Spaces:
Running
on
T4
Running
on
T4
Update app.py
Browse files
app.py
CHANGED
@@ -85,9 +85,12 @@ with gr.Blocks(theme=gr.themes.Monochrome(), title="Multicentury HTR Demo") as d
|
|
85 |
gr.Markdown("# Multicentury HTR Demo")
|
86 |
gr.Markdown("""The HTR pipeline contains three components: text region detection, textline detection and handwritten text recognition.
|
87 |
The components run machine learning models that have been trained at the National Archives of Finland using mostly handwritten documents
|
88 |
-
from 17th, 18th, 19th and 20th centuries.
|
|
|
89 |
Input image can be uploaded using the *Input image* window in the *Text content* tab, and the predicted text content will appear to the window
|
90 |
-
on the right side of the image. Results of text region and text line detection can be viewed in the *Text regions* and *Text lines* tabs.
|
|
|
|
|
91 |
with gr.Tab("Text content"):
|
92 |
with gr.Row():
|
93 |
input_img = gr.Image(label="Input image", type="pil")
|
|
|
85 |
gr.Markdown("# Multicentury HTR Demo")
|
86 |
gr.Markdown("""The HTR pipeline contains three components: text region detection, textline detection and handwritten text recognition.
|
87 |
The components run machine learning models that have been trained at the National Archives of Finland using mostly handwritten documents
|
88 |
+
from 17th, 18th, 19th and 20th centuries.
|
89 |
+
|
90 |
Input image can be uploaded using the *Input image* window in the *Text content* tab, and the predicted text content will appear to the window
|
91 |
+
on the right side of the image. Results of text region and text line detection can be viewed in the *Text regions* and *Text lines* tabs.
|
92 |
+
Best results are obtained when using high quality scans of documents with a regular layout.""")
|
93 |
+
|
94 |
with gr.Tab("Text content"):
|
95 |
with gr.Row():
|
96 |
input_img = gr.Image(label="Input image", type="pil")
|