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提交 7a13a4b8 编写于 作者: Y Yang Zhang 提交者： qingqing01
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Fix code format for `data_feed.py` (#2516)

上级 9e5c26da
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Showing with 82 addition and 84 deletion
PaddleCV/object_detection/ppdet/data/data_feed.py
浏览文件 @ 7a13a4b8
...@@ -413,14 +413,14 @@ class FasterRCNNTrainFeed(DataFeed): ...@@ -413,14 +413,14 @@ class FasterRCNNTrainFeed(DataFeed):
], ],
image_shape=[3, 1333, 800], image_shape=[3, 1333, 800],
sample_transforms=[ sample_transforms=[
DecodeImage(to_rgb=True), RandomFlipImage(prob=0.5), DecodeImage(to_rgb=True),
NormalizeImage( RandomFlipImage(prob=0.5),
mean=[0.485, 0.456, 0.406], NormalizeImage(mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225], std=[0.229, 0.224, 0.225],
is_scale=True, is_scale=True,
is_channel_first=False), ResizeImage( is_channel_first=False),
target_size=800, max_size=1333, ResizeImage(target_size=800, max_size=1333, interp=1),
interp=1), Permute(to_bgr=False) Permute(to_bgr=False)
], ],
batch_transforms=[PadBatch()], batch_transforms=[PadBatch()],
batch_size=1, batch_size=1,
...@@ -463,17 +463,17 @@ class MaskRCNNTrainFeed(DataFeed): ...@@ -463,17 +463,17 @@ class MaskRCNNTrainFeed(DataFeed):
], ],
image_shape=[3, 1333, 800], image_shape=[3, 1333, 800],
sample_transforms=[ sample_transforms=[
DecodeImage(to_rgb=True), RandomFlipImage( DecodeImage(to_rgb=True),
prob=0.5, is_mask_flip=True), NormalizeImage( RandomFlipImage(prob=0.5, is_mask_flip=True),
mean=[0.485, 0.456, 0.406], NormalizeImage(mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225], std=[0.229, 0.224, 0.225],
is_scale=True, is_scale=True,
is_channel_first=False), ResizeImage( is_channel_first=False),
target_size=800, ResizeImage(target_size=800,
max_size=1333, max_size=1333,
interp=1, interp=1,
use_cv2=True), Permute( use_cv2=True),
to_bgr=False, channel_first=True) Permute(to_bgr=False, channel_first=True)
], ],
batch_transforms=[PadBatch()], batch_transforms=[PadBatch()],
batch_size=1, batch_size=1,
...@@ -509,12 +509,12 @@ class FasterRCNNEvalFeed(DataFeed): ...@@ -509,12 +509,12 @@ class FasterRCNNEvalFeed(DataFeed):
fields=['image', 'im_info', 'im_id', 'im_shape'], fields=['image', 'im_info', 'im_id', 'im_shape'],
image_shape=[3, 1333, 800], image_shape=[3, 1333, 800],
sample_transforms=[ sample_transforms=[
DecodeImage(to_rgb=True), NormalizeImage( DecodeImage(to_rgb=True),
mean=[0.485, 0.456, 0.406], NormalizeImage(mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225], std=[0.229, 0.224, 0.225],
is_scale=True, is_scale=True,
is_channel_first=False), ResizeImage( is_channel_first=False),
target_size=800, max_size=1333, interp=1), ResizeImage(target_size=800, max_size=1333, interp=1),
Permute(to_bgr=False) Permute(to_bgr=False)
], ],
batch_transforms=[PadBatch()], batch_transforms=[PadBatch()],
...@@ -552,11 +552,12 @@ class FasterRCNNTestFeed(DataFeed): ...@@ -552,11 +552,12 @@ class FasterRCNNTestFeed(DataFeed):
fields=['image', 'im_info', 'im_id', 'im_shape'], fields=['image', 'im_info', 'im_id', 'im_shape'],
image_shape=[3, 1333, 800], image_shape=[3, 1333, 800],
sample_transforms=[ sample_transforms=[
DecodeImage(to_rgb=True), NormalizeImage( DecodeImage(to_rgb=True),
mean=[0.485, 0.456, 0.406], NormalizeImage(mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225], std=[0.229, 0.224, 0.225],
is_scale=True, is_scale=True,
is_channel_first=False), Permute(to_bgr=False) is_channel_first=False),
Permute(to_bgr=False)
], ],
batch_transforms=[PadBatch()], batch_transforms=[PadBatch()],
batch_size=1, batch_size=1,
...@@ -595,16 +596,16 @@ class MaskRCNNEvalFeed(DataFeed): ...@@ -595,16 +596,16 @@ class MaskRCNNEvalFeed(DataFeed):
fields=['image', 'im_info', 'im_id', 'im_shape'], fields=['image', 'im_info', 'im_id', 'im_shape'],
image_shape=[3, 1333, 800], image_shape=[3, 1333, 800],
sample_transforms=[ sample_transforms=[
DecodeImage(to_rgb=True), NormalizeImage( DecodeImage(to_rgb=True),
mean=[0.485, 0.456, 0.406], NormalizeImage(mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225], std=[0.229, 0.224, 0.225],
is_scale=True, is_scale=True,
is_channel_first=False), ResizeImage( is_channel_first=False),
target_size=800, ResizeImage(target_size=800,
max_size=1333, max_size=1333,
interp=1, interp=1,
use_cv2=True), Permute( use_cv2=True),
to_bgr=False, channel_first=True) Permute(to_bgr=False, channel_first=True)
], ],
batch_transforms=[PadBatch()], batch_transforms=[PadBatch()],
batch_size=1, batch_size=1,
...@@ -643,12 +644,13 @@ class MaskRCNNTestFeed(DataFeed): ...@@ -643,12 +644,13 @@ class MaskRCNNTestFeed(DataFeed):
fields=['image', 'im_info', 'im_id', 'im_shape'], fields=['image', 'im_info', 'im_id', 'im_shape'],
image_shape=[3, 1333, 800], image_shape=[3, 1333, 800],
sample_transforms=[ sample_transforms=[
DecodeImage(to_rgb=True), NormalizeImage( DecodeImage(to_rgb=True),
NormalizeImage(
mean=[0.485, 0.456, 0.406], mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225], std=[0.229, 0.224, 0.225],
is_scale=True, is_scale=True,
is_channel_first=False), Permute( is_channel_first=False),
to_bgr=False, channel_first=True) Permute(to_bgr=False, channel_first=True)
], ],
batch_transforms=[PadBatch()], batch_transforms=[PadBatch()],
batch_size=1, batch_size=1,
...@@ -688,28 +690,26 @@ class SSDTrainFeed(DataFeed): ...@@ -688,28 +690,26 @@ class SSDTrainFeed(DataFeed):
fields=['image', 'gt_box', 'gt_label', 'is_difficult'], fields=['image', 'gt_box', 'gt_label', 'is_difficult'],
image_shape=[3, 300, 300], image_shape=[3, 300, 300],
sample_transforms=[ sample_transforms=[
DecodeImage( DecodeImage(to_rgb=True, with_mixup=False),
to_rgb=True, NormalizeBox(),
with_mixup=False), NormalizeBox(), RandomDistort( RandomDistort(brightness_lower=0.875,
brightness_lower=0.875, brightness_upper=1.125,
brightness_upper=1.125, is_order=True),
is_order=True), ExpandImage( ExpandImage(max_ratio=4, prob=0.5),
max_ratio=4, prob=0.5), CropImage([[1, 1, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0],
CropImage( [1, 50, 0.3, 1.0, 0.5, 2.0, 0.1, 0.0],
batch_sampler=[[1, 1, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0], [1, 50, 0.3, 1.0, 0.5, 2.0, 0.3, 0.0],
[1, 50, 0.3, 1.0, 0.5, 2.0, 0.1, 0.0], [1, 50, 0.3, 1.0, 0.5, 2.0, 0.5, 0.0],
[1, 50, 0.3, 1.0, 0.5, 2.0, 0.3, 0.0], [1, 50, 0.3, 1.0, 0.5, 2.0, 0.7, 0.0],
[1, 50, 0.3, 1.0, 0.5, 2.0, 0.5, 0.0], [1, 50, 0.3, 1.0, 0.5, 2.0, 0.9, 0.0],
[1, 50, 0.3, 1.0, 0.5, 2.0, 0.7, 0.0], [1, 50, 0.3, 1.0, 0.5, 2.0, 0.0, 1.0]],
[1, 50, 0.3, 1.0, 0.5, 2.0, 0.9, 0.0], satisfy_all=False),
[1, 50, 0.3, 1.0, 0.5, 2.0, 0.0, 1.0]], ResizeImage(target_size=300, use_cv2=False, interp=1),
satisfy_all=False), ResizeImage( RandomFlipImage(is_normalized=True),
target_size=300, use_cv2=False, Permute(),
interp=1), RandomFlipImage(is_normalized=True), NormalizeImage(mean=[127.5, 127.5, 127.5],
Permute(), NormalizeImage( std=[127.502231, 127.502231, 127.502231],
mean=[127.5, 127.5, 127.5], is_scale=False)
std=[127.502231, 127.502231, 127.502231],
is_scale=False)
], ],
batch_transforms=[], batch_transforms=[],
batch_size=32, batch_size=32,
...@@ -747,10 +747,12 @@ class SSDEvalFeed(DataFeed): ...@@ -747,10 +747,12 @@ class SSDEvalFeed(DataFeed):
fields=['image', 'gt_box', 'gt_label', 'is_difficult'], fields=['image', 'gt_box', 'gt_label', 'is_difficult'],
image_shape=[3, 300, 300], image_shape=[3, 300, 300],
sample_transforms=[ sample_transforms=[
DecodeImage( DecodeImage(to_rgb=True, with_mixup=False),
to_rgb=True, with_mixup=False), NormalizeBox(), ResizeImage( NormalizeBox(),
target_size=300, use_cv2=False, interp=1), ResizeImage(target_size=300, use_cv2=False, interp=1),
RandomFlipImage(is_normalized=True), Permute(), NormalizeImage( RandomFlipImage(is_normalized=True),
Permute(),
NormalizeImage(
mean=[127.5, 127.5, 127.5], mean=[127.5, 127.5, 127.5],
std=[127.502231, 127.502231, 127.502231], std=[127.502231, 127.502231, 127.502231],
is_scale=False) is_scale=False)
...@@ -790,8 +792,9 @@ class SSDTestFeed(DataFeed): ...@@ -790,8 +792,9 @@ class SSDTestFeed(DataFeed):
fields=['image'], fields=['image'],
image_shape=[3, 300, 300], image_shape=[3, 300, 300],
sample_transforms=[ sample_transforms=[
DecodeImage(to_rgb=True), ResizeImage( DecodeImage(to_rgb=True),
target_size=300, use_cv2=False, interp=1), Permute(), ResizeImage(target_size=300, use_cv2=False, interp=1),
Permute(),
NormalizeImage( NormalizeImage(
mean=[127.5, 127.5, 127.5], mean=[127.5, 127.5, 127.5],
std=[127.502231, 127.502231, 127.502231], std=[127.502231, 127.502231, 127.502231],
...@@ -833,14 +836,12 @@ class YoloTrainFeed(DataFeed): ...@@ -833,14 +836,12 @@ class YoloTrainFeed(DataFeed):
fields=['image', 'gt_box', 'gt_label', 'gt_score'], fields=['image', 'gt_box', 'gt_label', 'gt_score'],
image_shape=[3, 608, 608], image_shape=[3, 608, 608],
sample_transforms=[ sample_transforms=[
DecodeImage( DecodeImage(to_rgb=True, with_mixup=True),
to_rgb=True, with_mixup=True), MixupImage(alpha=1.5, beta=1.5),
MixupImage(
alpha=1.5, beta=1.5),
NormalizeBox(), NormalizeBox(),
RandomDistort(), RandomDistort(),
ExpandImage( ExpandImage(max_ratio=4., prob=.5,
max_ratio=4., prob=.5, mean=[123.675, 116.28, 103.53]), mean=[123.675, 116.28, 103.53]),
CropImage([[1, 1, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0], CropImage([[1, 1, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0],
[1, 50, 0.3, 1.0, 0.5, 2.0, 0.1, 1.0], [1, 50, 0.3, 1.0, 0.5, 2.0, 0.1, 1.0],
[1, 50, 0.3, 1.0, 0.5, 2.0, 0.3, 1.0], [1, 50, 0.3, 1.0, 0.5, 2.0, 0.3, 1.0],
...@@ -903,8 +904,7 @@ class YoloEvalFeed(DataFeed): ...@@ -903,8 +904,7 @@ class YoloEvalFeed(DataFeed):
image_shape=[3, 608, 608], image_shape=[3, 608, 608],
sample_transforms=[ sample_transforms=[
DecodeImage(to_rgb=True), DecodeImage(to_rgb=True),
ResizeImage( ResizeImage(target_size=608, interp=2),
target_size=608, interp=2),
NormalizeImage( NormalizeImage(
mean=[0.485, 0.456, 0.406], mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225], std=[0.229, 0.224, 0.225],
...@@ -951,13 +951,11 @@ class YoloTestFeed(DataFeed): ...@@ -951,13 +951,11 @@ class YoloTestFeed(DataFeed):
image_shape=[3, 608, 608], image_shape=[3, 608, 608],
sample_transforms=[ sample_transforms=[
DecodeImage(to_rgb=True), DecodeImage(to_rgb=True),
ResizeImage( ResizeImage(target_size=608, interp=2),
target_size=608, interp=2), NormalizeImage(mean=[0.485, 0.456, 0.406],
NormalizeImage( std=[0.229, 0.224, 0.225],
mean=[0.485, 0.456, 0.406], is_scale=True,
std=[0.229, 0.224, 0.225], is_channel_first=False),
is_scale=True,
is_channel_first=False),
Permute(to_bgr=False), Permute(to_bgr=False),
], ],
batch_transforms=[], batch_transforms=[],
......
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