[Feature] Add HRSC Dataset (#96)

* Add HRSCDataset * Add HRSCDataset * Add doc * fix test path * fix num_class * add retinanet hrsc result * fix typo add s2anet config * fix add s2anet result * fix indentation
open-mmlab · Mar 14, 2022 · 1972435 · 1972435
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diff --git a/configs/_base_/datasets/hrsc.py b/configs/_base_/datasets/hrsc.py
@@ -0,0 +1,53 @@
+# dataset settings
+dataset_type = 'HRSCDataset'
+data_root = 'data/hrsc/'
+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'),
+    dict(type='LoadAnnotations', with_bbox=True),
+    dict(type='RResize', img_scale=(800, 800)),
+    dict(type='RRandomFlip', flip_ratio=0.5),
+    dict(type='Normalize', **img_norm_cfg),
+    dict(type='Pad', size_divisor=32),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels'])
+]
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='MultiScaleFlipAug',
+        img_scale=(800, 800),
+        flip=False,
+        transforms=[
+            dict(type='RResize'),
+            dict(type='Normalize', **img_norm_cfg),
+            dict(type='Pad', size_divisor=32),
+            dict(type='DefaultFormatBundle'),
+            dict(type='Collect', keys=['img'])
+        ])
+]
+data = dict(
+    samples_per_gpu=2,
+    workers_per_gpu=2,
+    train=dict(
+        type=dataset_type,
+        classwise=False,
+        ann_file=data_root + 'ImageSets/trainval.txt',
+        ann_subdir=data_root + 'FullDataSet/Annotations/',
+        img_subdir=data_root + 'FullDataSet/AllImages/',
+        pipeline=train_pipeline),
+    val=dict(
+        type=dataset_type,
+        classwise=False,
+        ann_file=data_root + 'ImageSets/trainval.txt',
+        ann_subdir=data_root + 'FullDataSet/Annotations/',
+        img_subdir=data_root + 'FullDataSet/AllImages/',
+        pipeline=test_pipeline),
+    test=dict(
+        type=dataset_type,
+        classwise=False,
+        ann_file=data_root + 'ImageSets/test.txt',
+        ann_subdir=data_root + 'FullDataSet/Annotations/',
+        img_subdir=data_root + 'FullDataSet/AllImages/',
+        pipeline=test_pipeline))
diff --git a/configs/rotated_retinanet/README.md b/configs/rotated_retinanet/README.md
@@ -22,6 +22,12 @@ DOTA1.0
 | ResNet50 (1024,1024,200) | 69.79 | le135 | 1x | 3.38 | 17.2 | - | 2 | [rotated_retinanet_obb_r50_fpn_1x_dota_le135](./rotated_retinanet_obb_r50_fpn_1x_dota_le135.py) |  [model](https://download.openmmlab.com/mmrotate/v0.1.0/rotated_retinanet/rotated_retinanet_obb_r50_fpn_1x_dota_le135/rotated_retinanet_obb_r50_fpn_1x_dota_le135-e4131166.pth) &#124; [log](https://download.openmmlab.com/mmrotate/v0.1.0/rotated_retinanet/rotated_retinanet_obb_r50_fpn_1x_dota_le135/rotated_retinanet_obb_r50_fpn_1x_dota_le135_20220128_130755.log.json)
 | ResNet50 (1024,1024,200) | 76.50 | le90 | 1x |   | 17.5 | MS+RR | 2 | [rotated_retinanet_obb_r50_fpn_1x_dota_ms_rr_le90](./rotated_retinanet_obb_r50_fpn_1x_dota_ms_rr_le90.py) |  [model](https://download.openmmlab.com/mmrotate/v0.1.0/rotated_retinanet/rotated_retinanet_obb_r50_fpn_1x_dota_ms_rr_le90/rotated_retinanet_obb_r50_fpn_1x_dota_ms_rr_le90-1da1ec9c.pth) &#124; [log](https://download.openmmlab.com/mmrotate/v0.1.0/rotated_retinanet/rotated_retinanet_obb_r50_fpn_1x_dota_ms_rr_le90/rotated_retinanet_obb_r50_fpn_1x_dota_ms_rr_le90_20220210_114843.log.json)
 
+HRSC
+
+|       Backbone        |  mAP  | Angle | lr schd | Mem (GB) | Inf Time (fps) | Aug | Batch Size |                                            Configs                                            | Download |
+|:---------------------:|:-----:|:-----------:|:-------:|:---------:|:---------:|:---------:|:---------:|:---------------------------------------------------------------------------------------------:|:-------------:|
+|  ResNet50 (800,800)   | 72.62 | le90 |   3x    |  |  | - | 2 | [rotated_retinanet_obb_r50_fpn_3x_hrsc_le90](./rotated_retinanet_obb_r50_fpn_3x_hrsc_le90.py) |
+
 Notes:
 - `MS` means multiple scale image split.
 - `RR` means random rotation.

diff --git a/configs/rotated_retinanet/rotated_retinanet_obb_r50_fpn_3x_hrsc_le90.py b/configs/rotated_retinanet/rotated_retinanet_obb_r50_fpn_3x_hrsc_le90.py
@@ -0,0 +1,92 @@
+_base_ = [
+    '../_base_/datasets/hrsc.py', '../_base_/schedules/schedule_3x.py',
+    '../_base_/default_runtime.py'
+]
+
+angle_version = 'le90'
+model = dict(
+    type='RotatedRetinaNet',
+    backbone=dict(
+        type='ResNet',
+        depth=50,
+        num_stages=4,
+        out_indices=(0, 1, 2, 3),
+        frozen_stages=1,
+        zero_init_residual=False,
+        norm_cfg=dict(type='BN', requires_grad=True),
+        norm_eval=True,
+        style='pytorch',
+        init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50')),
+    neck=dict(
+        type='FPN',
+        in_channels=[256, 512, 1024, 2048],
+        out_channels=256,
+        start_level=1,
+        add_extra_convs='on_input',
+        num_outs=5),
+    bbox_head=dict(
+        type='RotatedRetinaHead',
+        num_classes=1,
+        in_channels=256,
+        stacked_convs=4,
+        feat_channels=256,
+        assign_by_circumhbbox=None,
+        anchor_generator=dict(
+            type='RotatedAnchorGenerator',
+            octave_base_scale=4,
+            scales_per_octave=3,
+            ratios=[1.0, 0.5, 2.0],
+            strides=[8, 16, 32, 64, 128]),
+        bbox_coder=dict(
+            type='DeltaXYWHAOBBoxCoder',
+            angle_range=angle_version,
+            norm_factor=None,
+            edge_swap=True,
+            proj_xy=True,
+            target_means=(.0, .0, .0, .0, .0),
+            target_stds=(1.0, 1.0, 1.0, 1.0, 1.0)),
+        loss_cls=dict(
+            type='FocalLoss',
+            use_sigmoid=True,
+            gamma=2.0,
+            alpha=0.25,
+            loss_weight=1.0),
+        loss_bbox=dict(type='L1Loss', loss_weight=1.0)),
+    train_cfg=dict(
+        assigner=dict(
+            type='MaxIoUAssigner',
+            pos_iou_thr=0.5,
+            neg_iou_thr=0.4,
+            min_pos_iou=0,
+            ignore_iof_thr=-1,
+            iou_calculator=dict(type='RBboxOverlaps2D')),
+        allowed_border=-1,
+        pos_weight=-1,
+        debug=False),
+    test_cfg=dict(
+        nms_pre=2000,
+        min_bbox_size=0,
+        score_thr=0.05,
+        nms=dict(iou_thr=0.1),
+        max_per_img=2000))
+
+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'),
+    dict(type='LoadAnnotations', with_bbox=True),
+    dict(type='RResize', img_scale=(800, 800)),
+    dict(
+        type='RRandomFlip',
+        flip_ratio=[0.25, 0.25, 0.25],
+        direction=['horizontal', 'vertical', 'diagonal'],
+        version=angle_version),
+    dict(type='Normalize', **img_norm_cfg),
+    dict(type='Pad', size_divisor=32),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels'])
+]
+data = dict(
+    train=dict(pipeline=train_pipeline, version=angle_version),
+    val=dict(version=angle_version),
+    test=dict(version=angle_version))
diff --git a/configs/s2anet/README.md b/configs/s2anet/README.md
@@ -20,6 +20,11 @@ DOTA1.0
 | ResNet50 (1024,1024,200) | 73.91 | le135 | 1x | 3.14 | 15.5 | - | 2 | [s2anet_r50_fpn_1x_dota_le135](./s2anet_r50_fpn_1x_dota_le135.py) | [model](https://download.openmmlab.com/mmrotate/v0.1.0/s2anet/s2anet_r50_fpn_1x_dota_le135/s2anet_r50_fpn_1x_dota_le135-5dfcf396.pth) &#124; [log](https://download.openmmlab.com/mmrotate/v0.1.0/s2anet/s2anet_r50_fpn_1x_dota_le135/s2anet_r50_fpn_1x_dota_le135_20220124_163529.log.json)
 | ResNet50 (1024,1024,200) | 74.19 | le135 | 1x | 2.17 | 17.4 | - | 2 | [s2anet_r50_fpn_fp16_1x_dota_le135](./s2anet_r50_fpn_fp16_1x_dota_le135.py) | [model](https://download.openmmlab.com/mmrotate/v0.1.0/s2anet/s2anet_r50_fpn_fp16_1x_dota_le135/s2anet_r50_fpn_fp16_1x_dota_le135-5cac515c.pth) &#124; [log](https://download.openmmlab.com/mmrotate/v0.1.0/s2anet/s2anet_r50_fpn_fp16_1x_dota_le135/s2anet_r50_fpn_fp16_1x_dota_le135_20220303_194910.log.json)
 
+HRSC
+
+|       Backbone        |  mAP  | Angle | lr schd | Mem (GB) | Inf Time (fps) | Aug | Batch Size |                                            Configs                                            | Download |
+|:---------------------:|:-----:|:-----------:|:-------:|:---------:|:---------:|:---------:|:---------:|:---------------------------------------------------------------------------------------------:|:-------------:|
+|  ResNet50 (800,800)   | 89.75 | le90 |   3x    |  |  | - | 2 | [s2anet_r50_fpn_3x_hrsc_le135](./s2anet_r50_fpn_3x_hrsc_le135.py) |
 
 ## Citation
 ```

diff --git a/configs/s2anet/s2anet_r50_fpn_3x_hrsc_le135.py b/configs/s2anet/s2anet_r50_fpn_3x_hrsc_le135.py
@@ -0,0 +1,132 @@
+_base_ = [
+    '../_base_/datasets/hrsc.py', '../_base_/schedules/schedule_3x.py',
+    '../_base_/default_runtime.py'
+]
+
+angle_version = 'le135'
+model = dict(
+    type='S2ANet',
+    backbone=dict(
+        type='ResNet',
+        depth=50,
+        num_stages=4,
+        out_indices=(0, 1, 2, 3),
+        frozen_stages=1,
+        zero_init_residual=False,
+        norm_cfg=dict(type='BN', requires_grad=True),
+        norm_eval=True,
+        style='pytorch',
+        init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50')),
+    neck=dict(
+        type='FPN',
+        in_channels=[256, 512, 1024, 2048],
+        out_channels=256,
+        start_level=1,
+        add_extra_convs='on_input',
+        num_outs=5),
+    fam_head=dict(
+        type='RotatedRetinaHead',
+        num_classes=1,
+        in_channels=256,
+        stacked_convs=2,
+        feat_channels=256,
+        assign_by_circumhbbox=None,
+        anchor_generator=dict(
+            type='RotatedAnchorGenerator',
+            scales=[4],
+            ratios=[1.0],
+            strides=[8, 16, 32, 64, 128]),
+        bbox_coder=dict(
+            type='DeltaXYWHAOBBoxCoder',
+            angle_range=angle_version,
+            norm_factor=1,
+            edge_swap=False,
+            proj_xy=True,
+            target_means=(.0, .0, .0, .0, .0),
+            target_stds=(1.0, 1.0, 1.0, 1.0, 1.0)),
+        loss_cls=dict(
+            type='FocalLoss',
+            use_sigmoid=True,
+            gamma=2.0,
+            alpha=0.25,
+            loss_weight=1.0),
+        loss_bbox=dict(type='SmoothL1Loss', beta=0.11, loss_weight=1.0)),
+    align_cfgs=dict(
+        type='AlignConv',
+        kernel_size=3,
+        channels=256,
+        featmap_strides=[8, 16, 32, 64, 128]),
+    odm_head=dict(
+        type='ODMRefineHead',
+        num_classes=1,
+        in_channels=256,
+        stacked_convs=2,
+        feat_channels=256,
+        assign_by_circumhbbox=None,
+        anchor_generator=dict(
+            type='PseudoAnchorGenerator', strides=[8, 16, 32, 64, 128]),
+        bbox_coder=dict(
+            type='DeltaXYWHAOBBoxCoder',
+            angle_range=angle_version,
+            norm_factor=1,
+            edge_swap=False,
+            proj_xy=True,
+            target_means=(0.0, 0.0, 0.0, 0.0, 0.0),
+            target_stds=(1.0, 1.0, 1.0, 1.0, 1.0)),
+        loss_cls=dict(
+            type='FocalLoss',
+            use_sigmoid=True,
+            gamma=2.0,
+            alpha=0.25,
+            loss_weight=1.0),
+        loss_bbox=dict(type='SmoothL1Loss', beta=0.11, loss_weight=1.0)),
+    train_cfg=dict(
+        fam_cfg=dict(
+            assigner=dict(
+                type='MaxIoUAssigner',
+                pos_iou_thr=0.5,
+                neg_iou_thr=0.4,
+                min_pos_iou=0,
+                ignore_iof_thr=-1,
+                iou_calculator=dict(type='RBboxOverlaps2D')),
+            allowed_border=-1,
+            pos_weight=-1,
+            debug=False),
+        odm_cfg=dict(
+            assigner=dict(
+                type='MaxIoUAssigner',
+                pos_iou_thr=0.5,
+                neg_iou_thr=0.4,
+                min_pos_iou=0,
+                ignore_iof_thr=-1,
+                iou_calculator=dict(type='RBboxOverlaps2D')),
+            allowed_border=-1,
+            pos_weight=-1,
+            debug=False)),
+    test_cfg=dict(
+        nms_pre=2000,
+        min_bbox_size=0,
+        score_thr=0.05,
+        nms=dict(iou_thr=0.1),
+        max_per_img=2000))
+
+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'),
+    dict(type='LoadAnnotations', with_bbox=True),
+    dict(type='RResize', img_scale=(800, 800)),
+    dict(
+        type='RRandomFlip',
+        flip_ratio=[0.25, 0.25, 0.25],
+        direction=['horizontal', 'vertical', 'diagonal'],
+        version=angle_version),
+    dict(type='Normalize', **img_norm_cfg),
+    dict(type='Pad', size_divisor=32),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels'])
+]
+data = dict(
+    train=dict(pipeline=train_pipeline, version=angle_version),
+    val=dict(version=angle_version),
+    test=dict(version=angle_version))
diff --git a/mmrotate/datasets/__init__.py b/mmrotate/datasets/__init__.py
@@ -1,7 +1,8 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 from .builder import build_dataset  # noqa: F401, F403
 from .dota import DOTADataset  # noqa: F401, F403
+from .hrsc import HRSCDataset  # noqa: F401, F403
 from .pipelines import *  # noqa: F401, F403
 from .sar import SARDataset  # noqa: F401, F403
 
-__all__ = ['SARDataset', 'DOTADataset', 'build_dataset']
+__all__ = ['SARDataset', 'DOTADataset', 'build_dataset', 'HRSCDataset']