From c829f05471190341ef65a92c3bf000d5c26e2f62 Mon Sep 17 00:00:00 2001
From: Demetris Marnerides <dmarnerides@gmail.com>
Date: Fri, 26 Jul 2019 08:24:00 +0100
Subject: [PATCH] Added Registry use for validation datasets (distributed)
(#1058)
* Added Registry use for validation datasets (distributed)
* Allowing for default_args for build_dataset
* Using build_dataset instead of build_from_cfg
---
mmdet/apis/train.py | 4 ++--
mmdet/core/evaluation/eval_hooks.py | 5 ++---
mmdet/datasets/builder.py | 13 +++++++------
3 files changed, 11 insertions(+), 11 deletions(-)
diff --git a/mmdet/apis/train.py b/mmdet/apis/train.py
index 60d6c7d..0ebbb9e 100644
--- a/mmdet/apis/train.py
+++ b/mmdet/apis/train.py
@@ -11,7 +11,7 @@ from mmdet import datasets
from mmdet.core import (DistOptimizerHook, DistEvalmAPHook,
CocoDistEvalRecallHook, CocoDistEvalmAPHook,
Fp16OptimizerHook)
-from mmdet.datasets import build_dataloader
+from mmdet.datasets import build_dataloader, DATASETS
from mmdet.models import RPN
from .env import get_root_logger
@@ -174,7 +174,7 @@ def _dist_train(model, dataset, cfg, validate=False):
runner.register_hook(
CocoDistEvalRecallHook(val_dataset_cfg, **eval_cfg))
else:
- dataset_type = getattr(datasets, val_dataset_cfg.type)
+ dataset_type = DATASETS.get(val_dataset_cfg.type)
if issubclass(dataset_type, datasets.CocoDataset):
runner.register_hook(
CocoDistEvalmAPHook(val_dataset_cfg, **eval_cfg))
diff --git a/mmdet/core/evaluation/eval_hooks.py b/mmdet/core/evaluation/eval_hooks.py
index 99bd2d8..1786d93 100644
--- a/mmdet/core/evaluation/eval_hooks.py
+++ b/mmdet/core/evaluation/eval_hooks.py
@@ -5,7 +5,7 @@ import mmcv
import numpy as np
import torch
import torch.distributed as dist
-from mmcv.runner import Hook, obj_from_dict
+from mmcv.runner import Hook
from mmcv.parallel import scatter, collate
from pycocotools.cocoeval import COCOeval
from torch.utils.data import Dataset
@@ -21,8 +21,7 @@ class DistEvalHook(Hook):
if isinstance(dataset, Dataset):
self.dataset = dataset
elif isinstance(dataset, dict):
- self.dataset = obj_from_dict(dataset, datasets,
- {'test_mode': True})
+ self.dataset = datasets.build_dataset(dataset, {'test_mode': True})
else:
raise TypeError(
'dataset must be a Dataset object or a dict, not {}'.format(
diff --git a/mmdet/datasets/builder.py b/mmdet/datasets/builder.py
index 6b1ffba..3d4e2ca 100644
--- a/mmdet/datasets/builder.py
+++ b/mmdet/datasets/builder.py
@@ -5,7 +5,7 @@ from .dataset_wrappers import ConcatDataset, RepeatDataset
from .registry import DATASETS
-def _concat_dataset(cfg):
+def _concat_dataset(cfg, default_args=None):
ann_files = cfg['ann_file']
img_prefixes = cfg.get('img_prefix', None)
seg_prefixes = cfg.get('seg_prefixes', None)
@@ -22,17 +22,18 @@ def _concat_dataset(cfg):
data_cfg['seg_prefix'] = seg_prefixes[i]
if isinstance(proposal_files, (list, tuple)):
data_cfg['proposal_file'] = proposal_files[i]
- datasets.append(build_dataset(data_cfg))
+ datasets.append(build_dataset(data_cfg, default_args))
return ConcatDataset(datasets)
-def build_dataset(cfg):
+def build_dataset(cfg, default_args=None):
if cfg['type'] == 'RepeatDataset':
- dataset = RepeatDataset(build_dataset(cfg['dataset']), cfg['times'])
+ dataset = RepeatDataset(build_dataset(cfg['dataset'], default_args),
+ cfg['times'])
elif isinstance(cfg['ann_file'], (list, tuple)):
- dataset = _concat_dataset(cfg)
+ dataset = _concat_dataset(cfg, default_args)
else:
- dataset = build_from_cfg(cfg, DATASETS)
+ dataset = build_from_cfg(cfg, DATASETS, default_args)
return dataset
--
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