From dce6ec4c850f17f8ef618454107944aa7c81e6b3 Mon Sep 17 00:00:00 2001 From: johnzja Date: Sun, 9 Aug 2020 21:37:03 +0800 Subject: [PATCH] Add different config files into configs/ --- .../fast_scnn_4x3_1000e_cityscapes.py | 5 +- .../fast_scnn_4x3_450k_lr0.08_cityscapes.py | 64 +++++++++++++++++++ ...nn_4x8_100k_lr0.045_power1.2_cityscapes.py | 64 +++++++++++++++++++ .../fast_scnn_4x8_100k_lr0.08_cityscapes.py | 64 +++++++++++++++++++ .../fast_scnn_4x8_100k_lr0.12_cityscapes.py | 64 +++++++++++++++++++ .../fastscnn/fast_scnn_4x8_80k_cityscapes.py | 6 +- .../fast_scnn_4x8_80k_lr0.045_cityscapes.py | 64 +++++++++++++++++++ .../fast_scnn_4x8_80k_lr0.08_cityscapes.py | 64 +++++++++++++++++++ .../fast_scnn_4x8_80k_lr0.12_cityscapes.py | 64 +++++++++++++++++++ 9 files changed, 454 insertions(+), 5 deletions(-) create mode 100644 configs/fastscnn/fast_scnn_4x3_450k_lr0.08_cityscapes.py create mode 100644 configs/fastscnn/fast_scnn_4x8_100k_lr0.045_power1.2_cityscapes.py create mode 100644 configs/fastscnn/fast_scnn_4x8_100k_lr0.08_cityscapes.py create mode 100644 configs/fastscnn/fast_scnn_4x8_100k_lr0.12_cityscapes.py create mode 100644 configs/fastscnn/fast_scnn_4x8_80k_lr0.045_cityscapes.py create mode 100644 configs/fastscnn/fast_scnn_4x8_80k_lr0.08_cityscapes.py create mode 100644 configs/fastscnn/fast_scnn_4x8_80k_lr0.12_cityscapes.py diff --git a/configs/fastscnn/fast_scnn_4x3_1000e_cityscapes.py b/configs/fastscnn/fast_scnn_4x3_1000e_cityscapes.py index 6e6010e73..7583cb6f2 100644 --- a/configs/fastscnn/fast_scnn_4x3_1000e_cityscapes.py +++ b/configs/fastscnn/fast_scnn_4x3_1000e_cityscapes.py @@ -54,8 +54,9 @@ lr_config = dict( by_epoch=False, ) # runtime settings -# total_epochs = 1000 -total_iters = 247000 +total_epochs = 247000 evaluation = dict(interval=1000, metric='mIoU') checkpoint_config = dict(interval=1000) +# log config: log by iter. +log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook', by_epoch=False)]) diff --git a/configs/fastscnn/fast_scnn_4x3_450k_lr0.08_cityscapes.py b/configs/fastscnn/fast_scnn_4x3_450k_lr0.08_cityscapes.py new file mode 100644 index 000000000..f562f0d76 --- /dev/null +++ b/configs/fastscnn/fast_scnn_4x3_450k_lr0.08_cityscapes.py @@ -0,0 +1,64 @@ +_base_ = [ + '../_base_/models/fast_scnn.py', '../_base_/datasets/cityscapes.py', + '../_base_/default_runtime.py' +] +crop_size = (512, 1024) +cudnn_benchmark = True +# model training and testing settings +train_cfg = dict() +test_cfg = dict(mode='whole') + +# Here: What is parameter 'with_seg'? +img_norm_cfg = dict( + mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) +train_pipeline = [ + dict(type='LoadImageFromFile', to_float32=True), + dict(type='LoadAnnotations'), # with_seg=True + dict(type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)), + dict(type='RandomFlip', flip_ratio=0.5), + dict(type='PhotoMetricDistortion'), + dict(type='Normalize', **img_norm_cfg), + dict(type='RandomCrop', crop_size=crop_size), + dict(type='DefaultFormatBundle'), + dict(type='Collect', keys=['img', 'gt_semantic_seg']), +] +test_pipeline = [ + dict(type='LoadImageFromFile'), + dict( + type='MultiScaleFlipAug', + img_scale=(2048, 1024), + # 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=3, + workers_per_gpu=3, + train=dict(pipeline=train_pipeline), + val=dict(pipeline=test_pipeline), + test=dict(pipeline=test_pipeline)) + +# optimizer +optimizer = dict(type='SGD', lr=0.08, momentum=0.9, weight_decay=4e-5) +optimizer_config = dict() +# learning policy +lr_config = dict( + policy='poly', + power=0.9, + by_epoch=False, +) +# runtime settings +# total_epochs = 1000 +total_iters = 450000 +evaluation = dict(interval=2000, metric='mIoU') +checkpoint_config = dict(interval=2000) + +# log config: log by iter. +log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook', by_epoch=False)]) + diff --git a/configs/fastscnn/fast_scnn_4x8_100k_lr0.045_power1.2_cityscapes.py b/configs/fastscnn/fast_scnn_4x8_100k_lr0.045_power1.2_cityscapes.py new file mode 100644 index 000000000..078fa94c5 --- /dev/null +++ b/configs/fastscnn/fast_scnn_4x8_100k_lr0.045_power1.2_cityscapes.py @@ -0,0 +1,64 @@ +_base_ = [ + '../_base_/models/fast_scnn.py', '../_base_/datasets/cityscapes.py', + '../_base_/default_runtime.py' +] +crop_size = (512, 1024) +cudnn_benchmark = True +# model training and testing settings +train_cfg = dict() +test_cfg = dict(mode='whole') + +# Here: What is parameter 'with_seg'? +img_norm_cfg = dict( + mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) +train_pipeline = [ + dict(type='LoadImageFromFile', to_float32=True), + dict(type='LoadAnnotations'), # with_seg=True + dict(type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)), + dict(type='RandomFlip', flip_ratio=0.5), + dict(type='PhotoMetricDistortion'), + dict(type='Normalize', **img_norm_cfg), + dict(type='RandomCrop', crop_size=crop_size), + dict(type='DefaultFormatBundle'), + dict(type='Collect', keys=['img', 'gt_semantic_seg']), +] +test_pipeline = [ + dict(type='LoadImageFromFile'), + dict( + type='MultiScaleFlipAug', + img_scale=(2048, 1024), + # 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=8, + workers_per_gpu=4, + train=dict(pipeline=train_pipeline), + val=dict(pipeline=test_pipeline), + test=dict(pipeline=test_pipeline)) + +# optimizer +optimizer = dict(type='SGD', lr=0.045, momentum=0.9, weight_decay=4e-5) +optimizer_config = dict() +# learning policy +lr_config = dict( + policy='poly', + power=1.2, + by_epoch=False, +) +# runtime settings +# total_epochs = 1000 +total_iters = 100000 +evaluation = dict(interval=2000, metric='mIoU') +checkpoint_config = dict(interval=2000) + +# log config: log by iter. +log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook', by_epoch=False)]) + diff --git a/configs/fastscnn/fast_scnn_4x8_100k_lr0.08_cityscapes.py b/configs/fastscnn/fast_scnn_4x8_100k_lr0.08_cityscapes.py new file mode 100644 index 000000000..10f56e093 --- /dev/null +++ b/configs/fastscnn/fast_scnn_4x8_100k_lr0.08_cityscapes.py @@ -0,0 +1,64 @@ +_base_ = [ + '../_base_/models/fast_scnn.py', '../_base_/datasets/cityscapes.py', + '../_base_/default_runtime.py' +] +crop_size = (512, 1024) +cudnn_benchmark = True +# model training and testing settings +train_cfg = dict() +test_cfg = dict(mode='whole') + +# Here: What is parameter 'with_seg'? +img_norm_cfg = dict( + mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) +train_pipeline = [ + dict(type='LoadImageFromFile', to_float32=True), + dict(type='LoadAnnotations'), # with_seg=True + dict(type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)), + dict(type='RandomFlip', flip_ratio=0.5), + dict(type='PhotoMetricDistortion'), + dict(type='Normalize', **img_norm_cfg), + dict(type='RandomCrop', crop_size=crop_size), + dict(type='DefaultFormatBundle'), + dict(type='Collect', keys=['img', 'gt_semantic_seg']), +] +test_pipeline = [ + dict(type='LoadImageFromFile'), + dict( + type='MultiScaleFlipAug', + img_scale=(2048, 1024), + # 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=8, + workers_per_gpu=4, + train=dict(pipeline=train_pipeline), + val=dict(pipeline=test_pipeline), + test=dict(pipeline=test_pipeline)) + +# optimizer +optimizer = dict(type='SGD', lr=0.08, momentum=0.9, weight_decay=4e-5) +optimizer_config = dict() +# learning policy +lr_config = dict( + policy='poly', + power=0.9, + by_epoch=False, +) +# runtime settings +# total_epochs = 1000 +total_iters = 100000 +evaluation = dict(interval=2000, metric='mIoU') +checkpoint_config = dict(interval=2000) + +# log config: log by iter. +log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook', by_epoch=False)]) + diff --git a/configs/fastscnn/fast_scnn_4x8_100k_lr0.12_cityscapes.py b/configs/fastscnn/fast_scnn_4x8_100k_lr0.12_cityscapes.py new file mode 100644 index 000000000..9ff49a9db --- /dev/null +++ b/configs/fastscnn/fast_scnn_4x8_100k_lr0.12_cityscapes.py @@ -0,0 +1,64 @@ +_base_ = [ + '../_base_/models/fast_scnn.py', '../_base_/datasets/cityscapes.py', + '../_base_/default_runtime.py' +] +crop_size = (512, 1024) +cudnn_benchmark = True +# model training and testing settings +train_cfg = dict() +test_cfg = dict(mode='whole') + +# Here: What is parameter 'with_seg'? +img_norm_cfg = dict( + mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) +train_pipeline = [ + dict(type='LoadImageFromFile', to_float32=True), + dict(type='LoadAnnotations'), # with_seg=True + dict(type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)), + dict(type='RandomFlip', flip_ratio=0.5), + dict(type='PhotoMetricDistortion'), + dict(type='Normalize', **img_norm_cfg), + dict(type='RandomCrop', crop_size=crop_size), + dict(type='DefaultFormatBundle'), + dict(type='Collect', keys=['img', 'gt_semantic_seg']), +] +test_pipeline = [ + dict(type='LoadImageFromFile'), + dict( + type='MultiScaleFlipAug', + img_scale=(2048, 1024), + # 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=8, + workers_per_gpu=4, + train=dict(pipeline=train_pipeline), + val=dict(pipeline=test_pipeline), + test=dict(pipeline=test_pipeline)) + +# optimizer +optimizer = dict(type='SGD', lr=0.12, momentum=0.9, weight_decay=4e-5) +optimizer_config = dict() +# learning policy +lr_config = dict( + policy='poly', + power=0.9, + by_epoch=False, +) +# runtime settings +# total_epochs = 1000 +total_iters = 100000 +evaluation = dict(interval=2000, metric='mIoU') +checkpoint_config = dict(interval=2000) + +# log config: log by iter. +log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook', by_epoch=False)]) + diff --git a/configs/fastscnn/fast_scnn_4x8_80k_cityscapes.py b/configs/fastscnn/fast_scnn_4x8_80k_cityscapes.py index 51d2d61eb..dd6ac7f15 100644 --- a/configs/fastscnn/fast_scnn_4x8_80k_cityscapes.py +++ b/configs/fastscnn/fast_scnn_4x8_80k_cityscapes.py @@ -55,7 +55,7 @@ lr_config = dict( ) # runtime settings # total_epochs = 1000 -total_iters = 80000 -evaluation = dict(interval=8000, metric='mIoU') -checkpoint_config = dict(interval=8000) +total_iters = 100000 +evaluation = dict(interval=2000, metric='mIoU') +checkpoint_config = dict(interval=2000) diff --git a/configs/fastscnn/fast_scnn_4x8_80k_lr0.045_cityscapes.py b/configs/fastscnn/fast_scnn_4x8_80k_lr0.045_cityscapes.py new file mode 100644 index 000000000..f6fd1729e --- /dev/null +++ b/configs/fastscnn/fast_scnn_4x8_80k_lr0.045_cityscapes.py @@ -0,0 +1,64 @@ +_base_ = [ + '../_base_/models/fast_scnn.py', '../_base_/datasets/cityscapes.py', + '../_base_/default_runtime.py' +] +crop_size = (512, 1024) +cudnn_benchmark = True +# model training and testing settings +train_cfg = dict() +test_cfg = dict(mode='whole') + +# Here: What is parameter 'with_seg'? +img_norm_cfg = dict( + mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) +train_pipeline = [ + dict(type='LoadImageFromFile', to_float32=True), + dict(type='LoadAnnotations'), # with_seg=True + dict(type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)), + dict(type='RandomFlip', flip_ratio=0.5), + dict(type='PhotoMetricDistortion'), + dict(type='Normalize', **img_norm_cfg), + dict(type='RandomCrop', crop_size=crop_size), + dict(type='DefaultFormatBundle'), + dict(type='Collect', keys=['img', 'gt_semantic_seg']), +] +test_pipeline = [ + dict(type='LoadImageFromFile'), + dict( + type='MultiScaleFlipAug', + img_scale=(2048, 1024), + # 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=8, + workers_per_gpu=4, + train=dict(pipeline=train_pipeline), + val=dict(pipeline=test_pipeline), + test=dict(pipeline=test_pipeline)) + +# optimizer +optimizer = dict(type='SGD', lr=0.045, momentum=0.9, weight_decay=4e-5) +optimizer_config = dict() +# learning policy +lr_config = dict( + policy='poly', + power=0.9, + by_epoch=False, +) +# runtime settings +# total_epochs = 1000 +total_iters = 100000 +evaluation = dict(interval=2000, metric='mIoU') +checkpoint_config = dict(interval=2000) + +# log config: log by iter. +log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook', by_epoch=False)]) + diff --git a/configs/fastscnn/fast_scnn_4x8_80k_lr0.08_cityscapes.py b/configs/fastscnn/fast_scnn_4x8_80k_lr0.08_cityscapes.py new file mode 100644 index 000000000..aec2ea0a2 --- /dev/null +++ b/configs/fastscnn/fast_scnn_4x8_80k_lr0.08_cityscapes.py @@ -0,0 +1,64 @@ +_base_ = [ + '../_base_/models/fast_scnn.py', '../_base_/datasets/cityscapes.py', + '../_base_/default_runtime.py' +] +crop_size = (512, 1024) +cudnn_benchmark = True +# model training and testing settings +train_cfg = dict() +test_cfg = dict(mode='whole') + +# Here: What is parameter 'with_seg'? +img_norm_cfg = dict( + mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) +train_pipeline = [ + dict(type='LoadImageFromFile', to_float32=True), + dict(type='LoadAnnotations'), # with_seg=True + dict(type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)), + dict(type='RandomFlip', flip_ratio=0.5), + dict(type='PhotoMetricDistortion'), + dict(type='Normalize', **img_norm_cfg), + dict(type='RandomCrop', crop_size=crop_size), + dict(type='DefaultFormatBundle'), + dict(type='Collect', keys=['img', 'gt_semantic_seg']), +] +test_pipeline = [ + dict(type='LoadImageFromFile'), + dict( + type='MultiScaleFlipAug', + img_scale=(2048, 1024), + # 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=8, + workers_per_gpu=4, + train=dict(pipeline=train_pipeline), + val=dict(pipeline=test_pipeline), + test=dict(pipeline=test_pipeline)) + +# optimizer +optimizer = dict(type='SGD', lr=0.08, momentum=0.9, weight_decay=4e-5) +optimizer_config = dict() +# learning policy +lr_config = dict( + policy='poly', + power=0.9, + by_epoch=False, +) +# runtime settings +# total_epochs = 1000 +total_iters = 80000 +evaluation = dict(interval=2000, metric='mIoU') +checkpoint_config = dict(interval=2000) + +# log config: log by iter. +log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook', by_epoch=False)]) + diff --git a/configs/fastscnn/fast_scnn_4x8_80k_lr0.12_cityscapes.py b/configs/fastscnn/fast_scnn_4x8_80k_lr0.12_cityscapes.py new file mode 100644 index 000000000..cf6075f12 --- /dev/null +++ b/configs/fastscnn/fast_scnn_4x8_80k_lr0.12_cityscapes.py @@ -0,0 +1,64 @@ +_base_ = [ + '../_base_/models/fast_scnn.py', '../_base_/datasets/cityscapes.py', + '../_base_/default_runtime.py' +] +crop_size = (512, 1024) +cudnn_benchmark = True +# model training and testing settings +train_cfg = dict() +test_cfg = dict(mode='whole') + +# Here: What is parameter 'with_seg'? +img_norm_cfg = dict( + mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) +train_pipeline = [ + dict(type='LoadImageFromFile', to_float32=True), + dict(type='LoadAnnotations'), # with_seg=True + dict(type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)), + dict(type='RandomFlip', flip_ratio=0.5), + dict(type='PhotoMetricDistortion'), + dict(type='Normalize', **img_norm_cfg), + dict(type='RandomCrop', crop_size=crop_size), + dict(type='DefaultFormatBundle'), + dict(type='Collect', keys=['img', 'gt_semantic_seg']), +] +test_pipeline = [ + dict(type='LoadImageFromFile'), + dict( + type='MultiScaleFlipAug', + img_scale=(2048, 1024), + # 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=8, + workers_per_gpu=4, + train=dict(pipeline=train_pipeline), + val=dict(pipeline=test_pipeline), + test=dict(pipeline=test_pipeline)) + +# optimizer +optimizer = dict(type='SGD', lr=0.12, momentum=0.9, weight_decay=4e-5) +optimizer_config = dict() +# learning policy +lr_config = dict( + policy='poly', + power=0.9, + by_epoch=False, +) +# runtime settings +# total_epochs = 1000 +total_iters = 80000 +evaluation = dict(interval=2000, metric='mIoU') +checkpoint_config = dict(interval=2000) + +# log config: log by iter. +log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook', by_epoch=False)]) +