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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.") |