UnPlotter – Extract data from vector PDF plots

Hacker News

I thought you all might be interested in this recent project of mine. Here is a 78 second video demonstrating its use: https://youtu.be/AkR6-IWVgBU UnPlotter is a JS app that will extract the data from vector plots in PDF files. Perhaps you want to compare your method with a published result. Or perhaps you want a MOSFET performance curve from a product data sheet. Over the years, there have been many programs to extract data from raster plots. They typically use image processing / computer vision algorithms to 'follow the red line' -- and then scale the results to recover an approximation of the data. When I have needed to extract data from figures that were available as vector files, I was unwilling to take a screenshot and then use a raster extraction tool. Instead, I would delete all the extraneous data in a vector drawing program (say InkScape or Illustrator). Then I would convert to a text-based vector format (usually EPS, but more recently SVG). Then I would edit the file and reverse engineer the curves from the data. It was painstaking and slow, but it satisfies a certain level of OCD. UnPlotter does all this so you don't have to. The good news -- no image processing / CV algorithms needed to follow lines. Most plotting programs group the curves in a way that they are intrinsic. The accuracy is shocking -- although plotting programs may round their output, PDF stores real numbers as single precision floating point (in pt (1/72 in) in page coordinates) -- so some scaling occurs can introduce some truncation error, but you're effectively recovering the data to single precision (say less than 1e-5 error). Which is a ton better than picking pixels from a 300dpi image. Everything happens in your browser, the loaded PDF file never leaves your computer. No logging, tracking, etc. I'd always wondered why nobody ever made a tool to do this -- so I did. I hope some of you find it interesting and perhaps even useful.

Visit product View on Hacker NewsOct 29, 2025

Share card

Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

83%83% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: computer, new, single · Missing: mac, agents, macos

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: video, way · Missing: mobile apps, ios, personal

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: introduce · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

Relevance AI41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Vector experimentation platform for data scientists

Indie Hackers2ai

C+

C++ virtual_vec vector implementation47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

C++ virtual_vec vector implementation

Hacker News39

C+

C++23 constexpr n-dimensional Euclidean vector56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

C++23 constexpr n-dimensional Euclidean vector

Hacker News1

Extract text from any pdf in the browser61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Extract text from any pdf in the browser

Hacker News12

ChromeScraper – Extract Any Data from Any Website58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

ChromeScraper – Extract Any Data from Any Website

Hacker News5

an API to extract text from a PDF60%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

an API to extract text from a PDF

Hacker News51

SQLite-Vector – Vector search for SQLite, now Apache 2.066%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

SQLite-Vector – Vector search for SQLite, now Apache 2.0

Hacker News2

Datar63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Extract and reconcile data from documents

Product Hunt+9

Vector Video41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Vector Video

Hacker News55

Handinger58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Extract data from the internet

Product Hunt+243API

Browse all products Analyze your launch