Flowchart Generation and Mind Map Creation using Extracted Summarized Text

The technology discussed in this research study aims to transform text into a variety of visual representations, including mind maps, flowcharts, and summaries. The research underlines the usefulness of graphical representations and summaries for greater retention, starting with the challenges of remembering and digesting information from numerous sources. The project uses machine learning and deep learning algorithms to extract text from user-provided images or PDFs and transform it into mind maps or flowcharts based on user preferences. The capability of this research spans both the business and academic areas, allowing for the concise summarization of lengthy, complex documents. An overview of the literature on text extraction, summarization, and conversion techniques is given in the article. These techniques covered include OCR, network text analysis, deep learning-based summarization, keyword extraction, and data flow diagrams. The suggested method involves extracting text using OCR, summarising text using the T5 transformer model, creating flowcharts based on phrase relationships, and creating mind maps using NLTK and NetworkX modules. The conclusion of the study discusses the advantages and implementation specifics of each technique. The project offers a powerful way for converting text into visual representations in both academic and professional contexts, encouraging better comprehension, information retention, and improved learning and problem-solving skills.