Show HN: Course on Building Full-Stack Chrome Extensions with React and Node.js https://ift.tt/3mpteN4

Show HN: Course on Building Full-Stack Chrome Extensions with React and Node.js I've been working in the extension space on a variety of products for a number of years now and decided to put together a course on how everything I wish I knew when I first started out. It goes through building an entire "product", meaning UI, API, and extension, all communicating with each other. It covers a lot of topics I get asked about often as well such as extension-level authentication, injecting React apps into web pages via content scripts, and a bunch more. https://ift.tt/BqR6KhH February 22, 2025 at 11:28PM

Show HN: Willpayforthis.com – Ideas people will pay for https://ift.tt/R93K4Nr

Show HN: Willpayforthis.com – Ideas people will pay for Ah, there's a dumb easy hack to figure out what ideas people will pay for. Search "I'd pay for" on Twitter and you'll find hundreds of posts from people talking about pain points and products they'd pay for to solve them. Do this enough and you realize you have to filter through a lot of slop. slop. slop. I created willpayforthis.com to accumulate high signal, high quality posts and save you some time. I love thoughts from the community on how I can make it better, save you time, and help you work on the best ideas. https://ift.tt/7kGUR9P February 23, 2025 at 12:21AM

Show HN: Slime OS – An open-source app launcher for RP2040 based devices https://ift.tt/JUvskxO

Show HN: Slime OS – An open-source app launcher for RP2040 based devices https://ift.tt/L8pt5Q0 February 22, 2025 at 01:52AM

Show HN: Rhiza – easily create shortcuts and add entries to PATH https://ift.tt/dyY5r7X

Show HN: Rhiza – easily create shortcuts and add entries to PATH Rhiza is a Windows-only tool that makes any app easily launchable from both the command line and the Windows Start Menu. It works by creating shortcuts and adding entries to the PATH. Key Features: * Crawl ~ common directories to detect apps and games automatically * Add ~ any app by searching for it across the entire file system * Path ~ search for an executable and add its directory into PATH Rhiza simplifies app launching / calling tools by finding and managing them for you. https://ift.tt/4hwDJVI February 22, 2025 at 01:03AM

Show HN: DSBG – A Static Site Generator That Fast-Tracks Your Digital Presence https://ift.tt/2VhBmbY

Show HN: DSBG – A Static Site Generator That Fast-Tracks Your Digital Presence The ethos behind it is to automate your digital presence as much as possible, while retaining control over the created content. To that end, the following features are available: Easy installation; Support for Markdown & HTML source files; Automatic tag generation from paths ; built-in tag filtering; Client-side fuzzy search over all content; Automatic RSS feed generation; Watch mode with automatic rebuild for continuous feedback; 3 different themes, with the ability to add your own via custom CSS; Automatic share buttons for major social networks; Easy to extend with analytics, comments, and more. https://ift.tt/mwrfkBI February 22, 2025 at 12:09AM

Show HN: Agriquery – helping people sell their food https://ift.tt/wEqHNi0

Show HN: Agriquery – helping people sell their food We built Agriquery, a simple online marketplace designed to help farmers and small producers sell their produce directly to consumers (and businesses). Think Etsy, but for food. https://agriquery.com February 18, 2025 at 07:07PM

Show HN: Benchmarking VLMs vs. Traditional OCR https://ift.tt/daxherc

Show HN: Benchmarking VLMs vs. Traditional OCR Vision models have been gaining popularity as a replacement for traditional OCR. Especially with Gemini 2.0 becoming cost competitive with the cloud platforms. We've been continuously evaluating different models since we released the Zerox package last year ( https://ift.tt/5VIPSdG ). And we wanted to put some numbers behind it. So we’re open sourcing our internal OCR benchmark + evaluation datasets. Full writeup + data explorer here: https://ift.tt/U9sxq40 Github: https://ift.tt/jmMLbsi Huggingface: https://ift.tt/vuzDAZ1 Couple notes on the methodology: 1. We are using JSON accuracy as our primary metric. The end goal is to evaluate how well each OCR provider can prepare the data for LLM ingestion. 2. This methodology differs from a lot of OCR benchmarks, because it doesn't rely on text similarity. We believe text similarity measurements are heavily biased towards the exact layout of the ground truth text, and penalize correct OCR that has slight layout differences. 3. Every document goes Image => OCR => Predicted JSON. And we compare the predicted JSON against the annotated ground truth JSON. The VLMs are capable of Image => JSON directly, we are primarily trying to measure OCR accuracy here. Planning to release a separate report on direct JSON accuracy next week. This is a continuous work in progress! There are at least 10 additional providers we plan to add to the list. The next big roadmap items are: - Comparing OCR vs. direct extraction. Early results here show a slight accuracy improvement, but it’s highly variable on page length. - A multilingual comparison. Right now the evaluation data is english only. - A breakdown of the data by type (best model for handwriting, tables, charts, photos, etc.) https://ift.tt/U9sxq40 February 21, 2025 at 12:19AM