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Docker Bake is Now Generally Available in Docker Desktop 4.38!

6 February 2025 at 04:47

We’re excited to announce the General Availability of Docker Bake with Docker Desktop 4.38! This powerful build orchestration tool takes the hassle out of managing complex builds and offers simplicity, flexibility, and performance for teams of all sizes.

2400x1260 docker evergreen logo blog C 1

What is Docker Bake?

Docker Bake is an orchestration tool that streamlines Docker builds, similar to how Compose simplifies managing runtime environments. With Bake, you can define build stages and deployment environments in a declarative file, making complex builds easier to manage. It also leverages BuildKit’s parallelization and optimization features to speed up build times.

While Dockerfiles are excellent for defining image build steps, teams often need to build multiple images and execute helper tasks like testing, linting, and code generation. Traditionally, this meant juggling numerous docker build commands with their own options and arguments – a tedious and error-prone process.

Bake changes the game by introducing a declarative file format that encapsulates all options and image dependencies, referred to as targets. Additionally, Bake’s ability to parallelize and deduplicate work ensures faster and more efficient builds.

Why should you use Bake?

Challenges with complex Docker Build configuration:

  • Managing long, complex build commands filled with countless flags and environment variables.
  • Tedious workflows for building multiple images.
  • Difficulty declaring builds for specific targets or environments.
  • Requires a script or 3rd-party tool to make things manageable

Docker Bake tackles these challenges with a better way to manage complex builds with a simple, declarative approach.

Key benefits of Docker Bake

  • Simplicity: Replace complex chains of Docker build commands and scripts with a single docker buildx bake command while maintaining clear, version-controlled configuration files that are easy to understand and modify.
  • Flexibility: Express sophisticated build logic through HCL syntax and matrix builds, enabling dynamic configurations that adapt to different environments and requirements while supporting custom functions for advanced use cases.
  • Consistency: Maintain standardized build configurations across teams and environments through version-controlled files and inheritance patterns, eliminating environment-specific build issues and reducing configuration drift.
  • Performance: Automatically parallelize independent builds and eliminate redundant operations through context deduplication and intelligent caching, dramatically reducing build times for complex multi-image workflows.
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Figure 1: One simple Docker buildx bake command to replace all the flags and environment variables.

Use cases for Docker Bake

1. Monorepo and Image Bakery

Docker Bake can help developers efficiently manage and build multiple related Docker images from a single source repository. Plus, they can leverage shared configurations and automated dependency handling to enforce organizational standards.

  • Development Efficiency: Teams can maintain consistent build logic across dozens or hundreds of microservices in a single repository, reducing configuration drift and maintenance overhead.
  • Resource Optimization: Shared base images and contexts are automatically deduplicated, dramatically reducing build times and storage costs.
  • Standardization: Enforce organizational standards through inherited configurations, ensuring all services follow security, tagging, and testing requirements.
  • Change Management: A single source of truth for build configurations makes it easier to implement organization-wide changes like base image updates or security patches.

2. Compose users

Docker Bake provides seamless compatibility with existing docker-compose.yml files, allowing direct use of your current configurations. Existing Compose users are able to get started using Bake with minimal effort.

  • Gradual Adoption: Teams can incrementally adopt advanced build features while still leveraging their existing compose workflows and knowledge.
  • Development Consistency: Use the same configuration for both local development (via compose) and production builds (via Bake), eliminating “works on my machine” issues.
  • Enhanced Capabilities: Access powerful features like matrix builds and HCL expressions while maintaining compatibility with familiar compose syntax.
  • CI/CD Integration: Seamlessly integrate with existing CI/CD pipelines that already understand compose files while adding Bake’s advanced build capabilities.

3. Complex build configurations

Developers can use targets, groups, variables, functions, and matrix targets and many more tools in Bake to simplify their build configurations across projects and teams.

  • Cross-Platform Compatibility: Matrix builds enable teams to efficiently manage builds across multiple architectures, OS versions, and dependency combinations from a single configuration.
  • Dynamic Adaptation: HCL expressions allow builds to adapt to different environments, git branches, or CI variables without maintaining multiple configurations.
  • Build Optimization: Custom functions enable sophisticated logic for things like version calculation, tag generation, and conditional builds based on git history.
  • Quality Control: Variable validation and inheritance ensure consistent configuration across complex build scenarios, reducing errors and maintenance burden.
  • Scale Management: Groups and targets help organize large-scale build systems with dozens or hundreds of permutations, making them manageable and maintainable.

4. Docker Build Cloud

With Bake-optimized builds as the foundation, developers can achieve more efficient Docker Build Cloud performance and faster builds.

  • Enhanced Docker Build Cloud Performance: Instantly parallelize matrix builds across cloud infrastructure, turning hour-long build pipelines into minutes without managing build infrastructure.
  • Resource Optimization: Leverage Build Cloud’s distributed caching and deduplication to dramatically reduce bandwidth usage and build times, which is especially valuable for remote teams.
  • Cost Management: Save cost with DBC Bake’s precise target definitions mean you only consume cloud resources for exactly what needs to be built.
  • Developer Experience: Teams can run complex multi-architecture builds without powerful local machines, enabling development from any device while maintaining build performance.
  • CI/CD Enhancement: Offload resource-intensive builds from CI runners to Build Cloud, reducing CI costs and queue times while improving reliability.

What’s New in Bake for GA?

Docker Bake has been an experimental feature for several years, allowing us to refine and improve it based on user feedback. So, there is already a strong set of ingredients that users love, such as targets and groups, variables, HCL Expression Support, inheritance capabilities, matrix targets, and additional contexts. With this GA release, Bake is now ready for production use, and we’ve added several enhancements to make it more efficient, secure, and easier to use:

  • Deduplicated Context Transfers: Significantly speeds up build pipelines by eliminating redundant file transfers when multiple targets share the same build context.
  • Entitlements: Enhances security and resource management by providing fine-grained control over what capabilities and resources builders can access during the build process.
  • Composable Attributes: Simplifies configuration management by allowing teams to define reusable attribute sets that can be mixed, matched, and overridden across different targets.
  • Variable Validation: Prevents wasted time and resources by catching configuration errors before the actual build process begins.

Deduplicate context transfers

When you build targets concurrently using groups, build contexts are loaded independently for each target. If the same context is used by multiple targets in a group, that context is transferred once for each time it’s used. This can significantly impact build time, depending on your build configuration.

Previously, the workaround required users to define a named context that loads the context files and then have each target reference the named context. But with Bake, this will be handled automatically now.

Bake can automatically deduplicate context transfers from targets sharing the same context. When you build targets concurrently using groups, build contexts are loaded independently for each target. If the same context is used by multiple targets in a group, that context is transferred once for each time it’s used. This more efficient approach leads to much faster build time. 

Read more about how to speed up your build time in our docs

Entitlements

Bake now includes entitlements to control access to privileged operations, aligning with Build. This prevents unintended side effects and security risks. If Bake detects a potential issue — like a privileged access request or an attempt to access files outside the current directory — the build will fail unless explicitly allowed.

To be consistent, the Bake command now supports the --allow=ENTITLEMENT flag to grant access to additional entitlements. The following entitlements are currently supported for Bake.

  • Build equivalents
    • --allow network.host Allows executions with host networking.
    • --allow security.insecure Allows executions without sandbox. (i.e. —privileged)
  • File system: Grant filesystem access for builds that need access files outside the working directory. This will impact context, output, cache-from, cache-to, dockerfile, secret
    • --allow fs=<path|*> Grant read and write access to files outside the working directory.
    • --allow fs.read=<path|*> Grant read access to files outside the working directory.
    • --allow fs.write=<path|*> Grant write access to files outside the working directory.
  • ssh
    • --allow ssh – Allows exposing SSH agent.

Composable attributes

Several attributes previously had to be defined in CSV (e.g. type=provenance,mode=min). These were challenging to read and couldn’t be easily overridden. The following can now be defined as structured objects:

target "app" {
		attest = [
			{ type = "provenance", mode = "max" },
			{ type = "sbom", disabled = true}
		]

		cache-from = [
			{ type = "registry", ref = "user/app:cache" },
			{ type = "local", src = "path/to/cache"}
		]

		cache-to = [
			{ type = "local", dest = "path/to/cache" },
		]

		output = [
			{ type = "oci", dest = "../out.tar" },
			{ type = "local", dest="../out"}
		]

		secret = [
			{ id = "mysecret", src = "path/to/secret" },
			{ id = "mysecret2", env = "TOKEN" },
		]

		ssh = [
			{ id = "default" },
			{ id = "key", paths = ["path/to/key"] },
		]
}

As such, the attributes are now composable. Teams can mix, match, and override attributes across different targets which simplifies configuration management.

 target "app-dev" {
    attest = [
			{ type = "provenance", mode = "min" },
			{ type = "sbom", disabled = true}
		]
  }

  target "app-prod" {
    inherits = ["app-dev"]

    attest = [
			{ type = "provenance", mode = "max" },
		]
  }

Variable validation

Bake now supports validation for variables similar to Terraform to help developers catch and resolve configuration errors early. The GA for Bake also supports the following use cases.

Basic validation

To verify that the value of a variable conforms to an expected type, value range, or other condition, you can define custom validation rules using the validation block.

variable "FOO" {
  validation {
    condition = FOO != ""
    error_message = "FOO is required."
  }
}

target "default" {
  args = {
    FOO = FOO
  }
}

Multiple validations

To evaluate more than one condition, define multiple validation blocks for the variable. All conditions must be true.

variable "FOO" {
  validation {
    condition = FOO != ""
    error_message = "FOO is required."
  }
  validation {
    condition = strlen(FOO) > 4
    error_message = "FOO must be longer than 4 characters."
  }
}

target "default" {
  args = {
    FOO = FOO
  }
}

Dependency on other variables

You can reference other Bake variables in your condition expression, enabling validations that enforce dependencies between variables. This ensures that dependent variables are set correctly before proceeding.

variable "FOO" {}
variable "BAR" {
  validation {
    condition = FOO != ""
    error_message = "BAR requires FOO to be set."
  }
}

target "default" {
  args = {
    BAR = BAR
  }
}

New Bake options

In addition to updating the Bake configuration, we’ve added a new –list option. Previously, if you were unfamiliar with a project or wanted a reminder of the supported targets and variables, you would have to read through the file. Now, the list option will allow you to quickly query a list of them. It also supports the JSON format option if you need programmatic access.

List target

Quickly get a list of the targets available in your Bake configuration.

  • docker buildx bake --list targets
  • docker buildx bake --list type=targets,format=json

List variables

Get a list of variables available for your Bake configuration.

  • docker buildx bake --list variables
  • docker buildx bake --list type=variables,format=json

These improvements build on a powerful feature set, ensuring Bake is both reliable and future-ready.

Get started with Docker Bake

Ready to simplify your builds? Update to Docker Desktop 4.38 today and start using Bake. With its declarative syntax and advanced features, Docker Bake is here to help you build faster, more efficiently, and with less effort.

Explore the documentation to learn how to create your first Bake file and experience the benefits of streamlined builds firsthand.

Let’s bake something amazing together!

Seeed Studio at AWS re:Invent 2024: Empowering Edge AI and IoT Innovation 

By: Elaine Wu
22 January 2025 at 10:05
Acknowledgments
I want to express my heartfelt gratitude to Channa Samynathan, Senior Worldwide Specialist Solutions Architect at AWS, as well as the AWS IoT Robotics team for their valuable contributions to this post. Their insights and expertise were instrumental in delivering the event and this content.

As AWS re:Invent 2024 wrapped up, the energy and innovation displayed at the event left us inspired and excited about the future of IoT and Edge AI. Seeed Studio was proud to partner with AWS, contributing cutting-edge hardware and expertise to showcase the power of connected technologies in real-world applications. Here are some key highlights from our collaborations:

Advancing Disaster Response with Edge AI and IoT

At the Amazon Security and Disaster Response Activation, our hardware played a key role in showcasing the potential of IoT to revolutionize emergency scenarios. Here are some highlights from our collaboration:

1. Disaster Response with Meshtastic Devices and Nvidia Jetson 

We were proud to partner with AWS to demonstrate the power of IoT in disaster response scenarios. Our hardware, including the SenseCAP T1000-E Meshtastic Tracker and reComputer J4012, worked seamlessly with AWS IoT Core to create a private, reliable communication channel.

  • Real-time Data Tracking: Our system showcased the potential for compliant and real-time data tracking during emergencies, paving the way for rapid deployment in disaster scenarios.
  • Synergy of Edge Computing and Cloud Capabilities: This activation exemplifies the synergy of AWS IoT’s cloud capabilities and Seeed’s edge computing solutions to address real-world challenges.

We’re thrilled to see this project advancing toward commercialization to support disaster response efforts globally. At Seeed Studio, we’re committed to empowering innovation and advancing the possibilities of Edge AI and IoT.

LoRaWAN and Real-Time Tracking Across Las Vegas

One of the standout activations was the Amazon Security and Disaster Response Activation, which showcased the potential of AWS IoT in real-world scenarios. Our SenseCAP M2 Multi-Platform LoRaWAN Gateway played a key role in this demonstration, contributing to the creation of a vast LoRaWAN network that covered the entire city of Las Vegas.

Key Highlights:

  • Wide-Area Coverage: Our LoRaWAN gateways facilitated communication with 45 LoRaWAN devices carried by AWS staff, capturing GPS, humidity, and temperature data every two minutes.
  • Real-Time Updates: The data was transmitted through the LoRaWAN gateways to AWS IoT Core for LoRaWAN and published onto an Amazon Location Service map. The map, updated every two minutes, was accessible to attendees via a QR code.
  • Simulated Downstream Processing: By integrating the data with a TAK server, the activation demonstrated how real-time location and environmental information can enhance situational awareness and decision-making in security and emergency scenarios.

The Power of IoT in Critical Events

The successful implementation of this expansive network underscores the potential of IoT in enabling wide-area connectivity and situational awareness during critical events. At Seeed Studio, we’re committed to empowering innovation and advancing the possibilities of IoT.

3. Embodied AI Chess Demo at the Generative AI Pavilion

Another incredible activation was the Embodied AI Chess Demo at the AWS Generative AI Pavilion, which showcased the potential of AI-driven robotics in real-world applications. Our reServers powered the demonstration, ensuring seamless operation throughout the event.

Key Highlights:

  • AI-Powered Robotics: Using inference from foundation models via AWS Bedrock, robot arms performed chess moves based on real-time commands.
  • Flawless Performance: Our reServers of NVIDIA Jetson ensured seamless operation throughout the event, demonstrating the potential of industrial-grade hardware in advanced AI applications.

The Future of Intelligent Automation

This activation sparked engaging discussions about the integration of generative AI with robotics, pushing the boundaries of what’s possible in intelligent automation. At Seeed Studio, we’re committed to empowering innovation and advancing the possibilities of AI and robotics.

4. Hands-On Edge AI Workshop with NVIDIA Jetson and AWS IoT Greengrass

We partnered with AWS on the “Unleash Edge Computing with AWS IoT Greengrass on NVIDIA Jetson” workshop, providing attendees with hands-on experience in deploying and managing edge runtime devices through AWS IoT Core and AWS IoT Greengrass.

Key Highlights:

  • Practical Experience: Attendees gained practical experience in deploying and managing edge runtime devices, showcasing the potential of edge computing and Connected Edge Intelligence (CEI) in real-world use cases.
  • The workshop was using 150 reComputer J4012 and demonstrated the power of edge AI in real-world applications.

 

5. AWS IoT RaceTrack Revolution Builders’ Fair Activation with The Tiny Seeed Studio XIAO

At the AWS Builders’ Fair, the AWS IoT team wowed attendees with the AWS IoT RaceTrack Revolution demo. Our Seeed Studio XIAO ESP32 dev boards, with Wi-Fi capabilities, enhanced the experience by offloading video feeds seamlessly to the Nvidia Jetson device.

Key Highlights:

  • Innovative Demo: The demo showcased the power of AWS IoT in a hands-on, engaging setting, despite Wi-Fi challenges.
  • Seeed Studio XIAO ESP32 Dev Boards: Our dev boards played a crucial role in offloading video feeds, enhancing the overall experience.

Empowering Innovation and Advancing IoT Possibilities

At Seeed Studio, we’re committed to empowering innovation and advancing the possibilities of Edge AI and IoT. Our collaboration with AWS has been a testament to the power of connected technologies in real-world applications, and we look forward to continuing this journey together.

Empowering IoT Innovation Together


At Seeed Studio, we’re thrilled to have played a key role in the AWS re:Invent 2024, where the fusion of cloud computing and cutting-edge hardware unlocked new possibilities. Our collaboration with AWS has been instrumental in showcasing how our solutions can effortlessly integrate with the powerful AWS IoT ecosystem to tackle pressing issues in disaster response, security, AI, and beyond.

We’re committed to driving innovation forward with AWS and look forward to witnessing the real-world impact of these solutions. Stay tuned for more updates as we continue to push the boundaries of IoT and Edge AI together, empowering a smarter and more connected world.

The post Seeed Studio at AWS re:Invent 2024: Empowering Edge AI and IoT Innovation  appeared first on Latest Open Tech From Seeed.

ARMOR: Egocentric Perception for Humanoid Robot Powered by XIAO ESP32S3

16 January 2025 at 01:31

Daehwa Kim (Carnegie Mellon University), Mario Srouji, Chen Chen, and Jian Zhang (Apple) have developed ARMOR, an innovative egocentric perception hardware and software system for humanoid robots. By combining Seeed Studio XIAO ESP32S3-based wearable depth sensor networks and transformer-based policies, ARMOR tackles the challenges of collision avoidance and motion planning in dense environments. This system enhances spatial awareness and enables nimble and safe motion planning, outperforming traditional perception setups. ARMOR was deployed on the GR1 humanoid robot from Fourier Intelligence, showcasing its real-world applications.

[Source: Daehwa Kim]

Hardwares Used

ARMOR uses the following hardware components:

    • XIAO ESP32S3 microcontrollers: Efficiently collect sensor data and stream it to the robot’s onboard computer via I2C.
    • Onboard Computer: NVIDIA Jetson Xavier NX processes sensor inputs. 
    • GPU (NVIDIA GeForce RTX 4090): Handles ARMOR-Policy’s inference-time optimization for motion planning.
    • SparkFun VL53L5CX Time-of-Flight (ToF) lidar sensors: Distributed across the robot’s body for comprehensive point cloud perception.

How the ARMOR Works

The hardware solution of ARMOR’s egocentric perception system uses distributed ToF lidar sensor networks. Groups of four ToF sensors are connected to Seeed Studio XIAO ESP32S3 microcontrollers, capturing high-precision depth information from the environment. The XIAO ESP32S3 serves as a crucial intermediary controller, efficiently managing real-time sensor data transmission. It streams the collected depth data via USB to the robot’s onboard computer, the NVIDIA Jetson Xavier NX, which then wirelessly transmits the data to a powerful Linux machine equipped with an NVIDIA GeForce RTX 4090 GPU for data processing. This sophisticated data pipeline enables the creation of an occlusion-free point cloud around the humanoid robot, providing essential environmental awareness data for the ARMOR neural motion planning algorithm. The distributed and light-weight hardware setup also ensures enhanced spatial awareness and overcomes the limitations of head-mounted or external cameras, which often fail in cluttered or occluded environments.

Daehwa Kim, one of the core developers of this project, mentions why they selected the Seeed Studio XIAO for this project.

“We might imagine a future where users easily plug and play with wearable sensors for humanoids and augment robots' perceptions in various tasks. XIAO ESP32 series makes the wearable sensor system easily modularizable. We specifically adopted the XIAO ESP32S3 in ARMOR because of its powerful computing and tiny form factor.”
Armor Policy - Transformer-based policy [Source: Daehwa Kim]

The neural motion planning system, ARMOR-Policy, is built on a transformer-based architecture called the Action Chunking Transformer. This policy was trained on 86 hours of human motion data from the AMASS dataset using imitation learning. ARMOR-Policy processes the robot’s current state, goal positions, and sensor inputs to predict safe and efficient trajectories in real-time. The system leverages latent variables to explore multiple trajectory solutions during inference, ensuring flexibility and robustness.

Trained on 86 hours of human motion dataset [Source: Daehwa Kim]

ARMOR was rigorously tested in both simulated and real-world scenarios. It demonstrated remarkable improvements in performance, reducing collisions by 63.7% and increasing success rates by 78.7% compared to exocentric systems with dense head-mounted cameras. Additionally, the transformer-based ARMOR-Policy reduced computational latency by 26× compared to sampling-based motion planners like cuRobo, enabling efficient and nimble collision avoidance.

Real World Hardware Deployment [Source: Daehwa Kim]

Discover more about ARMOR

Want to explore ARMOR’s capabilities? The research team will soon release the source code, hardware details, and 3D CAD files on their GitHub repository. Dive deeper into this cutting-edge project by reading their paper on arXiv. Stay tuned for updates to replicate and innovate on this revolutionary approach to humanoid robot motion planning! To see ARMOR in action, check out their demonstration video on YouTube.

End Note

Hey community, we’re curating a monthly newsletter centering around the beloved Seeed Studio XIAO. If you want to stay up-to-date with:

🤖 Cool Projects from the Community to get inspiration and tutorials
📰 Product Updates: firmware update, new product spoiler
📖 Wiki Updates: new wikis + wiki contribution
📣 News: events, contests, and other community stuff

Please click the image below👇 to subscribe now!

The post ARMOR: Egocentric Perception for Humanoid Robot Powered by XIAO ESP32S3 appeared first on Latest Open Tech From Seeed.

💾

From Idea to Reality: Seeed and Flux.ai Speed Up Your Way to the Next Level!

11 December 2024 at 14:49

As many of you know, Seeed has always been committed to providing makers with easy-to-use and innovative products, services, and solutions. Over the past year, our partnership with Flux.ai has grown stronger than ever! 

Mind-blowing! Check Out What We've Created

For developers, Flux and Seeed have created a streamlined path from concept to reality. As an AI-driven design tool, Flux accelerates the PCB design process, while Seeed Studio Fusion provides rapid prototyping-PCB manufacturing & assembly services

This partnership has already empowered developers to bring their innovative ideas to life. By combining our expertise, we’ve been able to deliver exceptional results and generate significant visibility for these projects.  You can check them on our organization page at Flux!

We hope that our small support will bring significant changes to the areas and causes in need. Inspired by these projects? You’ll love what’s coming next!

LED Remix: Design the Next Generation

In order to invite more developers to co-create with us, we kickstart a campaign called LED Remix: Design the Next Generation!

ℹ How to Apply?

Step 1: Please fill out the form to submit your bravo project!

         🌟 Each participant is limited to two PCBA boards 100% completely FREE for one design, including PCB fabrication, the cost of parts, assembly, and shipping.

         🌟 Free usage of Flux.ai for 2 months

The project must include a LED design and a Xiao module, and use Flux.ai as the design tool❗

Step 2: After submitting your application, our team will promptly assess your design. Kindly await our team’s contact.

📅 Duration: 12th Dec. 2024- 12th Mar. 2025

By participating in this event, you agree to review your experience with us and allow us to share it and the design with the community on our social media platforms (Facebook, Twitter, blog, etc.).

ℹ If you’re currently short on ideas, don’t worry, we’re here to help!  

To provide you with some inspiration, we’ve invited Goku to design two mother projects below, which are designed by Flux.ai and manufactured at Seeed Studio Fusion

Feel free to build upon these projects and create your unique designs!🙌✊

It’s inspired by the character Destined One from “Black Myth: Wukong.” For this project, Goku uses 37 tiny pixel LEDs along with the Seeed Studio XIAO ESP32-C3 microcontroller, which will program with WLED.

➡Clone at Flux: https://www.flux.ai/gokux/black-myth-wukong

➡Detailed Tutorial: https://www.instructables.com/Lets-Make-a-Black-Myth-Wukong-LED-Art-PCB/

Ready to turn your Xiao ESP32-S3 into a smart lighting controller? WLED is the perfect tool for the job. This open-source web server lets you control both digital and analog LED strips, and even integrate with smart home platforms like Alexa and Google Assistant. Let’s get started!

➡Clone at Flux: https://www.flux.ai/seeedstudio/wled-rgb-led-driverp

➡Detailed Tutorial: https://www.instructables.com/WLED-ON-XIAO-ESP32/

Tips: You can find most of the components needed at Flux. If there are any questions during the design process, you can ask for help using the co-pilot. You can also go to Goku’s project file to view his designs, and it is possible to clone his project and make your own changes. We are ready to illuminate and spread your ideas coupled with projects anytime!​

Combining Flux’s AI-driven Auto-Layout with Seeed’s example projects makes it easy to create something uniquely yours quickly. Here’s how you can do it:
  • Step 1: Clone the Project
    • Start with a Seeed example project in Flux to avoid designing from scratch.
  • Step 2: Customize the Design
    • Use Flux’s editor and part library to customize the design, swap components, or add new functionality.
  • Step 3: Run the Auto-Layout
    • Let Flux’s AI optimize the placement and routing of components, ensuring your design is manufacturable and ready to go.

Auto-Layout uses AI to optimize component placement and routing while considering your design constraints. This ensures the layout is both functional and ready for manufacturing. Whether you’re adjusting an LED configuration or refining a component layout, Auto-Layout simplifies the process, allowing you to focus on your design.

Scale up your Creation with Seeed Studio Co-Create Program!

We will invite well-received LED Remix projects to the Seeed Studio Co-Create Program, where your products can be listed, sold and shipped directly by Seeed on the Seeed Studio Bazaar. We will also support designers to reach thousands of like-minded customers and distributors with Seeed’s global sales channels and social media presence.

Don’t hesitate! It’s a great chance to show off your ideas and skills. Join and fuel your passion now!

The post From Idea to Reality: Seeed and Flux.ai Speed Up Your Way to the Next Level! appeared first on Latest Open Tech From Seeed.

Let’s Type Cooler with KeebSupply Keyboards: Zilpzalp and GEIST TOTEM, Powered by Seeed Studio XIAO

29 November 2024 at 16:38

At KeebSupply, a passion for unique, high-quality mechanical keyboards has transformed a small hobby into a thriving business for Jakob, Conor, and Timur. Initially, Jakob and Conor’s tinkering led them to design a modest macropad in 2020, sparking a love for designing custom keyboards that’s only grown. Today, the KeebSupply team brings users thoughtful, meticulously crafted designs that balance simplicity with innovation, inviting keyboard enthusiasts of all skill levels to create and customize their perfect setup.

MacroPad image
Their very first 1337 MacroPad

With each product, KeebSupply aims to empower hobbyists and designers alike by creating versatile, customizable keyboards built around open-source principles. Collaborating with artists and designers in the mechanical keyboard community, the team develops products that support the DIY ethos, using quality materials and components while prioritizing accessibility.

Today, let’s dive into two of their very special innovations, Zilpzalp and GEIST TOTEM, to see how KeebSupply combines simplicity, community-driven design, and advanced tech with the tiny but powerful Seeed Studio XIAO controllers.

The Zilpzalp Keyboard: Compact, Portable, and Minimalist, Powered by XIAO RP2040


Source: KeebSupply

The Zilpzalp, designed by kilipan, brings a unique take to the unibody-split keyboard format. With just 28 keys, the Zilpzalp is a column-staggered keyboard that maintains the precision and functionality of a full-sized keyboard in a much smaller footprint. Its minimalist layout makes it a great choice for anyone prioritizing compactness without compromising on ergonomic features.

Central to the Zilpzalp’s design is the Seeed Studio XIAO RP2040 microcontroller, a compact yet powerful component that supports both QMK and ZMK firmware for wired and wireless configurations, respectively. The Zilpzalp offers various switch versions, including Choc and MX, with options for both hot-swap sockets and solder-only setups, so users can fully customize their tactile experience. Thanks to FOSS tools like KiCad and Ergogen, the keyboard’s PCB layout is open-source, inviting more customization options.

Source: KeebSupply

The Zilpzalp is ideal for minimalist enthusiasts who want a small, portable keyboard without sacrificing style or performance. Its compact nature makes it perfect for travelers, desk minimalists, and anyone looking to explore compact keyboards for the first time.

The GEIST TOTEM Keyboard: A Versatile, Ergonomic Split Design, Powered by XIAO nRF52840 and XIAO RP2040


Source: KeebSupply

GEIST TOTEM, a collaborative project between KeebSupply and designer GEIST, is a 38-key, column-staggered split keyboard designed with both comfort and flexibility in mind. TOTEM is a great fit for those who prefer a low-profile, ergonomic setup, as it comes with a split layout to help reduce strain on the fingers and wrists during long sessions.

The TOTEM kit comes in a wired and wireless variant. The wired version runs on the XIAO RP2040, while the wireless model uses the XIAO nRF52840 for seamless Bluetooth connectivity. Designed with beginners in mind, TOTEM includes pre-soldered diodes to streamline the assembly process. Each kit comes standard with a durable SLA 3D-printed black resin case, ensuring a sleek and sturdy build. For those seeking maximum convenience, a fully assembled kit option is also available, making it easy to dive into the world of custom keyboards.

GeistTotem img

Source: KeebSupply

It’s noteworthy that GEIST TOTEM won the first prize award in the Seeed Fusion DIY XIAO Mechanical Keyboard Contest back in 2022. It’s always exciting to see projects like this flourish in the community, thanks to KeebSupply.

The KeebSupply Experience

Whether you’re a DIY keyboard enthusiast or a newcomer to custom keyboards, KeebSupply’s Zilpzalp and TOTEM models bring something truly special to the table. These keyboards showcase the team’s commitment to accessible, high-quality designs, allowing users to personalize their typing experience fully. KeebSupply’s collaboration with designers like GEIST and kilipan reflects their passion for open-source designs and their support for the keyboard community.

For more about Zilpzalp, TOTEM, or any of KeebSupply’s projects, head over to their website.


More Info

End Note

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The post Let’s Type Cooler with KeebSupply Keyboards: Zilpzalp and GEIST TOTEM, Powered by Seeed Studio XIAO appeared first on Latest Open Tech From Seeed.

SeamPose Powered by XIAO nRF52840, Repurposing Seams for Upper-Body Pose Tracking with Smart Clothing

29 October 2024 at 17:31

Imagine turning your everyday clothes into smart motion-tracking tools. That’s exactly what a team of researchers at Cornell University has achieved with SeamPose. This innovative project, led by Catherine Tianhong Yu and Professor Cheng Zhang uses conductive threads sewn over the seams of a shirt to transform it into an upper-body pose-tracking device by unleashing the power of XIAO nRF52840. Unlike traditional sensor-laden garments that change the clothing’s appearance and comfort, SeamPose blends seamlessly into everyday wear without compromising aesthetics or fit.

This project offers exciting potential applications in areas like health monitoring, sports analytics, AR/VR, and human-robot interaction by making wearable tracking more accessible and comfortable.

Source: Cornell University Team

Hardwares

To build SeamPose, the following key hardware elements were used:

    • Long-sleeve T-shirt with machine-sewn conductive thread along the seams.
    • Customized Sensing Board:
      • XIAO nRF52840 
      • A 36x31mm board with two FDC2214 capacitance-to-digital converters
      • 3.7V 290mAh LiPo battery
Source: Cornell University Team

How SeamPose Works

SeamPose operates by transforming ordinary seams in a long-sleeve shirt into capacitive sensors, enabling real-time tracking of upper-body movements. Conductive threads, specifically insulated silver-plated nylon, are machine-sewn along key seams—such as the shoulders and sleeves—without altering the garment’s appearance or comfort. As the wearer moves, the seams stretch and shift, causing variations in their capacitance. These signals are captured by a customized sensing board integrated with two FDC2214 capacitance-to-digital converters and the XIAO nRF52840 microcontroller. The XIAO nRF52840 transmits the data wirelessly via Bluetooth Low Energy (BLE) to a nearby computer for processing.

The transmitted signals are fed into a deep learning model that maps the seam data to 3D joint positions relative to the pelvis. This allows the system to interpret complex upper-body movements using only eight sensors distributed symmetrically along the shirt. During testing, SeamPose achieved a mean per joint position error (MPJPE) of 6.0 cm, comparable to more invasive tracking systems. The XIAO nRF52840 ensures seamless real-time data transmission, making SeamPose a breakthrough in wearable technology by combining comfort with precise motion tracking.

Signals

Source: Cornell University Team

What’s Next for SeamPose?

SeamPose offers a glimpse into the future of smart clothing, where everyday garments become powerful tools for motion tracking without sacrificing comfort or design. However, challenges like real-world deployment considerations and smart-clothing manufacturing at scale need to be addressed for broader adoption. The research team plans to explore improved seam placement and enhanced sensor calibration for even more accurate tracking in the future.

If you’re excited about SeamPose and want to dive deeper, check out their paper on ACM Digital Library

End Note

Hey community, we’re curating a monthly newsletter centering around the beloved Seeed Studio XIAO. If you want to stay up-to-date with:

🤖 Cool Projects from the Community to get inspiration and tutorials
📰 Product Updates: firmware update, new product spoiler
📖 Wiki Updates: new wikis + wiki contribution
📣 News: events, contests, and other community stuff

Please click the image below👇 to subscribe now!

The post SeamPose Powered by XIAO nRF52840, Repurposing Seams for Upper-Body Pose Tracking with Smart Clothing appeared first on Latest Open Tech From Seeed.

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