| 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.") |