From 8b36785de6bc561732d68706b47a7ac462b85a59 Mon Sep 17 00:00:00 2001 From: nfs0619 <1447996181@qq.com> Date: Mon, 5 Aug 2024 11:45:04 +0800 Subject: [PATCH 1/2] Updated weekly wiki --- docs/Seeed_Elderly/weekly_wiki/wiki240729.md | 216 ++++++++++++++++++ .../XIAO_ESP32C3_Pin_Multiplexing.md | 2 +- docs/weekly_wiki.md | 92 ++------ 3 files changed, 236 insertions(+), 74 deletions(-) create mode 100644 docs/Seeed_Elderly/weekly_wiki/wiki240729.md diff --git a/docs/Seeed_Elderly/weekly_wiki/wiki240729.md b/docs/Seeed_Elderly/weekly_wiki/wiki240729.md new file mode 100644 index 000000000000..e4a5de85b682 --- /dev/null +++ b/docs/Seeed_Elderly/weekly_wiki/wiki240729.md @@ -0,0 +1,216 @@ +--- +description: Weekly Wiki +title: Weekly Wiki +keywords: +- weeely wiki +image: https://files.seeedstudio.com/wiki/IndexWiki/logo_image.jpg +last_update: + date: 07/29/2024 + author: Frank +--- + +
+ +## Greetings + +This is Frank in Seeed Studio and welcome to the Seeed Studio weekly wiki! Each Monday, I will introduce you our latest wiki, including the ones related to our new products, the interesting projects published by Seeed Studio, and the tutorials, introductions, etc... You name it. + +✨ For each week, when a collaborator contributes a project or fixes something important, we put the stars at the end of title of "Weekly Wiki" for more people be able to see their efforts👍. + +Today is July 29th and a brand new week has begun! Check out what Seeed Studio did last week! + +## Latest Wiki Launched + +### [SenseCAP Watcher as a Grove sensor](https://wiki.seeedstudio.com/watcher_as_grove/) + +
+ +In this wiki, we will explore the exciting possibilities that arise when Watcher, acting as a Grove sensor, leverages its UART (Universal Asynchronous Receiver/Transmitter) functionality. By enabling UART communication, Watcher can transmit valuable data such as captured images and recognition results through its UART interface, located on the back of the device. This opens up a world of opportunities for integrating Watcher with various hardware platforms and creating innovative applications. + +### [Watcher & Node-RED To Kafka Quick Start](https://wiki.seeedstudio.com/watcher_node_red_to_kafka/) + +
+ +Apache Kafka is a distributed event streaming platform designed for high-throughput, fault-tolerant data processing. It enables real-time data feeds by allowing producers to publish messages to topics, while consumers can subscribe to these topics to process the data. Kafka is widely used for building data pipelines, real-time analytics, and integrating various data sources. Its robust architecture ensures scalability and durability, making it a popular choice for modern data-driven applications. + +Why use Docker? Because Docker can simulate the environment of multiple computers on a single machine and deploy applications with great ease. Therefore, in this project, we will use Docker to set up the environment and improve efficiency. + +### [T1000-E Tracker for Meshtastic](https://wiki.seeedstudio.com/sensecap_t1000_e/) + +

pir

+ +
+ + Get One Now 🖱️ + +
+ + +It is a high-performance tracker designed for Meshtastic, as small as a credit card, effortlessly fitting in your pocket or attaching to your assets. It embeds Semtech's LR1110, Nordic's nRF52840, and Mediatek's AG3335 GPS module, providing Meshtastic users with a high-precision, low-power positioning and communication solution. + +
+ +
+ +This wiki provides a tutorial on how to use NVStreamer for RTSP video streaming on [reComputer J4012](https://www.seeedstudio.com/reComputer-J4012-p-5586.html). + +### [How to Run VLM on reComputer with Jetson Platform Services](https://wiki.seeedstudio.com/run_vlm_on_recomputer/) + +VLMs are multi modal models supporting images, video and text and using a combination of large language models and vision transformers. Based on this capability, they are able to support text prompts to query videos and images thereby enabling capabilities such as chatting with the video, and defining natural language based alerts. The [VLM AI service](https://docs.nvidia.com/jetson/jps/inference-services/vlm.html), enables quick deployment of VLMs with Jetson Platform Services for video insight applications. The VLM service exposes REST API endpoints to configure the video stream input, set alerts and ask questions in natural language about the input video stream. + +
+ +
+ +This wiki provides a tutorial on how to run VLM on [reComputer J4012](https://www.seeedstudio.com/reComputer-J4012-p-5586.html). + +### [How to Run Zero-Shot Detection on reComputer with Jetson Platform Services](https://wiki.seeedstudio.com/run_zero_shot_detection_on_recomputer/) + +Generative AI vision transformers such as CLIP have made it possible to build zero shot detection models capable of open vocabulary object detection. Meaning, the model is not bounded by a set of pre-defined classes to detect. The objects to detect are configured at runtime by the user. The Zero Shot Detection AI service, enables quick deployment of generative AI with Jetson Services for open vocabulary detection on video live stream input. The Zero Shot Detection AI service exposes REST API endpoints to control stream input and objects to detect. + +
+ +
+ +This wiki provides a tutorial on how to run Zero-Shot Detection on [reComputer J4012](https://www.seeedstudio.com/reComputer-J4012-p-5586.html). + +### [Pose-Based Light Control with Node-Red and Raspberry Pi with AIkit](https://wiki.seeedstudio.com/pose_based_light_control_with_nodered_and_rpi_with_aikit/) + +

pir

+ +This wiki will guide you on how to run YOLOv8 using an AI kit, use YOLOv8 to monitor your posture, and ultimately control your lights based on your posture. In this project, a USB camera captures your pose, and yolov8n run on [AI kit](https://www.seeedstudio.com/Raspberry-Pi-AI-Kit-p-5900.html) with [reComputer R1000](https://www.seeedstudio.com/reComputer-R1000-Series-Optional-Accessories.html) to detect your pose. The processed video, displaying the detected pose, is then streamed in real-time to [reTerminal DM](https://www.seeedstudio.com/reTerminal-DM-CM4104032-p-5898.html) using [gstreamer](https://gstreamer.freedesktop.org/). Meanwhile, the joint coordinates are sent using [mqtt](https://mqtt.org/) to [Node-RED](https://nodered.org/) which deploy on the reComputer R1000. At last, the Node-RED flow controls the smart lights based on the joint coordinates. + +### [reComputer R1000 with FIN to create a Equip Graphic](https://wiki.seeedstudio.com/reComputer_r1000_fin_floor_gaphic/) + +FIN Framework (FIN) is a software framework with application suites that can integrate, control, manage, analyze, visualize and connect. Its capabilities can be integrated by OEMs into a range of products and services. + +This article will show you how to use the `Graphics Builder` of FIN Framwork, and to create a `Equip Graphic` using the `Graphics Builder`. + +### [Convert Model to Edge TPU TFlite Format for Google Coral](https://wiki.seeedstudio.com/convert_model_to_edge_tpu_tflite_format_for_google_coral/) + +The [Coral M.2 Accelerator](https://www.seeedstudio.com/Coral-M2-Accelerator-with-Dual-Edge-TPU-p-4681.html) with Dual Edge TPU is an M.2 module that brings two Edge TPU coprocessors to existing systems and products with an available M.2 E-key slot.[Tensorflow](https://www.tensorflow.org/) and [Pytorch](https://pytorch.org/) is the most popular deep learning frameworks. So in order to use the Edge TPU, we need to compile the model to Edge TPU format. + +This wiki article will guide you through the process of compiling a model and running it on the Google Coral TPU, enabling you to leverage its capabilities for high-performance machine learning applications. + +### [How to Use Multiple CSI Cameras on reComputer with ROS](https://wiki.seeedstudio.com/csi_camera_on_ros/) + +This tutorial provides a step-by-step guide on how to read multiple CSI camera image data through ROS on [reComputer J30/J40](https://www.seeedstudio.com/reComputer-J4012-p-5586.html) series devices and publish image topics to be displayed in the RVIZ visualization interface. + +### [Recording and playback for Respeaker Lite](https://wiki.seeedstudio.com/respeaker_record_and_play/) + +This project demonstrates a basic loopback mechanism using the I2S interface, to test the reading and writing functions of I2S audio data. By switching I2S mode, the audio data is read from the microphone and then written to the speaker. + +### [How to Use NVStreamer for RTSP Streaming on reComputer with Jetson Platform Services](https://wiki.seeedstudio.com/getting_started_with_nvstreamer/) + +[NVStreamer](https://docs.nvidia.com/moj/nvstreamer/moj-nvstreamer.html) is a software developed by NVIDIA that can store and serve video files, which can then be streamed using the RTSP protocol. It is particularly useful for testing with VST, as it provides an alternative method to cameras for creating video sources as input for VST. Specifically, it offers a mechanism to use specific video files as input for VST testing. VST can be configured to receive RTSP streams as if they were coming from ONVIF-S cameras. + + +## Existed Wiki Updated + +### [XIAO ESP32C3 WiFi Usage](https://wiki.seeedstudio.com/XIAO_ESP32C3_WiFi_Usage/) + +We've added examples of [WiFi Usage](https://wiki.seeedstudio.com/XIAO_ESP32C3_WiFi_Usage/#scan-wi-fi-access-points). + +### [XIAO Pin Multiplexing](https://wiki.seeedstudio.com/XIAO_ESP32C3_Pin_Multiplexing/) + +We've added examples of [XIAO ESP32C3 Serial1 Usage](https://wiki.seeedstudio.com/XIAO_ESP32C3_Pin_Multiplexing/#serial1-usage). + +We've added examples of [XIAO ESP32C6 Serial1 Usage](https://wiki.seeedstudio.com/xiao_pin_multiplexing_esp33c6/#serial1-usage). + +We've added examples of [XIAO ESP32S3 Serial1 Usage](https://wiki.seeedstudio.com/xiao_esp32s3_pin_multiplexing/#serial1-usage). + + + + + +## The Efforts of Contributor + + + +- Check on [GitHub](https://github.com/orgs/Seeed-Studio/projects/6) for more information. +- We will be really appreciate if you can [share your ideas](https://github.com/orgs/Seeed-Studio/projects/6?pane=issue&itemId=35179519) with us! + + +## Past Weekly wiki + +
Click here + +- [weekly wiki on 2.27th](/Seeed_Elderly/weekly_wiki/wiki227) +- [weekly wiki on 3.06th](/Seeed_Elderly/weekly_wiki/wiki306) +- [weekly wiki on 3.13th](/Seeed_Elderly/weekly_wiki/wiki313) +- [weekly wiki on 3.20th](/Seeed_Elderly/weekly_wiki/wiki320) +- [weekly wiki on 3.27th](/Seeed_Elderly/weekly_wiki/wiki327) +- [weekly wiki on 4.03rd](/Seeed_Elderly/weekly_wiki/wiki403) +- [weekly wiki on 4.10th](/Seeed_Elderly/weekly_wiki/wiki410) +- [weekly wiki on 4.17th](/Seeed_Elderly/weekly_wiki/wiki417) +- [weekly wiki on 4.24th](/Seeed_Elderly/weekly_wiki/wiki424) +- [weekly wiki on 5.15th](/Seeed_Elderly/weekly_wiki/wiki515) +- [weekly wiki on 5.22nd](/Seeed_Elderly/weekly_wiki/wiki522) +- [weekly wiki on 5.29th](/Seeed_Elderly/weekly_wiki/wiki529) +- [weekly wiki on 6.05th](/Seeed_Elderly/weekly_wiki/wiki605) +- [weekly wiki on 6.12th](/Seeed_Elderly/weekly_wiki/wiki612) +- [weekly wiki on 6.19th](/Seeed_Elderly/weekly_wiki/wiki619) +- [weekly wiki on 7.03th](/Seeed_Elderly/weekly_wiki/wiki703) +- [weekly wiki on 7.10th](/Seeed_Elderly/weekly_wiki/wiki710) +- [weekly wiki on 7.17th](/Seeed_Elderly/weekly_wiki/wiki717) +- [weekly wiki on 7.24th](/Seeed_Elderly/weekly_wiki/wiki724) +- [weekly wiki on 7.31th](/Seeed_Elderly/weekly_wiki/wiki731) +- [weekly wiki on 8.07th](/Seeed_Elderly/weekly_wiki/wiki807) +- [weekly wiki on 8.21st](/Seeed_Elderly/weekly_wiki/wiki821) +- [weekly wiki on 8.28th](/Seeed_Elderly/weekly_wiki/wiki828) +- [weekly wiki on 9.11st](/Seeed_Elderly/weekly_wiki/wiki911) +- [weekly wiki on 9.18th](/Seeed_Elderly/weekly_wiki/wiki918) +- [weekly wiki on 9.25th](/Seeed_Elderly/weekly_wiki/wiki925) +- [weekly wiki on 10.9th](/Seeed_Elderly/weekly_wiki/wiki1009) +- [weekly wiki on 10.16th](/Seeed_Elderly/weekly_wiki/wiki1016) +- [weekly wiki on 10.23th](/Seeed_Elderly/weekly_wiki/wiki1023) +- [weekly wiki on 10.30th](/Seeed_Elderly/weekly_wiki/wiki1030) +- [weekly wiki on 11.06th](/Seeed_Elderly/weekly_wiki/wiki1106) +- [weekly wiki on 11.13th](/Seeed_Elderly/weekly_wiki/wiki1113) +- [weekly wiki on 11.20th](/Seeed_Elderly/weekly_wiki/wiki1120) +- [weekly wiki on 11.27th](/Seeed_Elderly/weekly_wiki/wiki1127) +- [weekly wiki on 12.04th](/Seeed_Elderly/weekly_wiki/wiki1204) +- [weekly wiki on 12.11th](/Seeed_Elderly/weekly_wiki/wiki1211) +- [weekly wiki on 12.18th](/Seeed_Elderly/weekly_wiki/wiki1218) +- [weekly wiki on 12.25th](/Seeed_Elderly/weekly_wiki/wiki1225) +- [weekly wiki on 2024.1.08th](/Seeed_Elderly/weekly_wiki/wiki240108) +- [weekly wiki on 2024.1.15th](/Seeed_Elderly/weekly_wiki/wiki240115) +- [weekly wiki on 2024.1.22nd](/Seeed_Elderly/weekly_wiki/wiki240122) +- [weekly wiki on 2024.1.29th](/Seeed_Elderly/weekly_wiki/wiki240129) +- [weekly wiki on 2024.2.19th](/Seeed_Elderly/weekly_wiki/wiki240219) +- [weekly wiki on 2024.2.26th](/Seeed_Elderly/weekly_wiki/wiki240226) +- [weekly wiki on 2024.3.04th](/Seeed_Elderly/weekly_wiki/wiki240304) +- [weekly wiki on 2024.3.11th](/Seeed_Elderly/weekly_wiki/wiki240311) +- [weekly wiki on 2024.3.18th](/Seeed_Elderly/weekly_wiki/wiki240318) +- [weekly wiki on 2024.3.25th](/Seeed_Elderly/weekly_wiki/wiki240325) +- [weekly wiki on 2024.4.01st](/Seeed_Elderly/weekly_wiki/wiki240401) +- [weekly wiki on 2024.4.08th](/Seeed_Elderly/weekly_wiki/wiki240408) +- [weekly wiki on 2024.4.15th](/Seeed_Elderly/weekly_wiki/wiki240415) +- [weekly wiki on 2024.4.22nd](/Seeed_Elderly/weekly_wiki/wiki240422) +- [weekly wiki on 2024.4.29th](/Seeed_Elderly/weekly_wiki/wiki240429) +- [weekly wiki on 2024.5.06th](/Seeed_Elderly/weekly_wiki/wiki240506) +- [weekly wiki on 2024.5.13th](/Seeed_Elderly/weekly_wiki/wiki240513) +- [weekly wiki on 2024.5.20th](/Seeed_Elderly/weekly_wiki/wiki240520) +- [weekly wiki on 2024.5.27th](/Seeed_Elderly/weekly_wiki/wiki240527) +- [weekly wiki on 2024.6.03rd](/Seeed_Elderly/weekly_wiki/wiki240603) +- [weekly wiki on 2024.6.10th](/Seeed_Elderly/weekly_wiki/wiki240610) +- [weekly wiki on 2024.6.17th](/Seeed_Elderly/weekly_wiki/wiki240617) +- [weekly wiki on 2024.6.24th](/Seeed_Elderly/weekly_wiki/wiki240624) +- [weekly wiki on 2024.7.01st](/Seeed_Elderly/weekly_wiki/wiki240701) +- [weekly wiki on 2024.7.08th](/Seeed_Elderly/weekly_wiki/wiki240708) +- [weekly wiki on 2024.7.16th](/Seeed_Elderly/weekly_wiki/wiki240716) +- [weekly wiki on 2024.7.22th](/Seeed_Elderly/weekly_wiki/wiki240722) + +
+ diff --git a/docs/Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_ESP32C3/XIAO_ESP32C3_Pin_Multiplexing.md b/docs/Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_ESP32C3/XIAO_ESP32C3_Pin_Multiplexing.md index d2668e80c6fc..24a386dd7903 100644 --- a/docs/Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_ESP32C3/XIAO_ESP32C3_Pin_Multiplexing.md +++ b/docs/Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_ESP32C3/XIAO_ESP32C3_Pin_Multiplexing.md @@ -321,7 +321,7 @@ According to the above XIAO ESP32C3 Pin diagrams for specific parameters,we can Core Function that need to be include: - `Serial1.begin(BAUD,SERIAL_8N1,RX_PIN,TX_PIN);` -- enalbe Serial1,the function prototype : `.begin(unsigned long baud, uint32_t config, int8_t rxPin, int8_t txPin);` - - `baud` :badu rate + - `baud` :baud rate - `config`:Configuration bit - `rxPin` :Receive Pin - `txPin` :Send Pin diff --git a/docs/weekly_wiki.md b/docs/weekly_wiki.md index 8029e40c31cf..76ccbcea2b81 100644 --- a/docs/weekly_wiki.md +++ b/docs/weekly_wiki.md @@ -5,7 +5,7 @@ keywords: - weeely wiki image: https://files.seeedstudio.com/wiki/IndexWiki/logo_image.jpg last_update: - date: 07/29/2024 + date: 08/05/2024 author: Frank --- @@ -17,98 +17,43 @@ This is Frank in Seeed Studio and welcome to the Seeed Studio weekly wiki! Each ✨ For each week, when a collaborator contributes a project or fixes something important, we put the stars at the end of title of "Weekly Wiki" for more people be able to see their efforts👍. -Today is July 29th and a brand new week has begun! Check out what Seeed Studio did last week! +Today is August 5th and a brand new week has begun! Check out what Seeed Studio did last week! ## Latest Wiki Launched -### [SenseCAP Watcher as a Grove sensor](https://wiki.seeedstudio.com/watcher_as_grove/) +### [Watcher To WhatsApp](https://wiki.seeedstudio.com/watcher_node_red_to_whatsapp/) -
+
-In this wiki, we will explore the exciting possibilities that arise when Watcher, acting as a Grove sensor, leverages its UART (Universal Asynchronous Receiver/Transmitter) functionality. By enabling UART communication, Watcher can transmit valuable data such as captured images and recognition results through its UART interface, located on the back of the device. This opens up a world of opportunities for integrating Watcher with various hardware platforms and creating innovative applications. +**WhatsApp** is an instant messaging and voice-over-IP service owned by Meta. It enables users to send text, voice, and video messages, make voice and video calls, and share images, documents, locations, and other content. -### [Watcher & Node-RED To Kafka Quick Start](https://wiki.seeedstudio.com/watcher_node_red_to_kafka/) +This tutorial will guide you through integrating the Watcher API with Node-RED to seamlessly send data from the Watcher to WhatsApp. This integration provides a simple and efficient method to **receive notifications and opens the door for further applications and integrations**. -
+### [Local AI Assistant : Deploy Ollama and AnytingLLM on Jetson](https://wiki.seeedstudio.com/local_ai_ssistant/) -Apache Kafka is a distributed event streaming platform designed for high-throughput, fault-tolerant data processing. It enables real-time data feeds by allowing producers to publish messages to topics, while consumers can subscribe to these topics to process the data. Kafka is widely used for building data pipelines, real-time analytics, and integrating various data sources. Its robust architecture ensures scalability and durability, making it a popular choice for modern data-driven applications. - -Why use Docker? Because Docker can simulate the environment of multiple computers on a single machine and deploy applications with great ease. Therefore, in this project, we will use Docker to set up the environment and improve efficiency. - -### [T1000-E Tracker for Meshtastic](https://wiki.seeedstudio.com/sensecap_t1000_e/) - -

pir

- -
- - Get One Now 🖱️ - -
- - -It is a high-performance tracker designed for Meshtastic, as small as a credit card, effortlessly fitting in your pocket or attaching to your assets. It embeds Semtech's LR1110, Nordic's nRF52840, and Mediatek's AG3335 GPS module, providing Meshtastic users with a high-precision, low-power positioning and communication solution. - -
- -
- -This wiki provides a tutorial on how to use NVStreamer for RTSP video streaming on [reComputer J4012](https://www.seeedstudio.com/reComputer-J4012-p-5586.html). - -### [How to Run VLM on reComputer with Jetson Platform Services](https://wiki.seeedstudio.com/run_vlm_on_recomputer/) - -VLMs are multi modal models supporting images, video and text and using a combination of large language models and vision transformers. Based on this capability, they are able to support text prompts to query videos and images thereby enabling capabilities such as chatting with the video, and defining natural language based alerts. The [VLM AI service](https://docs.nvidia.com/jetson/jps/inference-services/vlm.html), enables quick deployment of VLMs with Jetson Platform Services for video insight applications. The VLM service exposes REST API endpoints to configure the video stream input, set alerts and ask questions in natural language about the input video stream. - -
- -
- -This wiki provides a tutorial on how to run VLM on [reComputer J4012](https://www.seeedstudio.com/reComputer-J4012-p-5586.html). - -### [How to Run Zero-Shot Detection on reComputer with Jetson Platform Services](https://wiki.seeedstudio.com/run_zero_shot_detection_on_recomputer/) - -Generative AI vision transformers such as CLIP have made it possible to build zero shot detection models capable of open vocabulary object detection. Meaning, the model is not bounded by a set of pre-defined classes to detect. The objects to detect are configured at runtime by the user. The Zero Shot Detection AI service, enables quick deployment of generative AI with Jetson Services for open vocabulary detection on video live stream input. The Zero Shot Detection AI service exposes REST API endpoints to control stream input and objects to detect. +Local AI Assistant is an artificial intelligence application that runs on local hardware and software, offering intelligent interaction and data processing capabilities. It operates independently of cloud services, protecting user privacy while providing quick response times and high levels of customization.
- +
-This wiki provides a tutorial on how to run Zero-Shot Detection on [reComputer J4012](https://www.seeedstudio.com/reComputer-J4012-p-5586.html). - -### [Pose-Based Light Control with Node-Red and Raspberry Pi with AIkit](https://wiki.seeedstudio.com/pose_based_light_control_with_nodered_and_rpi_with_aikit/) - -

pir

- -This wiki will guide you on how to run YOLOv8 using an AI kit, use YOLOv8 to monitor your posture, and ultimately control your lights based on your posture. In this project, a USB camera captures your pose, and yolov8n run on [AI kit](https://www.seeedstudio.com/Raspberry-Pi-AI-Kit-p-5900.html) with [reComputer R1000](https://www.seeedstudio.com/reComputer-R1000-Series-Optional-Accessories.html) to detect your pose. The processed video, displaying the detected pose, is then streamed in real-time to [reTerminal DM](https://www.seeedstudio.com/reTerminal-DM-CM4104032-p-5898.html) using [gstreamer](https://gstreamer.freedesktop.org/). Meanwhile, the joint coordinates are sent using [mqtt](https://mqtt.org/) to [Node-RED](https://nodered.org/) which deploy on the reComputer R1000. At last, the Node-RED flow controls the smart lights based on the joint coordinates. - -### [reComputer R1000 with FIN to create a Equip Graphic](https://wiki.seeedstudio.com/reComputer_r1000_fin_floor_gaphic/) - -FIN Framework (FIN) is a software framework with application suites that can integrate, control, manage, analyze, visualize and connect. Its capabilities can be integrated by OEMs into a range of products and services. - -This article will show you how to use the `Graphics Builder` of FIN Framwork, and to create a `Equip Graphic` using the `Graphics Builder`. - -### [Convert Model to Edge TPU TFlite Format for Google Coral](https://wiki.seeedstudio.com/convert_model_to_edge_tpu_tflite_format_for_google_coral/) - -The [Coral M.2 Accelerator](https://www.seeedstudio.com/Coral-M2-Accelerator-with-Dual-Edge-TPU-p-4681.html) with Dual Edge TPU is an M.2 module that brings two Edge TPU coprocessors to existing systems and products with an available M.2 E-key slot.[Tensorflow](https://www.tensorflow.org/) and [Pytorch](https://pytorch.org/) is the most popular deep learning frameworks. So in order to use the Edge TPU, we need to compile the model to Edge TPU format. - -This wiki article will guide you through the process of compiling a model and running it on the Google Coral TPU, enabling you to leverage its capabilities for high-performance machine learning applications. +In this wiki, we will demonstrate how to set up a local knowledge base on Jetson devices with [ollama](https://ollama.com/) and [AnythingLLM](https://anythingllm.com/). By leveraging the powerful capabilities of large language models, we aim to enhance our work efficiency. -### [How to Use Multiple CSI Cameras on reComputer with ROS](https://wiki.seeedstudio.com/csi_camera_on_ros/) +### [Quick start with Zigbee on XIAO ESP32C6 by Arduino](https://wiki.seeedstudio.com/xiao_esp32c6_zigbee_arduino/) -This tutorial provides a step-by-step guide on how to read multiple CSI camera image data through ROS on [reComputer J30/J40](https://www.seeedstudio.com/reComputer-J4012-p-5586.html) series devices and publish image topics to be displayed in the RVIZ visualization interface. +
-### [Recording and playback for Respeaker Lite](https://wiki.seeedstudio.com/respeaker_record_and_play/) +Zigbee is a widely adopted wireless communication protocol that finds extensive use in home automation, smart energy management, and Internet of Things (IoT) applications. Known for its low power consumption, reliable data transmission, and mesh network capabilities, Zigbee is an excellent choice for building scalable and efficient wireless networks. -This project demonstrates a basic loopback mechanism using the I2S interface, to test the reading and writing functions of I2S audio data. By switching I2S mode, the audio data is read from the microphone and then written to the speaker. +Let's embark on this exciting journey of Zigbee development with the XIAO ESP32C6 and unlock the full potential of this powerful wireless communication protocol! -### [How to Use NVStreamer for RTSP Streaming on reComputer with Jetson Platform Services](https://wiki.seeedstudio.com/getting_started_with_nvstreamer/) +### [reComputer R1000 with FlowFuse](https://wiki.seeedstudio.com/recomputer_r1000_flow_fuse/) -[NVStreamer](https://docs.nvidia.com/moj/nvstreamer/moj-nvstreamer.html) is a software developed by NVIDIA that can store and serve video files, which can then be streamed using the RTSP protocol. It is particularly useful for testing with VST, as it provides an alternative method to cameras for creating video sources as input for VST. Specifically, it offers a mechanism to use specific video files as input for VST testing. VST can be configured to receive RTSP streams as if they were coming from ONVIF-S cameras. +[FlowFuse](https://flowfuse.com/) enhances Node-RED by adding features for collaborative development, managing remote deployments, supporting DevOps delivery pipelines, and hosting Node-RED applications. It serves as a DevOps platform specifically designed for the development and delivery of Node-RED applications, making it easier for teams to work together and deploy their projects efficiently. -## Existed Wiki Updated +