Spaces:
Build error
Build error
napatswift
commited on
Commit
·
49aa0b6
1
Parent(s):
1d4a6c0
Update weights - 40e
Browse files- model/text-det/psenet.pth +2 -2
- model/text-det/psenet.py +2 -163
model/text-det/psenet.pth
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:ae9fd081c8004a7a8a6f3d1bab370637a819b8dcefe0d9c23c54c2d2502339aa
|
3 |
+
size 353251813
|
model/text-det/psenet.py
CHANGED
@@ -29,114 +29,6 @@ model = dict(
|
|
29 |
std=[58.395, 57.12, 57.375],
|
30 |
bgr_to_rgb=True,
|
31 |
pad_size_divisor=32))
|
32 |
-
train_pipeline = [
|
33 |
-
dict(
|
34 |
-
type='LoadImageFromFile',
|
35 |
-
file_client_args=dict(backend='disk'),
|
36 |
-
color_type='color_ignore_orientation'),
|
37 |
-
dict(
|
38 |
-
type='LoadOCRAnnotations',
|
39 |
-
with_polygon=True,
|
40 |
-
with_bbox=True,
|
41 |
-
with_label=True),
|
42 |
-
dict(
|
43 |
-
type='TorchVisionWrapper',
|
44 |
-
op='ColorJitter',
|
45 |
-
brightness=0.12549019607843137,
|
46 |
-
saturation=0.5),
|
47 |
-
dict(type='FixInvalidPolygon'),
|
48 |
-
dict(type='ShortScaleAspectJitter', short_size=736, scale_divisor=32),
|
49 |
-
dict(type='RandomFlip', prob=0.5, direction='horizontal'),
|
50 |
-
dict(type='RandomRotate', max_angle=10),
|
51 |
-
dict(type='TextDetRandomCrop', target_size=(736, 736)),
|
52 |
-
dict(type='Pad', size=(736, 736)),
|
53 |
-
dict(
|
54 |
-
type='PackTextDetInputs',
|
55 |
-
meta_keys=('img_path', 'ori_shape', 'img_shape', 'scale_factor'))
|
56 |
-
]
|
57 |
-
test_pipeline = [
|
58 |
-
dict(
|
59 |
-
type='LoadImageFromFile',
|
60 |
-
file_client_args=dict(backend='disk'),
|
61 |
-
color_type='color_ignore_orientation'),
|
62 |
-
dict(type='Resize', scale=(2240, 2240), keep_ratio=True),
|
63 |
-
dict(
|
64 |
-
type='LoadOCRAnnotations',
|
65 |
-
with_polygon=True,
|
66 |
-
with_bbox=True,
|
67 |
-
with_label=True),
|
68 |
-
dict(
|
69 |
-
type='PackTextDetInputs',
|
70 |
-
meta_keys=('img_path', 'ori_shape', 'img_shape', 'scale_factor'))
|
71 |
-
]
|
72 |
-
thvc_textdet_data_root = 'data/det/vl+vc-textdet'
|
73 |
-
thvc_textdet_train = dict(
|
74 |
-
type='OCRDataset',
|
75 |
-
data_root='data/det/vl+vc-textdet',
|
76 |
-
ann_file='textdet_train.json',
|
77 |
-
data_prefix=dict(img_path='imgs/'),
|
78 |
-
filter_cfg=dict(filter_empty_gt=True, min_size=32),
|
79 |
-
pipeline=[
|
80 |
-
dict(
|
81 |
-
type='LoadImageFromFile',
|
82 |
-
file_client_args=dict(backend='disk'),
|
83 |
-
color_type='color_ignore_orientation'),
|
84 |
-
dict(
|
85 |
-
type='LoadOCRAnnotations',
|
86 |
-
with_polygon=True,
|
87 |
-
with_bbox=True,
|
88 |
-
with_label=True),
|
89 |
-
dict(
|
90 |
-
type='TorchVisionWrapper',
|
91 |
-
op='ColorJitter',
|
92 |
-
brightness=0.12549019607843137,
|
93 |
-
saturation=0.5),
|
94 |
-
dict(type='FixInvalidPolygon'),
|
95 |
-
dict(type='ShortScaleAspectJitter', short_size=736, scale_divisor=32),
|
96 |
-
dict(type='RandomFlip', prob=0.5, direction='horizontal'),
|
97 |
-
dict(type='RandomRotate', max_angle=10),
|
98 |
-
dict(type='TextDetRandomCrop', target_size=(736, 736)),
|
99 |
-
dict(type='Pad', size=(736, 736)),
|
100 |
-
dict(
|
101 |
-
type='PackTextDetInputs',
|
102 |
-
meta_keys=('img_path', 'ori_shape', 'img_shape', 'scale_factor'))
|
103 |
-
])
|
104 |
-
thvc_textdet_test = dict(
|
105 |
-
type='OCRDataset',
|
106 |
-
data_root='data/det/vl+vc-textdet',
|
107 |
-
ann_file='textdet_test.json',
|
108 |
-
data_prefix=dict(img_path='imgs/'),
|
109 |
-
test_mode=True,
|
110 |
-
pipeline=None)
|
111 |
-
thvote_textdet_data_root = 'data/det/textdet-thvote'
|
112 |
-
thvote_textdet_train = dict(
|
113 |
-
type='OCRDataset',
|
114 |
-
data_root='data/det/textdet-thvote',
|
115 |
-
ann_file='textdet_train.json',
|
116 |
-
data_prefix=dict(img_path='imgs/'),
|
117 |
-
filter_cfg=dict(filter_empty_gt=True, min_size=32),
|
118 |
-
pipeline=None)
|
119 |
-
thvote_textdet_test = dict(
|
120 |
-
type='OCRDataset',
|
121 |
-
data_root='data/det/textdet-thvote',
|
122 |
-
ann_file='textdet_test.json',
|
123 |
-
data_prefix=dict(img_path='imgs/'),
|
124 |
-
test_mode=True,
|
125 |
-
pipeline=[
|
126 |
-
dict(
|
127 |
-
type='LoadImageFromFile',
|
128 |
-
file_client_args=dict(backend='disk'),
|
129 |
-
color_type='color_ignore_orientation'),
|
130 |
-
dict(type='Resize', scale=(2240, 2240), keep_ratio=True),
|
131 |
-
dict(
|
132 |
-
type='LoadOCRAnnotations',
|
133 |
-
with_polygon=True,
|
134 |
-
with_bbox=True,
|
135 |
-
with_label=True),
|
136 |
-
dict(
|
137 |
-
type='PackTextDetInputs',
|
138 |
-
meta_keys=('img_path', 'ori_shape', 'img_shape', 'scale_factor'))
|
139 |
-
])
|
140 |
default_scope = 'mmocr'
|
141 |
env_cfg = dict(
|
142 |
cudnn_benchmark=True,
|
@@ -168,65 +60,13 @@ visualizer = dict(
|
|
168 |
type='TextDetLocalVisualizer',
|
169 |
name='visualizer',
|
170 |
vis_backends=[dict(type='LocalVisBackend')])
|
171 |
-
max_epochs =
|
172 |
optim_wrapper = dict(
|
173 |
type='OptimWrapper', optimizer=dict(type='Adam', lr=0.001))
|
174 |
train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=50, val_interval=20)
|
175 |
val_cfg = dict(type='ValLoop')
|
176 |
test_cfg = dict(type='TestLoop')
|
177 |
-
param_scheduler = [dict(type='PolyLR', power=0.9, end=
|
178 |
-
thvotecount_textdet_train = dict(
|
179 |
-
type='OCRDataset',
|
180 |
-
data_root='data/det/vl+vc-textdet',
|
181 |
-
ann_file='textdet_train.json',
|
182 |
-
data_prefix=dict(img_path='imgs/'),
|
183 |
-
filter_cfg=dict(filter_empty_gt=True, min_size=32),
|
184 |
-
pipeline=[
|
185 |
-
dict(
|
186 |
-
type='LoadImageFromFile',
|
187 |
-
file_client_args=dict(backend='disk'),
|
188 |
-
color_type='color_ignore_orientation'),
|
189 |
-
dict(
|
190 |
-
type='LoadOCRAnnotations',
|
191 |
-
with_polygon=True,
|
192 |
-
with_bbox=True,
|
193 |
-
with_label=True),
|
194 |
-
dict(
|
195 |
-
type='TorchVisionWrapper',
|
196 |
-
op='ColorJitter',
|
197 |
-
brightness=0.12549019607843137,
|
198 |
-
saturation=0.5),
|
199 |
-
dict(type='FixInvalidPolygon'),
|
200 |
-
dict(type='ShortScaleAspectJitter', short_size=736, scale_divisor=32),
|
201 |
-
dict(type='RandomFlip', prob=0.5, direction='horizontal'),
|
202 |
-
dict(type='RandomRotate', max_angle=10),
|
203 |
-
dict(type='TextDetRandomCrop', target_size=(736, 736)),
|
204 |
-
dict(type='Pad', size=(736, 736)),
|
205 |
-
dict(
|
206 |
-
type='PackTextDetInputs',
|
207 |
-
meta_keys=('img_path', 'ori_shape', 'img_shape', 'scale_factor'))
|
208 |
-
])
|
209 |
-
thvotecount_textdet_test = dict(
|
210 |
-
type='OCRDataset',
|
211 |
-
data_root='data/det/textdet-thvote',
|
212 |
-
ann_file='textdet_test.json',
|
213 |
-
data_prefix=dict(img_path='imgs/'),
|
214 |
-
test_mode=True,
|
215 |
-
pipeline=[
|
216 |
-
dict(
|
217 |
-
type='LoadImageFromFile',
|
218 |
-
file_client_args=dict(backend='disk'),
|
219 |
-
color_type='color_ignore_orientation'),
|
220 |
-
dict(type='Resize', scale=(2240, 2240), keep_ratio=True),
|
221 |
-
dict(
|
222 |
-
type='LoadOCRAnnotations',
|
223 |
-
with_polygon=True,
|
224 |
-
with_bbox=True,
|
225 |
-
with_label=True),
|
226 |
-
dict(
|
227 |
-
type='PackTextDetInputs',
|
228 |
-
meta_keys=('img_path', 'ori_shape', 'img_shape', 'scale_factor'))
|
229 |
-
])
|
230 |
train_dataloader = dict(
|
231 |
batch_size=10,
|
232 |
num_workers=16,
|
@@ -258,7 +98,6 @@ train_dataloader = dict(
|
|
258 |
type='ShortScaleAspectJitter',
|
259 |
short_size=736,
|
260 |
scale_divisor=32),
|
261 |
-
dict(type='RandomFlip', prob=0.5, direction='horizontal'),
|
262 |
dict(type='RandomRotate', max_angle=10),
|
263 |
dict(type='TextDetRandomCrop', target_size=(736, 736)),
|
264 |
dict(type='Pad', size=(736, 736)),
|
|
|
29 |
std=[58.395, 57.12, 57.375],
|
30 |
bgr_to_rgb=True,
|
31 |
pad_size_divisor=32))
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
32 |
default_scope = 'mmocr'
|
33 |
env_cfg = dict(
|
34 |
cudnn_benchmark=True,
|
|
|
60 |
type='TextDetLocalVisualizer',
|
61 |
name='visualizer',
|
62 |
vis_backends=[dict(type='LocalVisBackend')])
|
63 |
+
max_epochs = 50
|
64 |
optim_wrapper = dict(
|
65 |
type='OptimWrapper', optimizer=dict(type='Adam', lr=0.001))
|
66 |
train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=50, val_interval=20)
|
67 |
val_cfg = dict(type='ValLoop')
|
68 |
test_cfg = dict(type='TestLoop')
|
69 |
+
param_scheduler = [dict(type='PolyLR', power=0.9, end=50)]
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
70 |
train_dataloader = dict(
|
71 |
batch_size=10,
|
72 |
num_workers=16,
|
|
|
98 |
type='ShortScaleAspectJitter',
|
99 |
short_size=736,
|
100 |
scale_divisor=32),
|
|
|
101 |
dict(type='RandomRotate', max_angle=10),
|
102 |
dict(type='TextDetRandomCrop', target_size=(736, 736)),
|
103 |
dict(type='Pad', size=(736, 736)),
|