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Add support for Pascal Context 59 classes (open-mmlab#459)
* Add support for Pascal Context 59 classes (open-mmlab#459) * Create PascalContextDataset59 class in mmseg/datasets/pascal_context.py; * Set reduce_zero_label=True for train_pipeline and PascalContextDataset59; * Add some configs for Pascal-Context 59 classes training and testing; * Try to solve the problem about "fence(IoU)=nan grass(IoU)=0"; * Continue(1): Try to solve the problem about "fence(IoU)=nan grass(IoU)=0"; * ignore files and folders named tempxxx; * Continue(2): Try to solve the problem about "fence(IoU)=nan grass(IoU)=0"; * Modify the calculation of IoU; * Modify the CLASSES order of PascalContextDataset; * Add "fcn", "deeplabv3", "deeplabv3+", "pspnet" config file for model training based on PascalContextDataset59; Add some ignore items in ".gitignore"; * fix the bug "test_cfg specified in both outer field and model field " of pspnet config file; * * Clean unnecessary codes; * Add weighs link, config link, log link and evaluation results about PascalContextDataset59 in README.md * Add command line argument: "-p | --port", this arg can change the transmit port when you transmit data to distributed machine. * * Remove rebundant config files; * Remove "-p|--port" command argument; Co-authored-by: Jiarui XU <xvjiarui0826@gmail.com>
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# dataset settings | ||
dataset_type = 'PascalContextDataset59' | ||
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', reduce_zero_label=True), | ||
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', prob=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='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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configs/deeplabv3/deeplabv3_r101-d8_480x480_40k_pascal_context_59.py
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_base_ = './deeplabv3_r50-d8_480x480_40k_pascal_context_59.py' | ||
model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) |
2 changes: 2 additions & 0 deletions
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configs/deeplabv3/deeplabv3_r101-d8_480x480_80k_pascal_context_59.py
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_base_ = './deeplabv3_r50-d8_480x480_80k_pascal_context_59.py' | ||
model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) |
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configs/deeplabv3/deeplabv3_r50-d8_480x480_40k_pascal_context_59.py
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_base_ = [ | ||
'../_base_/models/deeplabv3_r50-d8.py', | ||
'../_base_/datasets/pascal_context_59.py', '../_base_/default_runtime.py', | ||
'../_base_/schedules/schedule_40k.py' | ||
] | ||
model = dict( | ||
decode_head=dict(num_classes=59), | ||
auxiliary_head=dict(num_classes=59), | ||
test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320))) | ||
optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001) |
10 changes: 10 additions & 0 deletions
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configs/deeplabv3/deeplabv3_r50-d8_480x480_80k_pascal_context_59.py
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_base_ = [ | ||
'../_base_/models/deeplabv3_r50-d8.py', | ||
'../_base_/datasets/pascal_context_59.py', '../_base_/default_runtime.py', | ||
'../_base_/schedules/schedule_80k.py' | ||
] | ||
model = dict( | ||
decode_head=dict(num_classes=59), | ||
auxiliary_head=dict(num_classes=59), | ||
test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320))) | ||
optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001) |
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2 changes: 2 additions & 0 deletions
2
configs/deeplabv3plus/deeplabv3plus_r101-d8_480x480_40k_pascal_context_59.py
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_base_ = './deeplabv3plus_r50-d8_480x480_40k_pascal_context_59.py' | ||
model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) |
2 changes: 2 additions & 0 deletions
2
configs/deeplabv3plus/deeplabv3plus_r101-d8_480x480_80k_pascal_context_59.py
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_base_ = './deeplabv3plus_r50-d8_480x480_80k_pascal_context_59.py' | ||
model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) |
10 changes: 10 additions & 0 deletions
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configs/deeplabv3plus/deeplabv3plus_r50-d8_480x480_40k_pascal_context_59.py
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_base_ = [ | ||
'../_base_/models/deeplabv3plus_r50-d8.py', | ||
'../_base_/datasets/pascal_context_59.py', '../_base_/default_runtime.py', | ||
'../_base_/schedules/schedule_40k.py' | ||
] | ||
model = dict( | ||
decode_head=dict(num_classes=59), | ||
auxiliary_head=dict(num_classes=59), | ||
test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320))) | ||
optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001) |
10 changes: 10 additions & 0 deletions
10
configs/deeplabv3plus/deeplabv3plus_r50-d8_480x480_80k_pascal_context_59.py
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@@ -0,0 +1,10 @@ | ||
_base_ = [ | ||
'../_base_/models/deeplabv3plus_r50-d8.py', | ||
'../_base_/datasets/pascal_context_59.py', '../_base_/default_runtime.py', | ||
'../_base_/schedules/schedule_80k.py' | ||
] | ||
model = dict( | ||
decode_head=dict(num_classes=59), | ||
auxiliary_head=dict(num_classes=59), | ||
test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320))) | ||
optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001) |
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_base_ = './fcn_r50-d8_480x480_40k_pascal_context_59.py' | ||
model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) |
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_base_ = './fcn_r50-d8_480x480_80k_pascal_context_59.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_59.py', '../_base_/default_runtime.py', | ||
'../_base_/schedules/schedule_40k.py' | ||
] | ||
model = dict( | ||
decode_head=dict(num_classes=59), | ||
auxiliary_head=dict(num_classes=59), | ||
test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320))) | ||
optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001) |
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_base_ = [ | ||
'../_base_/models/fcn_r50-d8.py', | ||
'../_base_/datasets/pascal_context_59.py', '../_base_/default_runtime.py', | ||
'../_base_/schedules/schedule_80k.py' | ||
] | ||
model = dict( | ||
decode_head=dict(num_classes=59), | ||
auxiliary_head=dict(num_classes=59), | ||
test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320))) | ||
optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001) |
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