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Commit b320d0ab authored by yhcao6's avatar yhcao6
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fix

parent 450cfb73
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Showing with 31 additions and 24 deletions
configs/ssd300_voc.py → configs/pascal_voc/ssd300_voc.py
View file @ b320d0ab
# model settings # model settings
input_size = 300
model = dict( model = dict(
type='SingleStageDetector', type='SingleStageDetector',
pretrained='data/vgg_backbone.pth', pretrained='data/vgg_backbone.pth',
backbone=dict( backbone=dict(
type='SSDVGG', type='SSDVGG',
input_size=300, input_size=input_size,
depth=16, depth=16,
with_last_pool=False, with_last_pool=False,
ceil_mode=True, ceil_mode=True,
...@@ -14,7 +15,7 @@ model = dict( ...@@ -14,7 +15,7 @@ model = dict(
neck=None, neck=None,
bbox_head=dict( bbox_head=dict(
type='SSDHead', type='SSDHead',
input_size=300, input_size=input_size,
in_channels=(512, 1024, 512, 256, 256, 256), in_channels=(512, 1024, 512, 256, 256, 256),
num_classes=21, num_classes=21,
anchor_strides=(8, 16, 32, 64, 100, 300), anchor_strides=(8, 16, 32, 64, 100, 300),
...@@ -50,6 +51,7 @@ data = dict( ...@@ -50,6 +51,7 @@ data = dict(
workers_per_gpu=3, workers_per_gpu=3,
train=dict( train=dict(
type='RepeatDataset', type='RepeatDataset',
times=20,
dataset=dict( dataset=dict(
type=dataset_type, type=dataset_type,
ann_file=[ ann_file=[
...@@ -77,8 +79,7 @@ data = dict( ...@@ -77,8 +79,7 @@ data = dict(
ratio_range=(1, 4)), ratio_range=(1, 4)),
random_crop=dict( random_crop=dict(
min_ious=(0.1, 0.3, 0.5, 0.7, 0.9), min_crop_size=0.3)), min_ious=(0.1, 0.3, 0.5, 0.7, 0.9), min_crop_size=0.3)),
resize_keep_ratio=False), resize_keep_ratio=False)),
times=20),
val=dict( val=dict(
type=dataset_type, type=dataset_type,
ann_file=data_root + 'VOC2007/ImageSets/Main/test.txt', ann_file=data_root + 'VOC2007/ImageSets/Main/test.txt',
......
configs/ssd512_voc.py → configs/pascal_voc/ssd512_voc.py
View file @ b320d0ab
# model settings # model settings
input_size = 512
model = dict( model = dict(
type='SingleStageDetector', type='SingleStageDetector',
pretrained='data/vgg_backbone.pth', pretrained='data/vgg_backbone.pth',
backbone=dict( backbone=dict(
type='SSDVGG', type='SSDVGG',
input_size=512, input_size=input_size,
depth=16, depth=16,
with_last_pool=False, with_last_pool=False,
ceil_mode=True, ceil_mode=True,
...@@ -14,7 +15,7 @@ model = dict( ...@@ -14,7 +15,7 @@ model = dict(
neck=None, neck=None,
bbox_head=dict( bbox_head=dict(
type='SSDHead', type='SSDHead',
input_size=512, input_size=input_size,
in_channels=(512, 1024, 512, 256, 256, 256, 256), in_channels=(512, 1024, 512, 256, 256, 256, 256),
num_classes=81, num_classes=81,
anchor_strides=(8, 16, 32, 64, 128, 256, 512), anchor_strides=(8, 16, 32, 64, 128, 256, 512),
...@@ -42,18 +43,22 @@ test_cfg = dict( ...@@ -42,18 +43,22 @@ test_cfg = dict(
max_per_img=200) max_per_img=200)
# model training and testing settings # model training and testing settings
# dataset settings # dataset settings
dataset_type = 'CocoDataset' dataset_type = 'VOCDataset'
data_root = 'data/coco/' data_root = 'data/VOCdevkit/'
img_norm_cfg = dict(mean=[123.675, 116.28, 103.53], std=[1, 1, 1], to_rgb=True) img_norm_cfg = dict(mean=[123.675, 116.28, 103.53], std=[1, 1, 1], to_rgb=True)
data = dict( data = dict(
imgs_per_gpu=8, imgs_per_gpu=8,
workers_per_gpu=3, workers_per_gpu=3,
train=dict( train=dict(
type='RepeatDataset', type='RepeatDataset',
times=20,
dataset=dict( dataset=dict(
type=dataset_type, type=dataset_type,
ann_file=data_root + 'annotations/instances_train2017.json', ann_file=[
img_prefix=data_root + 'train2017/', data_root + 'VOC2007/ImageSets/Main/trainval.txt',
data_root + 'VOC2012/ImageSets/Main/trainval.txt'
],
img_prefix=[data_root + 'VOC2007/', data_root + 'VOC2012/'],
img_scale=(512, 512), img_scale=(512, 512),
img_norm_cfg=img_norm_cfg, img_norm_cfg=img_norm_cfg,
size_divisor=None, size_divisor=None,
...@@ -74,12 +79,11 @@ data = dict( ...@@ -74,12 +79,11 @@ data = dict(
ratio_range=(1, 4)), ratio_range=(1, 4)),
random_crop=dict( random_crop=dict(
min_ious=(0.1, 0.3, 0.5, 0.7, 0.9), min_crop_size=0.3)), min_ious=(0.1, 0.3, 0.5, 0.7, 0.9), min_crop_size=0.3)),
resize_keep_ratio=False), resize_keep_ratio=False)),
times=10),
val=dict( val=dict(
type=dataset_type, type=dataset_type,
ann_file=data_root + 'annotations/instances_val2017.json', ann_file=data_root + 'VOC2007/ImageSets/Main/test.txt',
img_prefix=data_root + 'val2017/', img_prefix=data_root + 'VOC2007/',
img_scale=(512, 512), img_scale=(512, 512),
img_norm_cfg=img_norm_cfg, img_norm_cfg=img_norm_cfg,
size_divisor=None, size_divisor=None,
...@@ -90,8 +94,8 @@ data = dict( ...@@ -90,8 +94,8 @@ data = dict(
resize_keep_ratio=False), resize_keep_ratio=False),
test=dict( test=dict(
type=dataset_type, type=dataset_type,
ann_file=data_root + 'annotations/instances_val2017.json', ann_file=data_root + 'VOC2007/ImageSets/Main/test.txt',
img_prefix=data_root + 'val2017/', img_prefix=data_root + 'VOC2007/',
img_scale=(512, 512), img_scale=(512, 512),
img_norm_cfg=img_norm_cfg, img_norm_cfg=img_norm_cfg,
size_divisor=None, size_divisor=None,
......
configs/ssd300_coco.py
View file @ b320d0ab
# model settings # model settings
input_size = 300
model = dict( model = dict(
type='SingleStageDetector', type='SingleStageDetector',
pretrained='data/vgg_backbone.pth', pretrained='data/vgg_backbone.pth',
backbone=dict( backbone=dict(
type='SSDVGG', type='SSDVGG',
input_size=300, input_size=input_size,
depth=16, depth=16,
with_last_pool=False, with_last_pool=False,
ceil_mode=True, ceil_mode=True,
...@@ -14,7 +15,7 @@ model = dict( ...@@ -14,7 +15,7 @@ model = dict(
neck=None, neck=None,
bbox_head=dict( bbox_head=dict(
type='SSDHead', type='SSDHead',
input_size=300, input_size=input_size,
in_channels=(512, 1024, 512, 256, 256, 256), in_channels=(512, 1024, 512, 256, 256, 256),
num_classes=81, num_classes=81,
anchor_strides=(8, 16, 32, 64, 100, 300), anchor_strides=(8, 16, 32, 64, 100, 300),
...@@ -50,6 +51,7 @@ data = dict( ...@@ -50,6 +51,7 @@ data = dict(
workers_per_gpu=3, workers_per_gpu=3,
train=dict( train=dict(
type='RepeatDataset', type='RepeatDataset',
times=10,
dataset=dict( dataset=dict(
type=dataset_type, type=dataset_type,
ann_file=data_root + 'annotations/instances_train2017.json', ann_file=data_root + 'annotations/instances_train2017.json',
...@@ -74,8 +76,7 @@ data = dict( ...@@ -74,8 +76,7 @@ data = dict(
ratio_range=(1, 4)), ratio_range=(1, 4)),
random_crop=dict( random_crop=dict(
min_ious=(0.1, 0.3, 0.5, 0.7, 0.9), min_crop_size=0.3)), min_ious=(0.1, 0.3, 0.5, 0.7, 0.9), min_crop_size=0.3)),
resize_keep_ratio=False), resize_keep_ratio=False)),
times=10),
val=dict( val=dict(
type=dataset_type, type=dataset_type,
ann_file=data_root + 'annotations/instances_val2017.json', ann_file=data_root + 'annotations/instances_val2017.json',
......
configs/ssd512_coco.py
View file @ b320d0ab
# model settings # model settings
input_size = 512
model = dict( model = dict(
type='SingleStageDetector', type='SingleStageDetector',
pretrained='data/vgg_backbone.pth', pretrained='data/vgg_backbone.pth',
backbone=dict( backbone=dict(
type='SSDVGG', type='SSDVGG',
input_size=512, input_size=input_size,
depth=16, depth=16,
with_last_pool=False, with_last_pool=False,
ceil_mode=True, ceil_mode=True,
...@@ -14,7 +15,7 @@ model = dict( ...@@ -14,7 +15,7 @@ model = dict(
neck=None, neck=None,
bbox_head=dict( bbox_head=dict(
type='SSDHead', type='SSDHead',
input_size=512, input_size=input_size,
in_channels=(512, 1024, 512, 256, 256, 256, 256), in_channels=(512, 1024, 512, 256, 256, 256, 256),
num_classes=81, num_classes=81,
anchor_strides=(8, 16, 32, 64, 128, 256, 512), anchor_strides=(8, 16, 32, 64, 128, 256, 512),
...@@ -50,6 +51,7 @@ data = dict( ...@@ -50,6 +51,7 @@ data = dict(
workers_per_gpu=3, workers_per_gpu=3,
train=dict( train=dict(
type='RepeatDataset', type='RepeatDataset',
times=10,
dataset=dict( dataset=dict(
type=dataset_type, type=dataset_type,
ann_file=data_root + 'annotations/instances_train2017.json', ann_file=data_root + 'annotations/instances_train2017.json',
...@@ -74,8 +76,7 @@ data = dict( ...@@ -74,8 +76,7 @@ data = dict(
ratio_range=(1, 4)), ratio_range=(1, 4)),
random_crop=dict( random_crop=dict(
min_ious=(0.1, 0.3, 0.5, 0.7, 0.9), min_crop_size=0.3)), min_ious=(0.1, 0.3, 0.5, 0.7, 0.9), min_crop_size=0.3)),
resize_keep_ratio=False), resize_keep_ratio=False)),
times=10),
val=dict( val=dict(
type=dataset_type, type=dataset_type,
ann_file=data_root + 'annotations/instances_val2017.json', ann_file=data_root + 'annotations/instances_val2017.json',
......
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