File size: 1,842 Bytes
ca7fcaf |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 |
import streamlit as st
def app():
st.title("OCR solutions comparator")
st.write("")
st.write("")
st.write("")
st.markdown("##### This app allows you to compare, from a given picture, the results of different solutions:")
st.markdown("##### *EasyOcr, PaddleOCR, MMOCR, Tesseract*")
st.write("")
st.write("")
st.markdown(''' The 1st step is to choose the language for the text recognition (not all solutions \
support the same languages), and then choose the picture to consider. It is possible to upload a file, \
to take a picture, or to use a demo file. \
It is then possible to change the default values for the text area detection process, \
before launching the detection task for each solution.''')
st.write("")
st.markdown(''' The different results are then presented. The 2nd step is to choose one of these \
detection results, in order to carry out the text recognition process there. It is also possible to change \
the default settings for each solution.''')
st.write("")
st.markdown("###### The recognition results appear in 2 formats:")
st.markdown(''' - a visual format resumes the initial image, replacing the detected areas with \
the recognized text. The background is + or - strongly colored in green according to the \
confidence level of the recognition.
A slider allows you to change the font size, another \
allows you to modify the confidence threshold above which the text color changes: if it is at \
70% for example, then all the texts with a confidence threshold higher or equal to 70 will appear \
in white, in black otherwise.''')
st.markdown(" - a detailed format presents the results in a table, for each text box detected. \
It is possible to download this results in a local csv file.") |