Add model, configuration files and description
#1
by
mboillet
- opened
- README.md +54 -0
- line_hugin_munin.pth +3 -0
- parameters.yml +11 -0
README.md
CHANGED
@@ -1,3 +1,57 @@
|
|
1 |
---
|
|
|
2 |
license: mit
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
3 |
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
---
|
2 |
+
library_name: Doc-UFCN
|
3 |
license: mit
|
4 |
+
tags:
|
5 |
+
- Doc-UFCN
|
6 |
+
- PyTorch
|
7 |
+
- Object detection
|
8 |
+
metrics:
|
9 |
+
- IoU
|
10 |
+
- F1
|
11 |
+
- AP@.5
|
12 |
+
- AP@.75
|
13 |
+
- AP@[.5,.95]
|
14 |
---
|
15 |
+
|
16 |
+
|
17 |
+
# Hugin-Munin line detection
|
18 |
+
|
19 |
+
The Hugin-Munin line detection model predicts text lines from Hugin-Munin document images. This model was developed during the [HUGIN-MUNIN project](https://hugin-munin-project.github.io/).
|
20 |
+
|
21 |
+
## Model description
|
22 |
+
|
23 |
+
The model has been trained using the Doc-UFCN library on Hugin-Munin document images.
|
24 |
+
It has been trained on images with their largest dimension equal to 768 pixels, keeping the original aspect ratio.
|
25 |
+
The model predicts two classes: vertical and horizontal text lines.
|
26 |
+
|
27 |
+
## Evaluation results
|
28 |
+
|
29 |
+
The model achieves the following results:
|
30 |
+
|
31 |
+
| set | class | IoU | F1 | AP@[.5] | AP@[.75] | AP@[.5,.95] |
|
32 |
+
| ----- | ---------- | ----- | ----- | ------- | -------- | ----------- |
|
33 |
+
| train | vertical | 88.29 | 89.67 | 71.37 | 33.26 | 36.32 |
|
34 |
+
| | horizontal | 69.81 | 81.35 | 91.73 | 36.62 | 45.67 |
|
35 |
+
| val | vertical | 73.01 | 75.13 | 46.02 | 4.99 | 15.58 |
|
36 |
+
| | horizontal | 61.65 | 75.69 | 87.98 | 11.18 | 31.55 |
|
37 |
+
| test | vertical | 78.62 | 80.03 | 59.93 | 15.90 | 24.11 |
|
38 |
+
| | horizontal | 63.59 | 76.49 | 95.93 | 24.18 | 41.45 |
|
39 |
+
|
40 |
+
## How to use
|
41 |
+
|
42 |
+
Please refer to the Doc-UFCN library page (https://pypi.org/project/doc-ufcn/) to use this model.
|
43 |
+
|
44 |
+
# Cite us!
|
45 |
+
|
46 |
+
```bibtex
|
47 |
+
@inproceedings{boillet2020,
|
48 |
+
author = {Boillet, Mélodie and Kermorvant, Christopher and Paquet, Thierry},
|
49 |
+
title = {{Multiple Document Datasets Pre-training Improves Text Line Detection With
|
50 |
+
Deep Neural Networks}},
|
51 |
+
booktitle = {2020 25th International Conference on Pattern Recognition (ICPR)},
|
52 |
+
year = {2021},
|
53 |
+
month = Jan,
|
54 |
+
pages = {2134-2141},
|
55 |
+
doi = {10.1109/ICPR48806.2021.9412447}
|
56 |
+
}
|
57 |
+
```
|
line_hugin_munin.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:8e6e5e4f272a9b43a98de036c9164fdc522d2780e2e66dd601bde930bb14a950
|
3 |
+
size 49115013
|
parameters.yml
ADDED
@@ -0,0 +1,11 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
version: 0.0.1
|
3 |
+
parameters:
|
4 |
+
mean: [209, 204, 191]
|
5 |
+
std: [51, 51, 50]
|
6 |
+
min_cc: 50
|
7 |
+
classes:
|
8 |
+
- background
|
9 |
+
- text_line_horizontal
|
10 |
+
- text_line_vertical
|
11 |
+
input_size: 768
|