Add Pascal Context to mmsegmentation #133
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| # dataset settings | ||
| dataset_type = 'PascalContextDataset' | ||
| data_root = 'data/VOCdevkit/VOC2010/' | ||
| img_norm_cfg = dict( | ||
| mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) | ||
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| img_scale = (520, 520) | ||
| crop_size = (480, 480) | ||
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| train_pipeline = [ | ||
| dict(type='LoadImageFromFile'), | ||
| dict(type='LoadAnnotations'), | ||
| dict(type='Resize', img_scale=img_scale, ratio_range=(0.5, 2.0)), | ||
| dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75), | ||
| dict(type='RandomFlip', flip_ratio=0.5), | ||
| dict(type='PhotoMetricDistortion'), | ||
| dict(type='Normalize', **img_norm_cfg), | ||
| dict(type='Pad', size=crop_size, pad_val=0, seg_pad_val=255), | ||
| dict(type='DefaultFormatBundle'), | ||
| dict(type='Collect', keys=['img', 'gt_semantic_seg']), | ||
| ] | ||
| test_pipeline = [ | ||
| dict(type='LoadImageFromFile'), | ||
| dict( | ||
| type='MultiScaleFlipAug', | ||
| img_scale=img_scale, | ||
| #img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75], | ||
| flip=False, | ||
| transforms=[ | ||
| dict(type='Resize', keep_ratio=True), | ||
| # dict(type='Pad', size=crop_size, pad_val=(-123.675/58.395, -116.28/57.12, -103.53/57.375), seg_pad_val=255), | ||
| dict(type='RandomFlip'), | ||
| dict(type='Normalize', **img_norm_cfg), | ||
| dict(type='ImageToTensor', keys=['img']), | ||
| dict(type='Collect', keys=['img']), | ||
| ]) | ||
| ] | ||
| data = dict( | ||
| samples_per_gpu=4, | ||
| workers_per_gpu=4, | ||
| train=dict( | ||
| type=dataset_type, | ||
| data_root=data_root, | ||
| img_dir='JPEGImages', | ||
| ann_dir='SegmentationClassContext', | ||
| split='ImageSets/SegmentationContext/train.txt', | ||
| pipeline=train_pipeline), | ||
| val=dict( | ||
| type=dataset_type, | ||
| data_root=data_root, | ||
| img_dir='JPEGImages', | ||
| ann_dir='SegmentationClassContext', | ||
| split='ImageSets/SegmentationContext/val.txt', | ||
| pipeline=test_pipeline), | ||
| test=dict( | ||
| type=dataset_type, | ||
| data_root=data_root, | ||
| img_dir='JPEGImages', | ||
| ann_dir='SegmentationClassContext', | ||
| split='ImageSets/SegmentationContext/val.txt', | ||
| pipeline=test_pipeline)) |
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| # optimizer | ||
| optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001) | ||
| optimizer_config = dict() | ||
| # learning policy | ||
| lr_config = dict(policy='poly', power=0.9, min_lr=1e-4, by_epoch=False) | ||
| # runtime settings | ||
| total_iters = 40000 | ||
| checkpoint_config = dict(by_epoch=False, interval=4000) | ||
| evaluation = dict(interval=4000, metric='mIoU') | ||
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| # optimizer | ||
| optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001) | ||
| optimizer_config = dict() | ||
| # learning policy | ||
| lr_config = dict(policy='poly', power=0.9, min_lr=1e-4, by_epoch=False) | ||
|
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||
| # runtime settings | ||
| total_iters = 80000 | ||
| checkpoint_config = dict(by_epoch=False, interval=8000) | ||
| evaluation = dict(interval=8000, metric='mIoU') | ||
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| _base_ = './deeplabv3_r50-d8_480x480_40k_pascal_context.py' | ||
| model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) |
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| _base_ = './deeplabv3_r50-d8_480x480_80k_pascal_context.py' | ||
| model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) |
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| _base_ = [ | ||
| '../_base_/models/deeplabv3_r50-d8.py', | ||
| '../_base_/datasets/pascal_context.py', '../_base_/default_runtime.py', | ||
| '../_base_/schedules/schedule_40k_lr4e-3.py' | ||
| ] | ||
| model = dict( | ||
| decode_head=dict(num_classes=60), auxiliary_head=dict(num_classes=60)) | ||
| test_cfg = dict(mode='slide', crop_size=(480, 480), stride=(320, 320)) |
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| _base_ = [ | ||
| '../_base_/models/deeplabv3_r50-d8.py', | ||
| '../_base_/datasets/pascal_context.py', '../_base_/default_runtime.py', | ||
| '../_base_/schedules/schedule_80k_lr4e-3.py' | ||
| ] | ||
| model = dict( | ||
| decode_head=dict(num_classes=60), auxiliary_head=dict(num_classes=60)) | ||
| test_cfg = dict(mode='slide', crop_size=(480, 480), stride=(320, 320)) |
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| _base_ = './deeplabv3plus_r50-d8_480x480_40k_pascal_context.py' | ||
| model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) |
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| @@ -0,0 +1,2 @@ | ||
| _base_ = './deeplabv3plus_r50-d8_480x480_80k_pascal_context.py' | ||
| model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) |
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| _base_ = [ | ||
| '../_base_/models/deeplabv3plus_r50-d8.py', | ||
| '../_base_/datasets/pascal_context.py', '../_base_/default_runtime.py', | ||
| '../_base_/schedules/schedule_40k_lr4e-3.py' | ||
| ] | ||
| model = dict( | ||
| decode_head=dict(num_classes=60), auxiliary_head=dict(num_classes=60)) | ||
| test_cfg = dict(mode='slide', crop_size=(480, 480), stride=(320, 320)) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,8 @@ | ||
| _base_ = [ | ||
| '../_base_/models/deeplabv3plus_r50-d8.py', | ||
| '../_base_/datasets/pascal_context.py', '../_base_/default_runtime.py', | ||
| '../_base_/schedules/schedule_80k_lr4e-3.py' | ||
| ] | ||
| model = dict( | ||
| decode_head=dict(num_classes=60), auxiliary_head=dict(num_classes=60)) | ||
| test_cfg = dict(mode='slide', crop_size=(480, 480), stride=(320, 320)) |
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| _base_ = './fcn_r50-d8_480x480_40k_pascal_context.py' | ||
| model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) |
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|---|---|---|
| @@ -0,0 +1,2 @@ | ||
| _base_ = './fcn_r50-d8_480x480_80k_pascal_context.py' | ||
| model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) |
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| _base_ = [ | ||
| '../_base_/models/fcn_r50-d8.py', '../_base_/datasets/pascal_context.py', | ||
| '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k_lr4e-3.py' | ||
| ] | ||
| model = dict(decode_head=dict(num_classes=60)) | ||
| test_cfg = dict(mode='slide', crop_size=(480, 480), stride=(320, 320)) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,6 @@ | ||
| _base_ = [ | ||
| '../_base_/models/fcn_r50-d8.py', '../_base_/datasets/pascal_context.py', | ||
| '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k_lr4e-3.py' | ||
| ] | ||
| model = dict(decode_head=dict(num_classes=60)) | ||
| test_cfg = dict(mode='slide', crop_size=(480, 480), stride=(320, 320)) |
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| _base_ = [ | ||
| '../_base_/models/fcn_hr18.py', '../_base_/datasets/pascal_context.py', | ||
| '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k_lr4e-3.py' | ||
| ] | ||
| model = dict(decode_head=dict(num_classes=60)) | ||
| test_cfg = dict(mode='slide', crop_size=(480, 480), stride=(320, 320)) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,6 @@ | ||
| _base_ = [ | ||
| '../_base_/models/fcn_hr18.py', '../_base_/datasets/pascal_context.py', | ||
| '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k_lr4e-3.py' | ||
| ] | ||
| model = dict(decode_head=dict(num_classes=60)) | ||
| test_cfg = dict(mode='slide', crop_size=(480, 480), stride=(320, 320)) |
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| _base_ = './fcn_hr18_480x480_40k_pascal_context.py' | ||
| model = dict( | ||
| pretrained='open-mmlab://msra/hrnetv2_w18_small', | ||
| backbone=dict( | ||
| extra=dict( | ||
| stage1=dict(num_blocks=(2, )), | ||
| stage2=dict(num_blocks=(2, 2)), | ||
| stage3=dict(num_modules=3, num_blocks=(2, 2, 2)), | ||
| stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2))))) |
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,9 @@ | ||
| _base_ = './fcn_hr18_480x480_80k_pascal_context.py' | ||
| model = dict( | ||
| pretrained='open-mmlab://msra/hrnetv2_w18_small', | ||
| backbone=dict( | ||
| extra=dict( | ||
| stage1=dict(num_blocks=(2, )), | ||
| stage2=dict(num_blocks=(2, 2)), | ||
| stage3=dict(num_modules=3, num_blocks=(2, 2, 2)), | ||
| stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2))))) |
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| _base_ = './fcn_hr18_480x480_40k_pascal_context.py' | ||
| model = dict( | ||
| pretrained='open-mmlab://msra/hrnetv2_w48', | ||
| backbone=dict( | ||
| extra=dict( | ||
| stage2=dict(num_channels=(48, 96)), | ||
| stage3=dict(num_channels=(48, 96, 192)), | ||
| stage4=dict(num_channels=(48, 96, 192, 384)))), | ||
| decode_head=dict( | ||
| in_channels=[48, 96, 192, 384], channels=sum([48, 96, 192, 384]))) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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| _base_ = './fcn_hr18_480x480_80k_pascal_context.py' | ||
| model = dict( | ||
| pretrained='open-mmlab://msra/hrnetv2_w48', | ||
| backbone=dict( | ||
| extra=dict( | ||
| stage2=dict(num_channels=(48, 96)), | ||
| stage3=dict(num_channels=(48, 96, 192)), | ||
| stage4=dict(num_channels=(48, 96, 192, 384)))), | ||
| decode_head=dict( | ||
| in_channels=[48, 96, 192, 384], channels=sum([48, 96, 192, 384]))) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,2 @@ | ||
| _base_ = './pspnet_r50-d8_480x480_40k_pascal_context.py' | ||
| model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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| _base_ = './pspnet_r50-d8_480x480_80k_pascal_context.py' | ||
| model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) |
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We may delete this file and modify the corresponding lr directly.