Add ade doc (#10504)

open-mmlab · Jun 14, 2023 · e858b60 · e858b60
1 parent 429c2a4
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diff --git a/configs/_base_/datasets/ade20k_instance.py b/configs/_base_/datasets/ade20k_instance.py
@@ -0,0 +1,53 @@
+# dataset settings
+dataset_type = 'ADE20KInstanceDataset'
+data_root = 'data/ADEChallengeData2016/'
+
+# Example to use different file client
+# Method 1: simply set the data root and let the file I/O module
+# automatically infer from prefix (not support LMDB and Memcache yet)
+
+# data_root = 's3://openmmlab/datasets/detection/ADEChallengeData2016/'
+
+# Method 2: Use `backend_args`, `file_client_args` in versions before 3.0.0rc6
+# backend_args = dict(
+#     backend='petrel',
+#     path_mapping=dict({
+#         './data/': 's3://openmmlab/datasets/detection/',
+#         'data/': 's3://openmmlab/datasets/detection/'
+#     }))
+backend_args = None
+
+test_pipeline = [
+    dict(type='LoadImageFromFile', backend_args=backend_args),
+    dict(type='Resize', scale=(2560, 640), keep_ratio=True),
+    # If you don't have a gt annotation, delete the pipeline
+    dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
+    dict(
+        type='PackDetInputs',
+        meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape',
+                   'scale_factor'))
+]
+
+val_dataloader = dict(
+    batch_size=1,
+    num_workers=2,
+    persistent_workers=True,
+    drop_last=False,
+    sampler=dict(type='DefaultSampler', shuffle=False),
+    dataset=dict(
+        type=dataset_type,
+        data_root=data_root,
+        ann_file='ade20k_instance_val.json',
+        data_prefix=dict(img='images/validation'),
+        test_mode=True,
+        pipeline=test_pipeline,
+        backend_args=backend_args))
+test_dataloader = val_dataloader
+
+val_evaluator = dict(
+    type='CocoMetric',
+    ann_file=data_root + 'ade20k_instance_val.json',
+    metric=['bbox', 'segm'],
+    format_only=False,
+    backend_args=backend_args)
+test_evaluator = val_evaluator
diff --git a/configs/_base_/datasets/ade20k_panoptic.py b/configs/_base_/datasets/ade20k_panoptic.py
@@ -4,15 +4,6 @@
 
 backend_args = None
 
-train_pipeline = [
-    dict(type='LoadImageFromFile', backend_args=backend_args),
-    dict(type='LoadPanopticAnnotations', backend_args=backend_args),
-    # TODO: the performance of `FixScaleResize` need to check.
-    dict(type='FixScaleResize', scale=(2560, 640), backend_args=backend_args),
-    dict(type='RandomCrop', crop_size=(640, 640), crop_type='absolute'),
-    dict(type='RandomFlip', prob=0.5),
-    dict(type='PackDetInputs')
-]
 test_pipeline = [
     dict(type='LoadImageFromFile', backend_args=backend_args),
     dict(type='Resize', scale=(640, 640), keep_ratio=True),
@@ -23,20 +14,6 @@
                    'scale_factor'))
 ]
 
-train_dataloader = dict(
-    batch_size=4,
-    num_workers=2,
-    persistent_workers=True,
-    sampler=dict(type='DefaultSampler', shuffle=True),
-    batch_sampler=dict(type='AspectRatioBatchSampler'),
-    dataset=dict(
-        type=dataset_type,
-        data_root=data_root,
-        ann_file='ade20k_panoptic_train.json',
-        data_prefix=dict(img='images/training/', seg='ade20k_panoptic_train/'),
-        filter_cfg=dict(filter_empty_gt=True, min_size=32),
-        pipeline=train_pipeline,
-        backend_args=backend_args))
 val_dataloader = dict(
     batch_size=1,
     num_workers=2,

diff --git a/configs/_base_/datasets/ade20k_semantic.py b/configs/_base_/datasets/ade20k_semantic.py
@@ -5,7 +5,7 @@
 # Method 1: simply set the data root and let the file I/O module
 # automatically infer from prefix (not support LMDB and Memcache yet)
 
-# data_root = 's3://openmmlab/datasets/detection/coco/'
+# data_root = 's3://openmmlab/datasets/detection/ADEChallengeData2016/'
 
 # Method 2: Use `backend_args`, `file_client_args` in versions before 3.0.0rc6
 # backend_args = dict(

diff --git a/configs/_base_/datasets/refcoco+.py b/configs/_base_/datasets/refcoco+.py
@@ -51,5 +51,5 @@
         text_mode='original',
         pipeline=test_pipeline))
 
-val_evaluator = dict(type='RefSegMetric', metrics=['cIoU', 'mIoU'])
+val_evaluator = dict(type='RefSegMetric', iou_metrics=['cIoU', 'mIoU'])
 test_evaluator = val_evaluator
diff --git a/configs/_base_/datasets/refcoco.py b/configs/_base_/datasets/refcoco.py
@@ -51,5 +51,5 @@
         text_mode='original',
         pipeline=test_pipeline))
 
-val_evaluator = dict(type='RefSegMetric', metrics=['cIoU', 'mIoU'])
+val_evaluator = dict(type='RefSegMetric', iou_metrics=['cIoU', 'mIoU'])
 test_evaluator = val_evaluator
diff --git a/configs/_base_/datasets/refcocog.py b/configs/_base_/datasets/refcocog.py
@@ -51,5 +51,5 @@
         text_mode='original',
         pipeline=test_pipeline))
 
-val_evaluator = dict(type='RefSegMetric', metrics=['cIoU', 'mIoU'])
+val_evaluator = dict(type='RefSegMetric', iou_metrics=['cIoU', 'mIoU'])
 test_evaluator = val_evaluator
diff --git a/docs/en/user_guides/dataset_prepare.md b/docs/en/user_guides/dataset_prepare.md
@@ -99,3 +99,69 @@ data
 │   │   └── refs(umd).p
 |   |── train2014
 ```
+
+The images and annotations of [ADE20K](https://groups.csail.mit.edu/vision/datasets/ADE20K/) dataset can be download by running `tools/misc/download_dataset.py`:
+
+```shell
+python tools/misc/download_dataset.py --dataset-name ade20k_2016 --save-dir data --unzip
+```
+
+Then move the annotations to the `data/ADEChallengeData2016` directory and run the preprocess script to produce the coco format annotations:
+
+```shell
+mv data/annotations_instance data/ADEChallengeData2016/
+mv data/categoryMapping.txt data/ADEChallengeData2016/
+mv data/objectInfo150.txt data/ADEChallengeData2016/
+python tools/dataset_converters/ade20k2coco.py data/ADEChallengeData2016 --task panoptic
+python tools/dataset_converters/ade20k2coco.py data/ADEChallengeData2016 --task instance
+```
+
+The directory should be like this.
+
+```text
+data
+├── ADEChallengeData2016
+│   ├── ade20k_instance_train.json
+│   ├── ade20k_instance_val.json
+│   ├── ade20k_panoptic_train
+|   |   ├── ADE_train_00000001.png
+|   |   ├── ADE_train_00000002.png
+|   |   ├── ...
+│   ├── ade20k_panoptic_train.json
+│   ├── ade20k_panoptic_val
+|   |   ├── ADE_val_00000001.png
+|   |   ├── ADE_val_00000002.png
+|   |   ├── ...
+│   ├── ade20k_panoptic_val.json
+│   ├── annotations
+|   |   ├── training
+|   |   |   ├── ADE_train_00000001.png
+|   |   |   ├── ADE_train_00000002.png
+|   |   |   ├── ...
+|   |   ├── validation
+|   |   |   ├── ADE_val_00000001.png
+|   |   |   ├── ADE_val_00000002.png
+|   |   |   ├── ...
+│   ├── annotations_instance
+|   |   ├── training
+|   |   |   ├── ADE_train_00000001.png
+|   |   |   ├── ADE_train_00000002.png
+|   |   |   ├── ...
+|   |   ├── validation
+|   |   |   ├── ADE_val_00000001.png
+|   |   |   ├── ADE_val_00000002.png
+|   |   |   ├── ...
+│   ├── categoryMapping.txt
+│   ├── images
+│   |   ├── training
+|   |   |   ├── ADE_train_00000001.jpg
+|   |   |   ├── ADE_train_00000002.jpg
+|   |   |   ├── ...
+|   |   ├── validation
+|   |   |   ├── ADE_val_00000001.jpg
+|   |   |   ├── ADE_val_00000002.jpg
+|   |   |   ├── ...
+│   ├── imgCatIds.json
+│   ├── objectInfo150.txt
+|   |── sceneCategories.txt
+```
diff --git a/mmdet/datasets/__init__.py b/mmdet/datasets/__init__.py
@@ -1,5 +1,6 @@
 # Copyright (c) OpenMMLab. All rights reserved.
-from .ade20k import ADE20KPanopticDataset, ADE20KSegDataset
+from .ade20k import (ADE20KInstanceDataset, ADE20KPanopticDataset,
+                     ADE20KSegDataset)
 from .base_det_dataset import BaseDetDataset
 from .base_semseg_dataset import BaseSegDataset
 from .base_video_dataset import BaseVideoDataset
@@ -38,5 +39,6 @@
     'BaseVideoDataset', 'MOTChallengeDataset', 'TrackImgSampler',
     'ReIDDataset', 'YouTubeVISDataset', 'TrackAspectRatioBatchSampler',
     'ADE20KPanopticDataset', 'COCOCaptionDataset', 'RefCOCODataset',
-    'BaseSegDataset', 'ADE20KSegDataset', 'CocoSegDataset'
+    'BaseSegDataset', 'ADE20KSegDataset', 'CocoSegDataset',
+    'ADE20KInstanceDataset'
 ]