Edit Banana Turns AI‑Generated Pixel Diagrams into Fully Editable PPT and Drawio Files

Edit Banana addresses the common pain of uneditable AI‑generated pixel diagrams by instantly converting them into fully editable Drawio (XML) or PPTX files, preserving text, shapes, and connections, and offering LaTeX extraction and a human‑in‑the‑loop mode for complex icons.

Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
Edit Banana Turns AI‑Generated Pixel Diagrams into Fully Editable PPT and Drawio Files

Problem: Ineditable Pixel Diagrams

In scientific and engineering workflows, AI‑generated images are often delivered as static pixel graphics that cannot be edited. Adjusting formulas, tweaking boxes, or realigning elements requires labor‑intensive manual work because the output lacks a structural representation.

Solution: Edit Banana

Edit Banana does not generate images; it deconstructs them. The tool converts static diagrams into Drawio (XML) or PPTX files, providing true structural recovery.

Key Features

Upload any AI‑generated flowchart or sketch; the system launches a full‑scan mode and reconstructs vector objects within seconds.

Text is transformed into editable text boxes that retain font, size, color, and alignment, supporting multi‑line layout.

Standard shapes (rectangles, cylinders, diamonds) are mapped to PPT/Drawio components with adjustable color, border, and thickness.

Arrows become logical connectors with anchor points, automatically stretching when objects are moved.

Complex mathematical formulas are parsed into LaTeX code, enabling "formula‑level" editing for researchers.

Human‑in‑the‑loop mode allows users to manually select obscure icons; a background‑removal algorithm instantly creates transparent components.

Technical Architecture

The system follows a multimodal agent pipeline: visual perception → structural reasoning → code generation .

Text recognition is rebuilt with a spatial‑style clustering algorithm and a union‑find structure, capturing layout semantics and ensuring consistent styling.

Element detection is reinforced by state‑of‑the‑art models such as SAM3 and RMBG. The team constructed a dedicated scientific flowchart dataset, applied model distillation and manual labeling, and markedly improved boundary and nested‑container detection.

Topology recovery goes beyond box detection; the framework infers relationships by reasoning arrow direction and anchor points, guaranteeing that exported files preserve the original logical structure.

Impact and Outlook

Launched only three weeks ago, Edit Banana amassed 2 K GitHub stars and attracted thousands of developers to contribute. The project demonstrates a shift from mere image generation to editable outputs, making diagram maintainability and iterability the next productivity metric for AIGC workflows.

Edit Banana overview
Edit Banana overview
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multimodal AIOCRAIGCdrawioPPTXdiagram editingEdit Banana
Machine Learning Algorithms & Natural Language Processing
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Machine Learning Algorithms & Natural Language Processing

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