20,7 @@
     dict(type='mmdet.PackDetInputs')
 ]
 val_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.Resize', scale=(800, 800), keep_ratio=True),
     # avoid bboxes being resized
     dict(
@@ -35,7 +35,7 @@
                    'scale_factor', 'instances'))
 ]
 test_pipeline = [
-    dict(type='mmdet.LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='mmdet.LoadImageFromFile', backend_args=backend_args),
     dict(type='mmdet.Resize', scale=(800, 800), keep_ratio=True),
     dict(
         type='mmdet.PackDetInputs',
@@ -58,7 +58,8 @@
         ann_file='annotations/train2017.json',
         data_prefix=dict(img='JPEGImages/'),
         filter_cfg=dict(filter_empty_gt=True),
-        pipeline=train_pipeline))
+        pipeline=train_pipeline,
+        backend_args=backend_args))
 val_dataloader = dict(
     batch_size=1,
     num_workers=2,
@@ -72,7 +73,8 @@
         ann_file='annotations/test2017.json',
         data_prefix=dict(img='JPEGImages/'),
         test_mode=True,
-        pipeline=val_pipeline))
+        pipeline=val_pipeline,
+        backend_args=backend_args))
 test_dataloader = val_dataloader
 
 val_evaluator = dict(type='RotatedCocoMetric', metric='bbox')