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[Fix] Fix RandomResize default setting

pull/1801/head
xiexinchen.vendor 2022-07-06 06:04:40 +00:00 committed by zhengmiao
parent d54f80c649
commit b852f2605a
24 changed files with 120 additions and 24 deletions
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6
configs/_base_/datasets/ade20k.py
View File

@ -5,7 +5,11 @@ crop_size = (512, 512)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', reduce_zero_label=True),
dict(type='RandomResize', scale=(2048, 512), ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=(2048, 512),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/_base_/datasets/ade20k_640x640.py
View File

@ -5,7 +5,11 @@ crop_size = (640, 640)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', reduce_zero_label=True),
dict(type='RandomResize', scale=(2560, 640), ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=(2560, 640),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/_base_/datasets/chase_db1.py
View File

@ -6,7 +6,11 @@ crop_size = (128, 128)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations'),
dict(type='RandomResize', scale=img_scale, ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=img_scale,
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/_base_/datasets/cityscapes.py
View File

@ -5,7 +5,11 @@ crop_size = (512, 1024)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations'),
dict(type='RandomResize', scale=(2048, 1024), ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=(2048, 1024),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/_base_/datasets/cityscapes_1024x1024.py
View File

@ -3,7 +3,11 @@ crop_size = (1024, 1024)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations'),
dict(type='RandomResize', scale=(2048, 1024), ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=(2048, 1024),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/_base_/datasets/cityscapes_768x768.py
View File

@ -3,7 +3,11 @@ crop_size = (768, 768)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations'),
dict(type='RandomResize', scale=(2049, 1025), ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=(2049, 1025),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/_base_/datasets/cityscapes_769x769.py
View File

@ -3,7 +3,11 @@ crop_size = (769, 769)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations'),
dict(type='RandomResize', scale=(2049, 1025), ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=(2049, 1025),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/_base_/datasets/cityscapes_832x832.py
View File

@ -3,7 +3,11 @@ crop_size = (832, 832)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations'),
dict(type='RandomResize', scale=(2048, 1024), ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=(2048, 1024),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/_base_/datasets/coco-stuff10k.py
View File

@ -5,7 +5,11 @@ crop_size = (512, 512)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', reduce_zero_label=True),
dict(type='RandomResize', scale=(2048, 512), ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=(2048, 512),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/_base_/datasets/coco-stuff164k.py
View File

@ -5,7 +5,11 @@ crop_size = (512, 512)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations'),
dict(type='RandomResize', scale=(2048, 512), ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=(2048, 512),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/_base_/datasets/drive.py
View File

@ -6,7 +6,11 @@ crop_size = (64, 64)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations'),
dict(type='RandomResize', scale=img_scale, ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=img_scale,
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/_base_/datasets/hrf.py
View File

@ -6,7 +6,11 @@ crop_size = (256, 256)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations'),
dict(type='RandomResize', scale=img_scale, ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=img_scale,
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/_base_/datasets/isaid.py
View File

@ -12,7 +12,11 @@ crop_size = (896, 896)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations'),
dict(type='RandomResize', scale=(896, 896), ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=(896, 896),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/_base_/datasets/loveda.py
View File

@ -5,7 +5,11 @@ crop_size = (512, 512)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', reduce_zero_label=True),
dict(type='RandomResize', scale=(2048, 512), ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=(2048, 512),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/_base_/datasets/pascal_context.py
View File

@ -8,7 +8,11 @@ crop_size = (480, 480)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations'),
dict(type='RandomResize', scale=img_scale, ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=img_scale,
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/_base_/datasets/pascal_context_59.py
View File

@ -8,7 +8,11 @@ crop_size = (480, 480)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', reduce_zero_label=True),
dict(type='RandomResize', scale=img_scale, ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=img_scale,
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/_base_/datasets/pascal_voc12.py
View File

@ -5,7 +5,11 @@ crop_size = (512, 512)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations'),
dict(type='RandomResize', scale=(2048, 512), ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=(2048, 512),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/_base_/datasets/pascal_voc12_aug.py
View File

@ -5,7 +5,11 @@ crop_size = (512, 512)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations'),
dict(type='RandomResize', scale=(2048, 512), ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=(2048, 512),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/_base_/datasets/potsdam.py
View File

@ -5,7 +5,11 @@ crop_size = (512, 512)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', reduce_zero_label=True),
dict(type='RandomResize', scale=(512, 512), ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=(512, 512),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/_base_/datasets/stare.py
View File

@ -6,7 +6,11 @@ crop_size = (128, 128)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations'),
dict(type='RandomResize', scale=img_scale, ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=img_scale,
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/_base_/datasets/vaihingen.py
View File

@ -5,7 +5,11 @@ crop_size = (512, 512)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', reduce_zero_label=True),
dict(type='RandomResize', scale=(512, 512), ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=(512, 512),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/cgnet/cgnet_680x680_60k_cityscapes.py
View File

@ -30,7 +30,11 @@ model = dict(data_preprocessor=data_preprocessor)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations'),
dict(type='RandomResize', scale=(2048, 1024), ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=(2048, 1024),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size),
dict(type='RandomFlip', prob=0.5),
dict(type='PackSegInputs')

6
configs/knet/knet_s3_upernet_swin-l_8x2_640x640_adamw_80k_ade20k.py
View File

@ -30,7 +30,11 @@ crop_size = (640, 640)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', reduce_zero_label=True),
dict(type='RandomResize', scale=(2048, 640), ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=(2048, 640),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),

6
configs/segformer/segformer_mit-b5_640x640_160k_ade20k.py
View File

@ -6,7 +6,11 @@ data_preprocessor = dict(size=crop_size)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', reduce_zero_label=True),
dict(type='RandomResize', scale=(2048, 640), ratio_range=(0.5, 2.0)),
dict(
type='RandomResize',
scale=(2048, 640),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='RandomFlip', prob=0.5),
dict(type='PhotoMetricDistortion'),