--refactor=support build

projects/CAT-Seg/cat_seg/__init__.py

@@ -0,0 +1,2 @@
+from .models import *  # noqa: F401,F403
+from .utils import *  # noqa: F401,F403

projects/CAT-Seg/mmseg/models/clip_ovseg.py → projects/CAT-Seg/cat_seg/models/clip_ovseg.py

@@ -9,8 +9,10 @@
 from mmengine.model import BaseModule
 
 from mmseg.registry import MODELS
-from mmseg.utils import ConfigType, clip_templates
+from mmseg.utils import ConfigType
 from ..utils import clip_wrapper
+from ..utils.clip_templates import (IMAGENET_TEMPLATES,
+                                    IMAGENET_TEMPLATES_SELECT)
 
 
 @MODELS.register_module()
@@ -88,9 +90,9 @@ def __init__(
         # prepare clip templates
         self.prompt_ensemble_type = prompt_ensemble_type
         if self.prompt_ensemble_type == 'imagenet_select':
-            prompt_templates = clip_templates.IMAGENET_TEMPLATES_SELECT
+            prompt_templates = IMAGENET_TEMPLATES_SELECT
         elif self.prompt_ensemble_type == 'imagenet':
-            prompt_templates = clip_templates.IMAGENET_TEMPLATES
+            prompt_templates = IMAGENET_TEMPLATES
         elif self.prompt_ensemble_type == 'single':
             prompt_templates = [
                 'A photo of a {} in the scene',

projects/CAT-Seg/cat_seg/utils/__init__.py

@@ -0,0 +1,10 @@
+# Copyright (c) OpenMMLab. All rights reserved.
+from .clip_templates import (IMAGENET_TEMPLATES, IMAGENET_TEMPLATES_SELECT,
+                             IMAGENET_TEMPLATES_SELECT_CLIP, ViLD_templates)
+from .self_attention_block import FullAttention, LinearAttention
+
+__all__ = [
+    'FullAttention', 'LinearAttention', 'IMAGENET_TEMPLATES',
+    'IMAGENET_TEMPLATES_SELECT', 'IMAGENET_TEMPLATES_SELECT_CLIP',
+    'ViLD_templates'
+]

projects/CAT-Seg/configs/_base_/default_runtime.py

@@ -0,0 +1,15 @@
+default_scope = 'mmseg'
+env_cfg = dict(
+    cudnn_benchmark=True,
+    mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0),
+    dist_cfg=dict(backend='nccl'),
+)
+vis_backends = [dict(type='LocalVisBackend')]
+visualizer = dict(
+    type='SegLocalVisualizer', vis_backends=vis_backends, name='visualizer')
+log_processor = dict(by_epoch=False)
+log_level = 'INFO'
+load_from = None
+resume = False
+
+tta_model = dict(type='SegTTAModel')

projects/CAT-Seg/configs/_base_/schedules/schedule_160k.py

@@ -0,0 +1,25 @@
+# optimizer
+optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005)
+optim_wrapper = dict(type='OptimWrapper', optimizer=optimizer, clip_grad=None)
+# learning policy
+param_scheduler = [
+    dict(
+        type='PolyLR',
+        eta_min=1e-4,
+        power=0.9,
+        begin=0,
+        end=160000,
+        by_epoch=False)
+]
+# training schedule for 160k
+train_cfg = dict(
+    type='IterBasedTrainLoop', max_iters=160000, val_interval=16000)
+val_cfg = dict(type='ValLoop')
+test_cfg = dict(type='TestLoop')
+default_hooks = dict(
+    timer=dict(type='IterTimerHook'),
+    logger=dict(type='LoggerHook', interval=50, log_metric_by_epoch=False),
+    param_scheduler=dict(type='ParamSchedulerHook'),
+    checkpoint=dict(type='CheckpointHook', by_epoch=False, interval=16000),
+    sampler_seed=dict(type='DistSamplerSeedHook'),
+    visualization=dict(type='SegVisualizationHook'))

projects/CAT-Seg/configs/_base_/schedules/schedule_20k.py

@@ -0,0 +1,24 @@
+# optimizer
+optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005)
+optim_wrapper = dict(type='OptimWrapper', optimizer=optimizer, clip_grad=None)
+# learning policy
+param_scheduler = [
+    dict(
+        type='PolyLR',
+        eta_min=1e-4,
+        power=0.9,
+        begin=0,
+        end=20000,
+        by_epoch=False)
+]
+# training schedule for 20k
+train_cfg = dict(type='IterBasedTrainLoop', max_iters=20000, val_interval=2000)
+val_cfg = dict(type='ValLoop')
+test_cfg = dict(type='TestLoop')
+default_hooks = dict(
+    timer=dict(type='IterTimerHook'),
+    logger=dict(type='LoggerHook', interval=50, log_metric_by_epoch=False),
+    param_scheduler=dict(type='ParamSchedulerHook'),
+    checkpoint=dict(type='CheckpointHook', by_epoch=False, interval=2000),
+    sampler_seed=dict(type='DistSamplerSeedHook'),
+    visualization=dict(type='SegVisualizationHook'))

projects/CAT-Seg/configs/_base_/schedules/schedule_240k.py

@@ -0,0 +1,25 @@
+# optimizer
+optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005)
+optim_wrapper = dict(type='OptimWrapper', optimizer=optimizer, clip_grad=None)
+# learning policy
+param_scheduler = [
+    dict(
+        type='PolyLR',
+        eta_min=1e-4,
+        power=0.9,
+        begin=0,
+        end=240000,
+        by_epoch=False)
+]
+# training schedule for 240k
+train_cfg = dict(
+    type='IterBasedTrainLoop', max_iters=240000, val_interval=24000)
+val_cfg = dict(type='ValLoop')
+test_cfg = dict(type='TestLoop')
+default_hooks = dict(
+    timer=dict(type='IterTimerHook'),
+    logger=dict(type='LoggerHook', interval=50, log_metric_by_epoch=False),
+    param_scheduler=dict(type='ParamSchedulerHook'),
+    checkpoint=dict(type='CheckpointHook', by_epoch=False, interval=24000),
+    sampler_seed=dict(type='DistSamplerSeedHook'),
+    visualization=dict(type='SegVisualizationHook'))

projects/CAT-Seg/configs/_base_/schedules/schedule_320k.py

@@ -0,0 +1,25 @@
+# optimizer
+optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005)
+optim_wrapper = dict(type='OptimWrapper', optimizer=optimizer, clip_grad=None)
+# learning policy
+param_scheduler = [
+    dict(
+        type='PolyLR',
+        eta_min=1e-4,
+        power=0.9,
+        begin=0,
+        end=320000,
+        by_epoch=False)
+]
+# training schedule for 320k
+train_cfg = dict(
+    type='IterBasedTrainLoop', max_iters=320000, val_interval=32000)
+val_cfg = dict(type='ValLoop')
+test_cfg = dict(type='TestLoop')
+default_hooks = dict(
+    timer=dict(type='IterTimerHook'),
+    logger=dict(type='LoggerHook', interval=50, log_metric_by_epoch=False),
+    param_scheduler=dict(type='ParamSchedulerHook'),
+    checkpoint=dict(type='CheckpointHook', by_epoch=False, interval=32000),
+    sampler_seed=dict(type='DistSamplerSeedHook'),
+    visualization=dict(type='SegVisualizationHook'))

projects/CAT-Seg/configs/_base_/schedules/schedule_40k.py

@@ -0,0 +1,24 @@
+# optimizer
+optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005)
+optim_wrapper = dict(type='OptimWrapper', optimizer=optimizer, clip_grad=None)
+# learning policy
+param_scheduler = [
+    dict(
+        type='PolyLR',
+        eta_min=1e-4,
+        power=0.9,
+        begin=0,
+        end=40000,
+        by_epoch=False)
+]
+# training schedule for 40k
+train_cfg = dict(type='IterBasedTrainLoop', max_iters=40000, val_interval=4000)
+val_cfg = dict(type='ValLoop')
+test_cfg = dict(type='TestLoop')
+default_hooks = dict(
+    timer=dict(type='IterTimerHook'),
+    logger=dict(type='LoggerHook', interval=50, log_metric_by_epoch=False),
+    param_scheduler=dict(type='ParamSchedulerHook'),
+    checkpoint=dict(type='CheckpointHook', by_epoch=False, interval=4000),
+    sampler_seed=dict(type='DistSamplerSeedHook'),
+    visualization=dict(type='SegVisualizationHook'))

projects/CAT-Seg/configs/_base_/schedules/schedule_80k.py

@@ -0,0 +1,24 @@
+# optimizer
+optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005)
+optim_wrapper = dict(type='OptimWrapper', optimizer=optimizer, clip_grad=None)
+# learning policy
+param_scheduler = [
+    dict(
+        type='PolyLR',
+        eta_min=1e-4,
+        power=0.9,
+        begin=0,
+        end=80000,
+        by_epoch=False)
+]
+# training schedule for 80k
+train_cfg = dict(type='IterBasedTrainLoop', max_iters=80000, val_interval=8000)
+val_cfg = dict(type='ValLoop')
+test_cfg = dict(type='TestLoop')
+default_hooks = dict(
+    timer=dict(type='IterTimerHook'),
+    logger=dict(type='LoggerHook', interval=50, log_metric_by_epoch=False),
+    param_scheduler=dict(type='ParamSchedulerHook'),
+    checkpoint=dict(type='CheckpointHook', by_epoch=False, interval=8000),
+    sampler_seed=dict(type='DistSamplerSeedHook'),
+    visualization=dict(type='SegVisualizationHook'))

projects/CAT-Seg/configs/cat_seg/catseg_vitb-r101_4xb2-warmcoslr2e-4-adamw-80k_coco-stuff164k-384x384.py

@@ -3,6 +3,8 @@
     '../_base_/datasets/coco-stuff164k_384x384.py'
 ]
 
+custom_imports = dict(imports=['cat_seg'])
+
 norm_cfg = dict(type='SyncBN', requires_grad=True)
 crop_size = (384, 384)
 data_preprocessor = dict(