Show HN: Pickcode – Free online code editor for kids
15 by csmeyer | 2 comments on Hacker News.
Hi HN! I've posted Pickcode a few times (most recently https://ift.tt/3syBNDi ), but we've improved things quite a bit so I thought it was worth posting again. This is a bit of 1.0 release after a long year of working on the company full time! Pickcode is basically Replit-lite, for kids. The editor is simple: text editor + output console + big green button to run your code. We support Python, HTML/CSS/JS, Java, and our block/text hybrid language, Pickcode VL. We're partners on code.org's Hour of Code, and hundreds of thousands of students have tried our free stuff through them. An account for individual kids is totally free, and we offer some free Python and Pickcode VL lessons to get them started. We make money by selling licenses to schools for better customer support and roster/lesson management features. You can use this demo account I made to try out the editor: email: demo@student.pickcode.io pw: Demo1234 (Don't clobber other people's work, and what you put in the demo account is public so be nice)
Sunday, 30 June 2024
Saturday, 29 June 2024
Several Haitian migrants found at exclusive Florida Keys gated community, feds say
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Friday, 28 June 2024
Thursday, 27 June 2024
Wednesday, 26 June 2024
Tuesday, 25 June 2024
New top story on Hacker News: Show HN: Glasskube – Open Source Kubernetes Package Manager, alternative to Helm
Show HN: Glasskube – Open Source Kubernetes Package Manager, alternative to Helm
6 by pmig | 0 comments on Hacker News.
Hello HN, we're Philip and Louis from Glasskube ( https://ift.tt/YLp4Cia ). We're working on an open-source package manager for Kubernetes. It's an alternative to tools like Helm or Kustomize, primarily focused on making deploying, updating, and configuring Kubernetes packages simpler and a lot faster. Here is a demo video ( https://www.youtube.com/watch?v=aIeTHGWsG2c#t=17s ) with quick start instructions. Most developers working with Kubernetes use Helm, an open-source tool created during a hackathon nine years ago. However, with the rapid growth of Kubernetes packages to over 800 packages on the CNCF landscape today, the prerequisites have changed, and we believe it’s time for a new package manager. Every engineer we talked to has a love-hate relationship with Helm, and we also found ourselves defaulting to Helm despite its shortcomings due to a lack of alternatives. We have spent enough time trying to get Helm to do what we need. From looking for the correct chart, trying to learn how each value affects the components and hand-crafting a schemaless values.yaml file, to debugging the final release if it inevitably fails to install, the experience of using Helm is, for the most part, time consuming and cumbersome. Charts often become more complex, requiring the use of sub-charts. These umbrella charts tend to be even harder to maintain and upgrade, because so many different components are bundled into a single release. We talked to over 100 developers and found that everyone developed their own little workarounds, with some working better than others. We collected the feedback poured everything we learned from that into a new package manager. We want to build something that is as easy to use as Homebrew or npm and make package management on Kubernetes as easy as on every other platform. Some of the features Glasskube already supports are Typesafe package configuration via UI or interactive CLI to inject values from other packages, ConfigMaps, and Secrets. Browse our central package repository so there is no need to look for a Helm repository to find a specific package. All packages are dependency-aware so they can be used and referenced by multiple other packages even across namespaces. We validate the complete dependency tree - So packages get installed in the correct namespace. Preview and perform pending updates to your desired version with a single click of a button. All updates have been tested in the Glasskube test suite before being available in the public repository. Use multiple repositories and publish your own private packages (e.g., your company's internal services packages, so all developers will have the up-to-date and easily configured internal services). All features are available via UI or interactive CLI. You can also manage all packages via GitOps. Currently, we are focused on enhancing the user experience, aiming to save engineers as much time as possible. We are still using Helm and Manifests under the hood. However, together with the community, we plan to develop an entirely new packaging and bundling format for all cloud-native packages. This will provide package developers with a straightforward way to define how to install and configure packages, offer simple upgrade paths, and enable us to provide feedback, crash reports, and analytics to every developer working on Kubernetes packages. We also started working on a cloud version. You can pre-signup here in case you are interested: https://glasskube.cloud We'd greatly appreciate any feedback you have and hope you get the chance to try out Glasskube.
6 by pmig | 0 comments on Hacker News.
Hello HN, we're Philip and Louis from Glasskube ( https://ift.tt/YLp4Cia ). We're working on an open-source package manager for Kubernetes. It's an alternative to tools like Helm or Kustomize, primarily focused on making deploying, updating, and configuring Kubernetes packages simpler and a lot faster. Here is a demo video ( https://www.youtube.com/watch?v=aIeTHGWsG2c#t=17s ) with quick start instructions. Most developers working with Kubernetes use Helm, an open-source tool created during a hackathon nine years ago. However, with the rapid growth of Kubernetes packages to over 800 packages on the CNCF landscape today, the prerequisites have changed, and we believe it’s time for a new package manager. Every engineer we talked to has a love-hate relationship with Helm, and we also found ourselves defaulting to Helm despite its shortcomings due to a lack of alternatives. We have spent enough time trying to get Helm to do what we need. From looking for the correct chart, trying to learn how each value affects the components and hand-crafting a schemaless values.yaml file, to debugging the final release if it inevitably fails to install, the experience of using Helm is, for the most part, time consuming and cumbersome. Charts often become more complex, requiring the use of sub-charts. These umbrella charts tend to be even harder to maintain and upgrade, because so many different components are bundled into a single release. We talked to over 100 developers and found that everyone developed their own little workarounds, with some working better than others. We collected the feedback poured everything we learned from that into a new package manager. We want to build something that is as easy to use as Homebrew or npm and make package management on Kubernetes as easy as on every other platform. Some of the features Glasskube already supports are Typesafe package configuration via UI or interactive CLI to inject values from other packages, ConfigMaps, and Secrets. Browse our central package repository so there is no need to look for a Helm repository to find a specific package. All packages are dependency-aware so they can be used and referenced by multiple other packages even across namespaces. We validate the complete dependency tree - So packages get installed in the correct namespace. Preview and perform pending updates to your desired version with a single click of a button. All updates have been tested in the Glasskube test suite before being available in the public repository. Use multiple repositories and publish your own private packages (e.g., your company's internal services packages, so all developers will have the up-to-date and easily configured internal services). All features are available via UI or interactive CLI. You can also manage all packages via GitOps. Currently, we are focused on enhancing the user experience, aiming to save engineers as much time as possible. We are still using Helm and Manifests under the hood. However, together with the community, we plan to develop an entirely new packaging and bundling format for all cloud-native packages. This will provide package developers with a straightforward way to define how to install and configure packages, offer simple upgrade paths, and enable us to provide feedback, crash reports, and analytics to every developer working on Kubernetes packages. We also started working on a cloud version. You can pre-signup here in case you are interested: https://glasskube.cloud We'd greatly appreciate any feedback you have and hope you get the chance to try out Glasskube.
Monday, 24 June 2024
Journalist shot by Minneapolis police at George Floyd protest in hospice care
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Sunday, 23 June 2024
Saturday, 22 June 2024
New top story on Hacker News: Ask HN: Advice for Leading a Software Migration?
Ask HN: Advice for Leading a Software Migration?
7 by drekipus | 5 comments on Hacker News.
Hey HN, I'm about to take lead of a decent sized software migration at work. (From V1 of some subsystem, to v2, both in house. We want to deprecated and eventually remove V1 totally) For 8 of our clients, totalling about 16 million customers. I don't have too many details to share, as I don't know what's relevant. But I'm asking if anyone has any advice or recommended reading regarding such? One book that is really inspiring me about it is "how big things get done" by Bent Flyvbjerg and Dan Gardner. In it, there's some key bits of advice such as * Think slow, ask fast, and mitigate long tailed risks. * Compartmentalize and stick to repeated processes. "Build with LEGOs" * Look around at other projects of similar nature. The last point is why I'm here, as I know some of you have been in the game for longer than I have, so feel free to share experiences that you might think is relevant, if you'd like.
7 by drekipus | 5 comments on Hacker News.
Hey HN, I'm about to take lead of a decent sized software migration at work. (From V1 of some subsystem, to v2, both in house. We want to deprecated and eventually remove V1 totally) For 8 of our clients, totalling about 16 million customers. I don't have too many details to share, as I don't know what's relevant. But I'm asking if anyone has any advice or recommended reading regarding such? One book that is really inspiring me about it is "how big things get done" by Bent Flyvbjerg and Dan Gardner. In it, there's some key bits of advice such as * Think slow, ask fast, and mitigate long tailed risks. * Compartmentalize and stick to repeated processes. "Build with LEGOs" * Look around at other projects of similar nature. The last point is why I'm here, as I know some of you have been in the game for longer than I have, so feel free to share experiences that you might think is relevant, if you'd like.
Friday, 21 June 2024
Battery company Anker unveils modular whole-home battery system — here's how it could boost home electrification
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Thursday, 20 June 2024
Wednesday, 19 June 2024
New top story on Hacker News: Show HN: Modular Pi Cam
Show HN: Modular Pi Cam
11 by jcun4128 | 1 comments on Hacker News.
This is the third camera I've designed/made around the raspberry pi parts/ecosystem. The repo has all the STL files, parts list, most wiring diagrams. The first one was the custom Pi Zero HQ cam which was featured on a Hackaday article/podcast. The modular version (aside from being able to swap cameras) mostly has the latest software. Recently I added the ability to process videos in the background (ffmpeg merges wav/mp4 files together). The camera uses crop-zoom-panning for dialing in shots with manual lenses. The menu is created by layering images/text with PIL. Live preview is a little slow as it's SPI based. If anybody is a pro at python I'd appreciate insight on better code. I've mostly just followed a context-based folder layout regarding where everything is. I have not added custom/manual settings yet, it uses auto settings for the most part except for when you use a V3 camera module (which has electronic aperture) then it uses the d-pad to set the focus/diopter value. I have another camera in mind/future build although it's more tailored for videos. Some sample video I've shot. https://www.youtube.com/watch?v=JkjXkQD0j9w Assembly video https://www.youtube.com/watch?v=dXG-MoIw93Q At some point I will rewrite the code for a new general purpose DIY camera software from what I've learned, that'll be an undertaking.
11 by jcun4128 | 1 comments on Hacker News.
This is the third camera I've designed/made around the raspberry pi parts/ecosystem. The repo has all the STL files, parts list, most wiring diagrams. The first one was the custom Pi Zero HQ cam which was featured on a Hackaday article/podcast. The modular version (aside from being able to swap cameras) mostly has the latest software. Recently I added the ability to process videos in the background (ffmpeg merges wav/mp4 files together). The camera uses crop-zoom-panning for dialing in shots with manual lenses. The menu is created by layering images/text with PIL. Live preview is a little slow as it's SPI based. If anybody is a pro at python I'd appreciate insight on better code. I've mostly just followed a context-based folder layout regarding where everything is. I have not added custom/manual settings yet, it uses auto settings for the most part except for when you use a V3 camera module (which has electronic aperture) then it uses the d-pad to set the focus/diopter value. I have another camera in mind/future build although it's more tailored for videos. Some sample video I've shot. https://www.youtube.com/watch?v=JkjXkQD0j9w Assembly video https://www.youtube.com/watch?v=dXG-MoIw93Q At some point I will rewrite the code for a new general purpose DIY camera software from what I've learned, that'll be an undertaking.
Tuesday, 18 June 2024
Reclusive Taliban leader warns Afghans against earning money or gaining 'worldly honor'
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New top story on Hacker News: Show HN: Billard – Generate music from ball collisions in 2D space
Show HN: Billard – Generate music from ball collisions in 2D space
10 by bambax | 0 comments on Hacker News.
Hello HN! Here's Billard. It combines music and physics into a unique creative tool, as I explore various unconventional methods for generating music. Most traditional music composition tools revolve around the idea of a repeatable pattern. Billard is a webapp that never repeats itself. It generates music automatically based on the collisions of balls in a 2D space. Collisions trigger notes (or chords) in a given key. One can add balls or move them (y-position is pitch); the app remembers its state between reloads; or it can be reset with the 'init' button on the top left. Gravity can be adjusted in real time to change the behavior of the balls. It owes a lot of inspiration to Brian Eno and Erik Satie (inventor of musique d'ameublement , or "furniture music"). Some may think the lack of pattern makes it not musical enough -- but this lets it be listened to —and watched— for a while without boredom. The webapp is made using plain JavaScript. (All SVG icons were made 'by hand'.) It uses Tone.js only for triggering piano samples. Beyond piano, it's MIDI-enabled and works well at slow speed with haunting, dark synth sounds. Hope you like it!
10 by bambax | 0 comments on Hacker News.
Hello HN! Here's Billard. It combines music and physics into a unique creative tool, as I explore various unconventional methods for generating music. Most traditional music composition tools revolve around the idea of a repeatable pattern. Billard is a webapp that never repeats itself. It generates music automatically based on the collisions of balls in a 2D space. Collisions trigger notes (or chords) in a given key. One can add balls or move them (y-position is pitch); the app remembers its state between reloads; or it can be reset with the 'init' button on the top left. Gravity can be adjusted in real time to change the behavior of the balls. It owes a lot of inspiration to Brian Eno and Erik Satie (inventor of musique d'ameublement , or "furniture music"). Some may think the lack of pattern makes it not musical enough -- but this lets it be listened to —and watched— for a while without boredom. The webapp is made using plain JavaScript. (All SVG icons were made 'by hand'.) It uses Tone.js only for triggering piano samples. Beyond piano, it's MIDI-enabled and works well at slow speed with haunting, dark synth sounds. Hope you like it!
Monday, 17 June 2024
Sunday, 16 June 2024
Donald Trump Revealed Why He ‘Doesn’t Like to Have His Picture Taken’ Next to His Youngest Son Barron
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Saturday, 15 June 2024
Friday, 14 June 2024
Thursday, 13 June 2024
Wednesday, 12 June 2024
Tuesday, 11 June 2024
iOS 18 is official. Here’s how it’s going to change your iPhone forever
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Monday, 10 June 2024
Sunday, 9 June 2024
New top story on Hacker News: Is KDB a sane choice for a datalake in 2024?
Is KDB a sane choice for a datalake in 2024?
9 by sonthonax | 7 comments on Hacker News.
Pardon the vague question, but KDB is very much institutional knowledge hidden from the outside world. People have built their livelihoods around it and use it as a hammer for all sorts of nails. It's also extremely expensive and written in a language with origins so obtuse that it's progenitor APL needed a custom keyboard laden with mathematical symbols. Within my firm, it's very hard to get an outside perspective, the KDB developers are true believers in KDB, but they they obviously don't want to be professionally replaced. So I'm asking the more forward leaning HN. One nail in my job, is KDB as a data-lake and I'm being driven nuts by it. I write code in Rust that prices options. There's a lot of complex code involved in this, I use a mix of numeric simulations to calculate greeks and somewhat lengthy analytical formulas. The data that I save to KDB is quite raw, I save the market data and derived volatility surfaces, which are themselves complex-ish models needing some carefully unit-tested code to convert in to implied vols. Right now my desk has no proper tooling for backtesting that uses our own data. And I'm constantly being asked to do something about it, and I don't know what to do! I'm 99% sure KDB is the wrong tool for the job, because of three things: - It's not horizontally scalable. A divide and conquer algo on N<{small_number} cores is pointless. - I'm scared to do queries that return a lot of data. It's non trivial to get a day's worth of data. The query will just often freeze, it doesn't even buffer. Even if I'm just trying to fetch what should be a logical partition, the wire format is really inefficient and uncompressed. I feel like I need to engineering work for trivial things. - The main thing is that I need to do complex math to convert my raw data, order-books and vol-surfaces into useful data to backtest. I have no idea how do do any of this in KDB. My firm is primarily a spot desk, and while I respect my colleagues, their answer is: > Other firms are really invested in KDB and use KDB for this, just figure it out. I'm going nuts because I'm under the assumption that these other firms are way larger and have teams of KDB-quants doing the actual research. While we have some quant traders who know a bit of KDB but they work in the spot side with far more simple math. I keep on advocating for some Parquet style data-store with Spark/Dask/Arrow/Polars running on top of it that can be horizontally scaled and most importantly, with Polars, I can write my backtests in Rust and leverage the libraries I've already written. I get shot down with "we use KDB here". I just don't know how I can deliver a maintainable solution to my traders with this current infrastructure. Bizarrely, and this is a financial firm, no one in a team of ~100 devs has ever touched Spark style tech other than me here. What should I do? Are my concerns overblown? Am I misunderstanding the power of KDB?
9 by sonthonax | 7 comments on Hacker News.
Pardon the vague question, but KDB is very much institutional knowledge hidden from the outside world. People have built their livelihoods around it and use it as a hammer for all sorts of nails. It's also extremely expensive and written in a language with origins so obtuse that it's progenitor APL needed a custom keyboard laden with mathematical symbols. Within my firm, it's very hard to get an outside perspective, the KDB developers are true believers in KDB, but they they obviously don't want to be professionally replaced. So I'm asking the more forward leaning HN. One nail in my job, is KDB as a data-lake and I'm being driven nuts by it. I write code in Rust that prices options. There's a lot of complex code involved in this, I use a mix of numeric simulations to calculate greeks and somewhat lengthy analytical formulas. The data that I save to KDB is quite raw, I save the market data and derived volatility surfaces, which are themselves complex-ish models needing some carefully unit-tested code to convert in to implied vols. Right now my desk has no proper tooling for backtesting that uses our own data. And I'm constantly being asked to do something about it, and I don't know what to do! I'm 99% sure KDB is the wrong tool for the job, because of three things: - It's not horizontally scalable. A divide and conquer algo on N<{small_number} cores is pointless. - I'm scared to do queries that return a lot of data. It's non trivial to get a day's worth of data. The query will just often freeze, it doesn't even buffer. Even if I'm just trying to fetch what should be a logical partition, the wire format is really inefficient and uncompressed. I feel like I need to engineering work for trivial things. - The main thing is that I need to do complex math to convert my raw data, order-books and vol-surfaces into useful data to backtest. I have no idea how do do any of this in KDB. My firm is primarily a spot desk, and while I respect my colleagues, their answer is: > Other firms are really invested in KDB and use KDB for this, just figure it out. I'm going nuts because I'm under the assumption that these other firms are way larger and have teams of KDB-quants doing the actual research. While we have some quant traders who know a bit of KDB but they work in the spot side with far more simple math. I keep on advocating for some Parquet style data-store with Spark/Dask/Arrow/Polars running on top of it that can be horizontally scaled and most importantly, with Polars, I can write my backtests in Rust and leverage the libraries I've already written. I get shot down with "we use KDB here". I just don't know how I can deliver a maintainable solution to my traders with this current infrastructure. Bizarrely, and this is a financial firm, no one in a team of ~100 devs has ever touched Spark style tech other than me here. What should I do? Are my concerns overblown? Am I misunderstanding the power of KDB?
Saturday, 8 June 2024
Friday, 7 June 2024
New top story on Hacker News: Ask HN: Machine Learning Engineers, what do you do at work?
Ask HN: Machine Learning Engineers, what do you do at work?
29 by Gooblebrai | 8 comments on Hacker News.
I'm curious about the day-to-day of a Machine Learning engineer. If you work in this field, could you share what your typical tasks and projects look like? What are you working on?
29 by Gooblebrai | 8 comments on Hacker News.
I'm curious about the day-to-day of a Machine Learning engineer. If you work in this field, could you share what your typical tasks and projects look like? What are you working on?
Thursday, 6 June 2024
Wednesday, 5 June 2024
Tuesday, 4 June 2024
New top story on Hacker News: Show HN: Shortbread App – AI-powered, romantic comics for women
Show HN: Shortbread App – AI-powered, romantic comics for women
12 by Fengjiao | 7 comments on Hacker News.
Hi HN! Fengjiao and Evan here. We are building Shortbread App, Netflix for webcomics. We publish guilty-pleasure romance series (think 50 Shades of Gray) as comics. Like the mature version of Webtoon. You can see two comics episodes at https://ift.tt/hTk3o96... https://ift.tt/1Np7Wzk... , and read more in the app via https://ift.tt/AQlh1KX . All comics in the app are made by artists using the Shortbread AI Comics Studio ( https://shortbread.ai ). It is a powerful Photoshop-like editor that speeds up comic creation 10x with AI. The editor provides consistency and granular artistic control. More below. We first posted on HN 6 months ago when we built a prompt-to-comics AI ( https://ift.tt/9qQE2Yw ). We sunsetted this soon after - it was a fun experiment but it didn’t meet the real need of comic artists. Shortbread Studio now changes this by enhancing how creators naturally work instead of replacing them. The tech: One-shot Character LoRA: Artists upload a single photo of their character. Our backend uses prompt engineering and ControlNet pipelines to generate a synthetic dataset from this photo. This dataset shows the character in all kinds of angles, poses and facial expressions that the artist can pick the best from. It’s then sent to our LoRA training service to create a LoRA model. This takes about 7 minutes. Control -> Redraw -> Refine Workflow: In real life drawing, you draw, erase, and draw again. The human creative process is iterative. In Shortbread Studio, artists can start from a text prompt, a sketch, a web image or a pose reference as a basis, create an initial panel and quickly modify and regenerate until they get what they want. If you spend 5 seconds, you get a decent panel. If you spend 10 minutes, you can push the limits and get pro results. Built-in Post-Processing: The editor’s features include liquify, upscale, remove background, and outpainting to extend an image. This allows artists to remove, add, or modify parts of an image on a pixel level without drawing by hand. We combine this with segmentation models like Segment Anything ( https://ift.tt/NGCZEXa ) to support intelligently selecting and editing a part of an image. Google-docs like collaboration: The Studio runs in the browser and supports comments and collaboration. LLM Powered Copy Editor: Comics need text. An AI agent proofreads speech bubbles, fixes lettering and identifies grammar mistakes. Read our comics: https://ift.tt/zcZY2oE (free to download + read, iOS + Android) All of the above are built by a team of 3 engineers including myself. I will be around to answer any questions in this thread!
12 by Fengjiao | 7 comments on Hacker News.
Hi HN! Fengjiao and Evan here. We are building Shortbread App, Netflix for webcomics. We publish guilty-pleasure romance series (think 50 Shades of Gray) as comics. Like the mature version of Webtoon. You can see two comics episodes at https://ift.tt/hTk3o96... https://ift.tt/1Np7Wzk... , and read more in the app via https://ift.tt/AQlh1KX . All comics in the app are made by artists using the Shortbread AI Comics Studio ( https://shortbread.ai ). It is a powerful Photoshop-like editor that speeds up comic creation 10x with AI. The editor provides consistency and granular artistic control. More below. We first posted on HN 6 months ago when we built a prompt-to-comics AI ( https://ift.tt/9qQE2Yw ). We sunsetted this soon after - it was a fun experiment but it didn’t meet the real need of comic artists. Shortbread Studio now changes this by enhancing how creators naturally work instead of replacing them. The tech: One-shot Character LoRA: Artists upload a single photo of their character. Our backend uses prompt engineering and ControlNet pipelines to generate a synthetic dataset from this photo. This dataset shows the character in all kinds of angles, poses and facial expressions that the artist can pick the best from. It’s then sent to our LoRA training service to create a LoRA model. This takes about 7 minutes. Control -> Redraw -> Refine Workflow: In real life drawing, you draw, erase, and draw again. The human creative process is iterative. In Shortbread Studio, artists can start from a text prompt, a sketch, a web image or a pose reference as a basis, create an initial panel and quickly modify and regenerate until they get what they want. If you spend 5 seconds, you get a decent panel. If you spend 10 minutes, you can push the limits and get pro results. Built-in Post-Processing: The editor’s features include liquify, upscale, remove background, and outpainting to extend an image. This allows artists to remove, add, or modify parts of an image on a pixel level without drawing by hand. We combine this with segmentation models like Segment Anything ( https://ift.tt/NGCZEXa ) to support intelligently selecting and editing a part of an image. Google-docs like collaboration: The Studio runs in the browser and supports comments and collaboration. LLM Powered Copy Editor: Comics need text. An AI agent proofreads speech bubbles, fixes lettering and identifies grammar mistakes. Read our comics: https://ift.tt/zcZY2oE (free to download + read, iOS + Android) All of the above are built by a team of 3 engineers including myself. I will be around to answer any questions in this thread!
Monday, 3 June 2024
New top story on Hacker News: Show HN: I made a tiny camera with super long battery life
Show HN: I made a tiny camera with super long battery life
28 by davekeck | 4 comments on Hacker News.
Hey HN! A few years ago someone kept trying to steal my motorcycle, so I decided to make a small camera with really long battery life to catch them. The hardware/software is totally open source, but the companion app only supports macOS currently. (I'm a big fan of native apps, and didn't want to block releasing on Linux/Windows support.) I wrote some blog posts about the process: PCB design: https://ift.tt/CoaSner Enclosure design: https://ift.tt/slzOJLr Image pipeline: https://ift.tt/GuMKjXx Rainproofing: https://ift.tt/x4BLdFA Source: https://ift.tt/gi4Vy3D
28 by davekeck | 4 comments on Hacker News.
Hey HN! A few years ago someone kept trying to steal my motorcycle, so I decided to make a small camera with really long battery life to catch them. The hardware/software is totally open source, but the companion app only supports macOS currently. (I'm a big fan of native apps, and didn't want to block releasing on Linux/Windows support.) I wrote some blog posts about the process: PCB design: https://ift.tt/CoaSner Enclosure design: https://ift.tt/slzOJLr Image pipeline: https://ift.tt/GuMKjXx Rainproofing: https://ift.tt/x4BLdFA Source: https://ift.tt/gi4Vy3D
Sunday, 2 June 2024
Saturday, 1 June 2024
Deputies: Alcohol factor in deadly Grand Rapids Township crash
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