From 9118a94a4a0eee4ae2a24908f6c6684fb9a76468 Mon Sep 17 00:00:00 2001
From: Cao Yuhang <yhcao6@gmail.com>
Date: Tue, 24 Dec 2019 17:03:34 +0800
Subject: [PATCH] Split SegResizeFlipPadRescale into different existing
transforms (#1852)
* Split seg trans
* Modify cfg
* fix typo
---
configs/hrnet/htc_hrnetv2p_w32_20e.py | 2 +-
...-c5_mstrain_400_1400_x101_64x4d_fpn_20e.py | 2 +-
configs/htc/htc_r101_fpn_20e.py | 2 +-
configs/htc/htc_r50_fpn_1x.py | 2 +-
configs/htc/htc_r50_fpn_20e.py | 2 +-
configs/htc/htc_x101_32x4d_fpn_20e_16gpu.py | 2 +-
configs/htc/htc_x101_64x4d_fpn_20e_16gpu.py | 2 +-
mmdet/datasets/custom.py | 1 +
mmdet/datasets/pipelines/__init__.py | 6 +--
mmdet/datasets/pipelines/loading.py | 1 +
mmdet/datasets/pipelines/transforms.py | 54 +++++++++----------
11 files changed, 39 insertions(+), 37 deletions(-)
diff --git a/configs/hrnet/htc_hrnetv2p_w32_20e.py b/configs/hrnet/htc_hrnetv2p_w32_20e.py
index 8279f24..a148963 100644
--- a/configs/hrnet/htc_hrnetv2p_w32_20e.py
+++ b/configs/hrnet/htc_hrnetv2p_w32_20e.py
@@ -221,7 +221,7 @@ train_pipeline = [
dict(type='RandomFlip', flip_ratio=0.5),
dict(type='Normalize', **img_norm_cfg),
dict(type='Pad', size_divisor=32),
- dict(type='SegResizeFlipPadRescale', scale_factor=1 / 8),
+ dict(type='SegRescale', scale_factor=1 / 8),
dict(type='DefaultFormatBundle'),
dict(
type='Collect',
diff --git a/configs/htc/htc_dconv_c3-c5_mstrain_400_1400_x101_64x4d_fpn_20e.py b/configs/htc/htc_dconv_c3-c5_mstrain_400_1400_x101_64x4d_fpn_20e.py
index 2072f29..275b7fb 100644
--- a/configs/htc/htc_dconv_c3-c5_mstrain_400_1400_x101_64x4d_fpn_20e.py
+++ b/configs/htc/htc_dconv_c3-c5_mstrain_400_1400_x101_64x4d_fpn_20e.py
@@ -217,7 +217,7 @@ train_pipeline = [
dict(type='RandomFlip', flip_ratio=0.5),
dict(type='Normalize', **img_norm_cfg),
dict(type='Pad', size_divisor=32),
- dict(type='SegResizeFlipPadRescale', scale_factor=1 / 8),
+ dict(type='SegRescale', scale_factor=1 / 8),
dict(type='DefaultFormatBundle'),
dict(
type='Collect',
diff --git a/configs/htc/htc_r101_fpn_20e.py b/configs/htc/htc_r101_fpn_20e.py
index 661c564..4f0ec72 100644
--- a/configs/htc/htc_r101_fpn_20e.py
+++ b/configs/htc/htc_r101_fpn_20e.py
@@ -205,7 +205,7 @@ train_pipeline = [
dict(type='RandomFlip', flip_ratio=0.5),
dict(type='Normalize', **img_norm_cfg),
dict(type='Pad', size_divisor=32),
- dict(type='SegResizeFlipPadRescale', scale_factor=1 / 8),
+ dict(type='SegRescale', scale_factor=1 / 8),
dict(type='DefaultFormatBundle'),
dict(
type='Collect',
diff --git a/configs/htc/htc_r50_fpn_1x.py b/configs/htc/htc_r50_fpn_1x.py
index 4945f2e..34ac663 100644
--- a/configs/htc/htc_r50_fpn_1x.py
+++ b/configs/htc/htc_r50_fpn_1x.py
@@ -205,7 +205,7 @@ train_pipeline = [
dict(type='RandomFlip', flip_ratio=0.5),
dict(type='Normalize', **img_norm_cfg),
dict(type='Pad', size_divisor=32),
- dict(type='SegResizeFlipPadRescale', scale_factor=1 / 8),
+ dict(type='SegRescale', scale_factor=1 / 8),
dict(type='DefaultFormatBundle'),
dict(
type='Collect',
diff --git a/configs/htc/htc_r50_fpn_20e.py b/configs/htc/htc_r50_fpn_20e.py
index ccf73a0..47714ac 100644
--- a/configs/htc/htc_r50_fpn_20e.py
+++ b/configs/htc/htc_r50_fpn_20e.py
@@ -205,7 +205,7 @@ train_pipeline = [
dict(type='RandomFlip', flip_ratio=0.5),
dict(type='Normalize', **img_norm_cfg),
dict(type='Pad', size_divisor=32),
- dict(type='SegResizeFlipPadRescale', scale_factor=1 / 8),
+ dict(type='SegRescale', scale_factor=1 / 8),
dict(type='DefaultFormatBundle'),
dict(
type='Collect',
diff --git a/configs/htc/htc_x101_32x4d_fpn_20e_16gpu.py b/configs/htc/htc_x101_32x4d_fpn_20e_16gpu.py
index 915a54e..b211ba9 100644
--- a/configs/htc/htc_x101_32x4d_fpn_20e_16gpu.py
+++ b/configs/htc/htc_x101_32x4d_fpn_20e_16gpu.py
@@ -207,7 +207,7 @@ train_pipeline = [
dict(type='RandomFlip', flip_ratio=0.5),
dict(type='Normalize', **img_norm_cfg),
dict(type='Pad', size_divisor=32),
- dict(type='SegResizeFlipPadRescale', scale_factor=1 / 8),
+ dict(type='SegRescale', scale_factor=1 / 8),
dict(type='DefaultFormatBundle'),
dict(
type='Collect',
diff --git a/configs/htc/htc_x101_64x4d_fpn_20e_16gpu.py b/configs/htc/htc_x101_64x4d_fpn_20e_16gpu.py
index 99ceefc..0186d72 100644
--- a/configs/htc/htc_x101_64x4d_fpn_20e_16gpu.py
+++ b/configs/htc/htc_x101_64x4d_fpn_20e_16gpu.py
@@ -207,7 +207,7 @@ train_pipeline = [
dict(type='RandomFlip', flip_ratio=0.5),
dict(type='Normalize', **img_norm_cfg),
dict(type='Pad', size_divisor=32),
- dict(type='SegResizeFlipPadRescale', scale_factor=1 / 8),
+ dict(type='SegRescale', scale_factor=1 / 8),
dict(type='DefaultFormatBundle'),
dict(
type='Collect',
diff --git a/mmdet/datasets/custom.py b/mmdet/datasets/custom.py
index d068543..935b39d 100644
--- a/mmdet/datasets/custom.py
+++ b/mmdet/datasets/custom.py
@@ -98,6 +98,7 @@ class CustomDataset(Dataset):
results['proposal_file'] = self.proposal_file
results['bbox_fields'] = []
results['mask_fields'] = []
+ results['seg_fields'] = []
def _filter_imgs(self, min_size=32):
"""Filter images too small."""
diff --git a/mmdet/datasets/pipelines/__init__.py b/mmdet/datasets/pipelines/__init__.py
index ae55b25..bfe375c 100644
--- a/mmdet/datasets/pipelines/__init__.py
+++ b/mmdet/datasets/pipelines/__init__.py
@@ -5,12 +5,12 @@ from .loading import LoadAnnotations, LoadImageFromFile, LoadProposals
from .test_aug import MultiScaleFlipAug
from .transforms import (Albu, Expand, MinIoURandomCrop, Normalize, Pad,
PhotoMetricDistortion, RandomCrop, RandomFlip, Resize,
- SegResizeFlipPadRescale)
+ SegRescale)
__all__ = [
'Compose', 'to_tensor', 'ToTensor', 'ImageToTensor', 'ToDataContainer',
'Transpose', 'Collect', 'LoadAnnotations', 'LoadImageFromFile',
'LoadProposals', 'MultiScaleFlipAug', 'Resize', 'RandomFlip', 'Pad',
- 'RandomCrop', 'Normalize', 'SegResizeFlipPadRescale', 'MinIoURandomCrop',
- 'Expand', 'PhotoMetricDistortion', 'Albu'
+ 'RandomCrop', 'Normalize', 'SegRescale', 'MinIoURandomCrop', 'Expand',
+ 'PhotoMetricDistortion', 'Albu'
]
diff --git a/mmdet/datasets/pipelines/loading.py b/mmdet/datasets/pipelines/loading.py
index 9f3007e..f4aa6de 100644
--- a/mmdet/datasets/pipelines/loading.py
+++ b/mmdet/datasets/pipelines/loading.py
@@ -91,6 +91,7 @@ class LoadAnnotations(object):
results['gt_semantic_seg'] = mmcv.imread(
osp.join(results['seg_prefix'], results['ann_info']['seg_map']),
flag='unchanged').squeeze()
+ results['seg_fields'].append('gt_semantic_seg')
return results
def __call__(self, results):
diff --git a/mmdet/datasets/pipelines/transforms.py b/mmdet/datasets/pipelines/transforms.py
index dc38597..f57eb4e 100644
--- a/mmdet/datasets/pipelines/transforms.py
+++ b/mmdet/datasets/pipelines/transforms.py
@@ -149,12 +149,23 @@ class Resize(object):
]
results[key] = masks
+ def _resize_seg(self, results):
+ for key in results.get('seg_fields', []):
+ if self.keep_ratio:
+ gt_seg = mmcv.imrescale(
+ results[key], results['scale'], interpolation='nearest')
+ else:
+ gt_seg = mmcv.imresize(
+ results[key], results['scale'], interpolation='nearest')
+ results['gt_semantic_seg'] = gt_seg
+
def __call__(self, results):
if 'scale' not in results:
self._random_scale(results)
self._resize_img(results)
self._resize_bboxes(results)
self._resize_masks(results)
+ self._resize_seg(results)
return results
def __repr__(self):
@@ -229,6 +240,11 @@ class RandomFlip(object):
mmcv.imflip(mask, direction=results['flip_direction'])
for mask in results[key]
]
+
+ # flip segs
+ for key in results.get('seg_fields', []):
+ results[key] = mmcv.imflip(
+ results[key], direction=results['flip_direction'])
return results
def __repr__(self):
@@ -280,9 +296,14 @@ class Pad(object):
else:
results[key] = np.empty((0, ) + pad_shape, dtype=np.uint8)
+ def _pad_seg(self, results):
+ for key in results.get('seg_fields', []):
+ results[key] = mmcv.impad(results[key], results['pad_shape'][:2])
+
def __call__(self, results):
self._pad_img(results)
self._pad_masks(results)
+ self._pad_seg(results)
return results
def __repr__(self):
@@ -386,15 +407,8 @@ class RandomCrop(object):
@PIPELINES.register_module
-class SegResizeFlipPadRescale(object):
- """A sequential transforms to semantic segmentation maps.
-
- The same pipeline as input images is applied to the semantic segmentation
- map, and finally rescale it by some scale factor. The transforms include:
- 1. resize
- 2. flip
- 3. pad
- 4. rescale (so that the final size can be different from the image size)
+class SegRescale(object):
+ """Rescale semantic segmentation maps.
Args:
scale_factor (float): The scale factor of the final output.
@@ -404,24 +418,10 @@ class SegResizeFlipPadRescale(object):
self.scale_factor = scale_factor
def __call__(self, results):
- if results['keep_ratio']:
- gt_seg = mmcv.imrescale(
- results['gt_semantic_seg'],
- results['scale'],
- interpolation='nearest')
- else:
- gt_seg = mmcv.imresize(
- results['gt_semantic_seg'],
- results['scale'],
- interpolation='nearest')
- if results['flip']:
- gt_seg = mmcv.imflip(gt_seg)
- if gt_seg.shape != results['pad_shape']:
- gt_seg = mmcv.impad(gt_seg, results['pad_shape'][:2])
- if self.scale_factor != 1:
- gt_seg = mmcv.imrescale(
- gt_seg, self.scale_factor, interpolation='nearest')
- results['gt_semantic_seg'] = gt_seg
+ for key in results.get('seg_fields', []):
+ if self.scale_factor != 1:
+ results[key] = mmcv.imrescale(
+ results[key], self.scale_factor, interpolation='nearest')
return results
def __repr__(self):
--
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