gaborcselle
commited on
Commit
·
306ced6
1
Parent(s):
56062ea
Added details to README.md
Browse files
README.md
CHANGED
@@ -1,10 +1,10 @@
|
|
1 |
---
|
2 |
-
license:
|
3 |
base_model: microsoft/resnet-18
|
4 |
tags:
|
5 |
- generated_from_trainer
|
6 |
datasets:
|
7 |
-
-
|
8 |
metrics:
|
9 |
- accuracy
|
10 |
model-index:
|
@@ -23,10 +23,61 @@ model-index:
|
|
23 |
- name: Accuracy
|
24 |
type: accuracy
|
25 |
value: 0.963265306122449
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
26 |
---
|
27 |
|
28 |
-
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
29 |
-
should probably proofread and complete it, then remove this comment. -->
|
30 |
|
31 |
# font-identifier
|
32 |
|
@@ -37,15 +88,21 @@ It achieves the following results on the evaluation set:
|
|
37 |
|
38 |
## Model description
|
39 |
|
40 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
41 |
|
42 |
## Intended uses & limitations
|
43 |
|
44 |
-
|
45 |
|
46 |
## Training and evaluation data
|
47 |
|
48 |
-
|
49 |
|
50 |
## Training procedure
|
51 |
|
@@ -123,4 +180,4 @@ The following hyperparameters were used during training:
|
|
123 |
- Transformers 4.36.0.dev0
|
124 |
- Pytorch 2.0.0
|
125 |
- Datasets 2.12.0
|
126 |
-
- Tokenizers 0.14.1
|
|
|
1 |
---
|
2 |
+
license: mit
|
3 |
base_model: microsoft/resnet-18
|
4 |
tags:
|
5 |
- generated_from_trainer
|
6 |
datasets:
|
7 |
+
- gaborcselle/font-examples
|
8 |
metrics:
|
9 |
- accuracy
|
10 |
model-index:
|
|
|
23 |
- name: Accuracy
|
24 |
type: accuracy
|
25 |
value: 0.963265306122449
|
26 |
+
widget:
|
27 |
+
- text: What font is this?
|
28 |
+
- src: >-
|
29 |
+
https://huggingface.co/gaborcselle/font-identifier/resolve/main/hf_samples/ArchitectsDaughter-Regular_1.png
|
30 |
+
example_title: Architects Daughter
|
31 |
+
- src: >-
|
32 |
+
https://huggingface.co/gaborcselle/font-identifier/resolve/main/hf_samples/Arial%20Bold_39.png
|
33 |
+
example_title: Arial Bold
|
34 |
+
- src: >-
|
35 |
+
https://huggingface.co/gaborcselle/font-identifier/resolve/main/hf_samples/Courier_28.png
|
36 |
+
example_title: Courier
|
37 |
+
- src: >-
|
38 |
+
https://huggingface.co/gaborcselle/font-identifier/resolve/main/hf_samples/Helvetica_3.png
|
39 |
+
example_title: Helvetica
|
40 |
+
- src: >-
|
41 |
+
https://huggingface.co/gaborcselle/font-identifier/resolve/main/hf_samples/IBMPlexSans-Regular_25.png
|
42 |
+
example_title: IBM Plex Sans
|
43 |
+
- src: >-
|
44 |
+
https://huggingface.co/gaborcselle/font-identifier/resolve/main/hf_samples/Inter-Regular_43.png
|
45 |
+
example_title: Inter
|
46 |
+
- src: >-
|
47 |
+
https://huggingface.co/gaborcselle/font-identifier/resolve/main/hf_samples/Lobster-Regular_25.png
|
48 |
+
example_title: Lobster
|
49 |
+
- src: >-
|
50 |
+
https://huggingface.co/gaborcselle/font-identifier/resolve/main/hf_samples/Merriweather-Regular_1.png
|
51 |
+
example_title: Merriweather
|
52 |
+
- src: >-
|
53 |
+
https://huggingface.co/gaborcselle/font-identifier/resolve/main/hf_samples/Poppins-Regular_22.png
|
54 |
+
example_title: Poppins
|
55 |
+
- src: >-
|
56 |
+
https://huggingface.co/gaborcselle/font-identifier/resolve/main/hf_samples/RobotoMono-Regular_38.png
|
57 |
+
example_title: Roboto Mono
|
58 |
+
- src: >-
|
59 |
+
https://huggingface.co/gaborcselle/font-identifier/resolve/main/hf_samples/Times_New_Roman_Bold
|
60 |
+
Italic_26.png
|
61 |
+
example_title: Times New Roman Bold Italic
|
62 |
+
- src: >-
|
63 |
+
https://huggingface.co/gaborcselle/font-identifier/resolve/main/hf_samples/Times_New_Roman_Italic_16.png
|
64 |
+
example_title: Times New Roman Italic
|
65 |
+
- src: >-
|
66 |
+
https://huggingface.co/gaborcselle/font-identifier/resolve/main/hf_samples/TitilliumWeb-Regular_5.png
|
67 |
+
example_title: Titillium Web
|
68 |
+
- src: >-
|
69 |
+
https://huggingface.co/gaborcselle/font-identifier/resolve/main/hf_samples/Trebuchet_MS_Italic_47.png
|
70 |
+
example_title: Trebuchet MS Italic
|
71 |
+
- src: >-
|
72 |
+
https://huggingface.co/gaborcselle/font-identifier/resolve/main/hf_samples/Trebuchet_MS_11.png
|
73 |
+
example_title: Trebuchet MS
|
74 |
+
- src: >-
|
75 |
+
https://huggingface.co/gaborcselle/font-identifier/resolve/main/hf_samples/Verdana_Bold_43.png
|
76 |
+
example_title: Verdana Bold
|
77 |
+
language:
|
78 |
+
- en
|
79 |
---
|
80 |
|
|
|
|
|
81 |
|
82 |
# font-identifier
|
83 |
|
|
|
88 |
|
89 |
## Model description
|
90 |
|
91 |
+
Identify the font used in an image. Visual classifier based on ResNet18.
|
92 |
+
|
93 |
+
I built this project in 1 day, with a minute-by-minute journal:
|
94 |
+
* [On Twitter/X](https://twitter.com/gabor/status/1722300841691103467)
|
95 |
+
* [On Pebble.social](https://pebble.social/@gabor/111376050835874755)
|
96 |
+
* [On Threads.net](https://www.threads.net/@gaborcselle/post/CzZJpJCpxTz)
|
97 |
+
|
98 |
|
99 |
## Intended uses & limitations
|
100 |
|
101 |
+
Identify any of 48 standard fonts from the training data.
|
102 |
|
103 |
## Training and evaluation data
|
104 |
|
105 |
+
Trained and eval'd on the [gaborcselle/font-examples](https://huggingface.co/datasets/gaborcselle/font-examples) dataset (80/20 split).
|
106 |
|
107 |
## Training procedure
|
108 |
|
|
|
180 |
- Transformers 4.36.0.dev0
|
181 |
- Pytorch 2.0.0
|
182 |
- Datasets 2.12.0
|
183 |
+
- Tokenizers 0.14.1
|