Merge branch 'limengzhang/fix_testpipeline_loadannotation' into 'refactor_dev'

[Fix] Fix no LoadAnnotations in testpipeline

See merge request openmmlab-enterprise/openmmlab-ce/mmsegmentation!41

configs/_base_/datasets/ade20k.py

@@ -14,6 +14,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=(2048, 512), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations', reduce_zero_label=True),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(

configs/_base_/datasets/ade20k_640x640.py

@@ -14,6 +14,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=(2560, 640), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations', reduce_zero_label=True),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(

configs/_base_/datasets/chase_db1.py

@@ -15,6 +15,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=img_scale, keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations'),
     dict(type='PackSegInputs')
 ]
 

configs/_base_/datasets/cityscapes.py

@@ -14,6 +14,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=(2048, 1024), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations'),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(

configs/_base_/datasets/cityscapes_1024x1024.py

@@ -12,6 +12,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=(2048, 1024), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations'),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(dataset=dict(pipeline=train_pipeline))

configs/_base_/datasets/cityscapes_768x768.py

@@ -12,6 +12,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=(2049, 1025), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations'),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(dataset=dict(pipeline=train_pipeline))

configs/_base_/datasets/cityscapes_769x769.py

@@ -12,6 +12,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=(2049, 1025), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations'),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(dataset=dict(pipeline=train_pipeline))

configs/_base_/datasets/cityscapes_832x832.py

@@ -12,6 +12,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=(2048, 1024), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations'),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(dataset=dict(pipeline=train_pipeline))

configs/_base_/datasets/coco-stuff10k.py

@@ -14,6 +14,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=(2048, 512), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations', reduce_zero_label=True),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(

configs/_base_/datasets/coco-stuff164k.py

@@ -14,6 +14,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=(2048, 512), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations'),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(

configs/_base_/datasets/drive.py

@@ -15,6 +15,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=img_scale, keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations'),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(

configs/_base_/datasets/hrf.py

@@ -15,6 +15,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=img_scale, keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations'),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(

configs/_base_/datasets/isaid.py

@@ -21,6 +21,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=(896, 896), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations'),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(

configs/_base_/datasets/loveda.py

@@ -14,6 +14,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=(1024, 1024), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations', reduce_zero_label=True),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(

configs/_base_/datasets/pascal_context.py

@@ -17,6 +17,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=img_scale, keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations'),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(

configs/_base_/datasets/pascal_context_59.py

@@ -17,6 +17,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=img_scale, keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations', reduce_zero_label=True),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(

configs/_base_/datasets/pascal_voc12.py

@@ -14,6 +14,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=(2048, 512), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations'),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(

configs/_base_/datasets/potsdam.py

@@ -14,6 +14,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=(512, 512), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations', reduce_zero_label=True),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(

configs/_base_/datasets/stare.py

@@ -15,6 +15,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=img_scale, keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations'),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(

configs/_base_/datasets/vaihingen.py

@@ -14,6 +14,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=(512, 512), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations', reduce_zero_label=True),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(

configs/beit/upernet_beit-base_640x640_160k_ade20k_ms.py

@@ -7,6 +7,9 @@ test_pipeline = [
     # img_ratios is [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
     # original image scale is (2560, 640)
     dict(type='Resize', scale=(2560, 640), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations', reduce_zero_label=True),
     dict(type='PackSegInputs'),
 ]
 val_dataloader = dict(batch_size=1, dataset=dict(pipeline=test_pipeline))

configs/beit/upernet_beit-large_fp16_640x640_160k_ade20k_ms.py

@@ -7,6 +7,9 @@ test_pipeline = [
     # img_ratios is [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
     # original image scale is (2560, 640)
     dict(type='Resize', scale=(2560, 640), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations', reduce_zero_label=True),
     dict(type='PackSegInputs'),
 ]
 val_dataloader = dict(dataset=dict(pipeline=test_pipeline))

configs/cgnet/cgnet_680x680_60k_cityscapes.py

@@ -38,6 +38,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=(2048, 1024), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations'),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(

configs/knet/knet_s3_upernet_swin-l_8x2_640x640_adamw_80k_ade20k.py

@@ -32,6 +32,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=(2048, 640), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations', reduce_zero_label=True),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(dataset=dict(pipeline=train_pipeline))

configs/mae/upernet_mae-base_fp16_512x512_160k_ade20k_ms.py

@@ -7,6 +7,9 @@ test_pipeline = [
     # img_ratios is [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
     # original image scale is (2048, 512)
     dict(type='Resize', scale=(2048, 512), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations', reduce_zero_label=True),
     dict(type='PackSegInputs')
 ]
 val_dataloader = dict(batch_size=1, dataset=dict(pipeline=test_pipeline))

configs/pspnet/pspnet_r50-d8_512x1024_40k_dark.py

@@ -9,6 +9,9 @@ model = dict(preprocess_cfg=preprocess_cfg)
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=(1920, 1080), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations'),
     dict(type='PackSegInputs')
 ]
 test_dataloader = dict(

configs/pspnet/pspnet_r50-d8_512x1024_40k_night_driving.py

@@ -10,6 +10,9 @@ model = dict(preprocess_cfg=preprocess_cfg)
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=(1920, 1080), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations'),
     dict(type='PackSegInputs')
 ]
 test_dataloader = dict(

configs/pspnet/pspnet_r50-d8_512x1024_80k_dark.py

@@ -10,6 +10,9 @@ model = dict(preprocess_cfg=preprocess_cfg)
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=(1920, 1080), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations'),
     dict(type='PackSegInputs')
 ]
 test_dataloader = dict(

configs/pspnet/pspnet_r50-d8_512x1024_80k_night_driving.py

@@ -10,6 +10,9 @@ model = dict(preprocess_cfg=preprocess_cfg)
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=(1920, 1080), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations'),
     dict(type='PackSegInputs')
 ]
 test_dataloader = dict(

configs/segformer/segformer_mit-b5_640x640_160k_ade20k.py

@@ -15,6 +15,9 @@ train_pipeline = [
 test_pipeline = [
     dict(type='LoadImageFromFile'),
     dict(type='Resize', scale=(2048, 640), keep_ratio=True),
+    # add loading annotation after ``Resize`` because ground truth
+    # does not need to do resize data transform
+    dict(type='LoadAnnotations', reduce_zero_label=True),
     dict(type='PackSegInputs')
 ]
 train_dataloader = dict(dataset=dict(pipeline=train_pipeline))

tests/test_config.py

@@ -92,6 +92,8 @@ def test_config_data_pipeline():
         to_float32 = load_img_pipeline.get('to_float32', False)
         config_mod.train_pipeline.pop(0)
         config_mod.test_pipeline.pop(0)
+        # remove loading annotation in test pipeline
+        config_mod.test_pipeline.pop(1)
 
         train_pipeline = Compose(config_mod.train_pipeline)
         test_pipeline = Compose(config_mod.test_pipeline)