diff --git a/docs/assets/img/getting_started_pics/m5stickv/kflash_gui_01.jpg b/docs/assets/img/getting_started_pics/m5stickv/kflash_gui_01.jpg index 096b39a1..530d35e7 100644 Binary files a/docs/assets/img/getting_started_pics/m5stickv/kflash_gui_01.jpg and b/docs/assets/img/getting_started_pics/m5stickv/kflash_gui_01.jpg differ diff --git a/docs/assets/img/product_pics/core/minicore/m5stickc/m5stickc_05.jpg b/docs/assets/img/product_pics/core/minicore/m5stickc/m5stickc_05.jpg index 436dc13b..559182cf 100644 Binary files a/docs/assets/img/product_pics/core/minicore/m5stickc/m5stickc_05.jpg and b/docs/assets/img/product_pics/core/minicore/m5stickc/m5stickc_05.jpg differ diff --git a/docs/assets/img/product_pics/unit/Fan/unit_fan_01.jpg b/docs/assets/img/product_pics/unit/fan/unit_fan_01.jpg similarity index 100% rename from docs/assets/img/product_pics/unit/Fan/unit_fan_01.jpg rename to docs/assets/img/product_pics/unit/fan/unit_fan_01.jpg diff --git a/docs/assets/img/product_pics/unit/Fan/unit_fan_02.jpg b/docs/assets/img/product_pics/unit/fan/unit_fan_02.jpg similarity index 100% rename from docs/assets/img/product_pics/unit/Fan/unit_fan_02.jpg rename to docs/assets/img/product_pics/unit/fan/unit_fan_02.jpg diff --git a/docs/assets/img/product_pics/unit/Fan/unit_fan_03.jpg b/docs/assets/img/product_pics/unit/fan/unit_fan_03.jpg similarity index 100% rename from docs/assets/img/product_pics/unit/Fan/unit_fan_03.jpg rename to docs/assets/img/product_pics/unit/fan/unit_fan_03.jpg diff --git a/docs/assets/img/product_pics/unit/Fan/unit_fan_04.jpg b/docs/assets/img/product_pics/unit/fan/unit_fan_04.jpg similarity index 100% rename from docs/assets/img/product_pics/unit/Fan/unit_fan_04.jpg rename to docs/assets/img/product_pics/unit/fan/unit_fan_04.jpg diff --git a/docs/assets/img/related_documents/v-training/1.jpg b/docs/assets/img/related_documents/v-training/1.jpg index 58ea99fb..9e0cdfab 100644 Binary files a/docs/assets/img/related_documents/v-training/1.jpg and b/docs/assets/img/related_documents/v-training/1.jpg differ diff --git a/docs/assets/img/related_documents/v-training/v_training.png b/docs/assets/img/related_documents/v-training/v_training.png new file mode 100644 index 00000000..51ed5750 Binary files /dev/null and b/docs/assets/img/related_documents/v-training/v_training.png differ diff --git a/docs/en/app/flir.md b/docs/en/app/flir.md index e9db15c7..30757113 100644 --- a/docs/en/app/flir.md +++ b/docs/en/app/flir.md @@ -28,6 +28,7 @@ The effective image generate by the Lepton sensor is 160×120, but you can proce - Field of view: 56°, with shutter - Lepton Input Supply Voltage: 1.2V，2.8V，2.5V - 3.1V IO - Fast imaging time (< 0.5 second) +- Product Size：54mm x 54mm x 29mm ## Parameter diff --git a/docs/en/app/lidarbot.md b/docs/en/app/lidarbot.md index a1ef099b..76257a26 100644 --- a/docs/en/app/lidarbot.md +++ b/docs/en/app/lidarbot.md @@ -78,9 +78,9 @@ If you are interest in AGV development, We especially encourage you to modify th - + - + >1.EasyLoader is a simple and fast program burner. Every product page in EasyLoader provides a product-related case program. It can be burned to the master through simple steps, and a series of function verification can be performed.(**Currently EasyLoader is only available for Windows OS**) diff --git a/docs/en/core/fire.md b/docs/en/core/fire.md index 2ed5001a..8d83b810 100644 --- a/docs/en/core/fire.md +++ b/docs/en/core/fire.md @@ -35,7 +35,7 @@ The newly-produced M5Core replaces the screen with better display performance an **Notice2:** -There are two versions of IMU sensors (MPU6886 and SH200Q) currently available on the Fire host, which are basically identical in function. +There are two versions of IMU sensors (MPU6886 and SH200Q) currently available on the Fire host, which are basically identical in function.To identify the IMU sensor, you can use python code to scan the I2C address MPU6886(0x68)/SH200Q（0x6c) **Notice3:** diff --git a/docs/en/hat/hat-neoflash.md b/docs/en/hat/hat-neoflash.md new file mode 100644 index 00000000..9861cac9 --- /dev/null +++ b/docs/en/hat/hat-neoflash.md @@ -0,0 +1,86 @@ +# Neoflash HAT {docsify-ignore-all} + + + +*** + +:memo:**[Description](#Description)**    🛒**[Purchase](https://m5stack.com/products/m5stickc-proto-plus-hat)** + + +## Description + +**Neoflash HAT** is + + + + +## Product Features + +- Hole Size: 0.039" 1mm (CNC Drilled) +- Hole Pitch: 0.1 in - (2.54 mm) +- Entire Hole Quantity: 168 Holes + +## Include + +- 1x PROTO PLUS HAT +- 1x 8 pin header（90°） + +## Application + +- Prototyping +- Related work by M5 User: [view](https://www.hackster.io/kiraku-labo/balance-robot-9009db) + + + +## Video + +**Demo** + + + + +## Code + +*To get complete code, please click [here](https://github.com/ShashaDDD/EC11Encoder).* + +```arduino +#include +#include +#include +#include "RotaryEncoderWithButton.h" + + +//#include + +//RotaryEncoderWithButton rotary(2,3,4); +RotaryEncoderWithButton rotary(26,36,0); + +uint32_t data; +int i; +void t1Callback(); +Task t1(5, TASK_FOREVER, &RotaryEncoderWithButton::ReadAB); +Scheduler runner; + +void setup() { + M5.begin(); + Serial.begin(115200); + rotary.begin(); + + runner.init(); + runner.addTask(t1); + + delay(100); + t1.enable(); + +} + +void loop() { + runner.execute(); +} +``` + + + + diff --git a/docs/en/related_documents/v-training.md b/docs/en/related_documents/v-training.md index 59ddcab9..55f568e2 100644 --- a/docs/en/related_documents/v-training.md +++ b/docs/en/related_documents/v-training.md @@ -1,20 +1,27 @@ # V-Training {docsify-ignore-all} -**[1. Download Firmware](#Download-Firmware)** + -**[2. Flash Firmware](#Flash-Firmware)** +**[1. Burner Firmware](#Burner-Firmware)** + +**[2. Insert SD Card](#Insert-SD-Card)** **[3. Material Training](#Material-Training)** **[4. Upload Data to Cloud](#Upload-Data-to-Cloud)** -**[5. Run Recognition Program](#Run-Recognition-Program)** +**[5. Download Model](#Download-Model)** + +**[6. Run Recognition Program](#Run-Recognition-Program)** -

Users who have already programmed the firmware should start directly from the third step.

-## EasyLoader optional +## Burner Firmware + +

Users who have already programmed the firmware should start directly from the Second step.

+ +### EasyLoader optional @@ -24,15 +31,13 @@ >2, After downloaded , double click to run the app, connect the device to computer via USB cable, select the com port number, then click "Burn" to start it. -## Download Firmware optional +### Download Firmware optional > EasyLoader is only Window-supported. If you don't have a Windows computer or you would like to download specific file to flash , please use "Kflash, download firmware below " -## Flash Firmware - >1, Select Kflash_GUI flash tool for your computer OS.
@@ -53,12 +58,11 @@ ## Material Training - ### boot code > Material Training requires SD cards, users could downloade boot code zip files, unzip the files to SD card.(M5StickC only recognized certain type of SD card , [click to see the supported type](en/core/m5stickv?id=sd-card-test)) - + @@ -80,7 +84,7 @@ note：In order to reach a certain accuracy, each Class should contains at least 35 pictures, or the Could Training would give out a rejection -## Material Checking and Compress +### Material Checking and Compress >After finish the shooting, shut down the device, take out SD card, put the photos materials into "train" and "vaild" folder. Copy to your computer. @@ -102,15 +106,17 @@ ->After training accomplished, code file will sent to your personal e-mail, copy the download link to download the file to your computer. +## Download Model + +>After training accomplished, code file will sent to your personal e-mail, copy the download link to download the file to your computer.Unzip the file, copy it to SD card, keep the SD card in the M5StickV + + ## Run Recognition Program ->Unzip the file, copy it to SD card, keep the SD card in the M5StickV, power on to run the progarm automatically. - - +>power on to run the progarm automatically. diff --git a/docs/en/unit/vibrator.md b/docs/en/unit/vibrator.md index 1a319a07..b9033f36 100644 --- a/docs/en/unit/vibrator.md +++ b/docs/en/unit/vibrator.md @@ -39,6 +39,7 @@ These days miniature vibrating motors are used in a wide range of products, not ## Schematic + diff --git a/docs/zh_CN/app/flir.md b/docs/zh_CN/app/flir.md index 5664a4be..70d8f710 100644 --- a/docs/zh_CN/app/flir.md +++ b/docs/zh_CN/app/flir.md @@ -25,6 +25,7 @@ - Field of view: 56°, with shutter - Lepton 输入电源电压: 1.2V，2.8V，2.5V - 3.1V IO - 快速成像 (< 0.5 second) +- 产品尺寸：54mm x 54mm x 29mm ## 参数 diff --git a/docs/zh_CN/app/lidarbot.md b/docs/zh_CN/app/lidarbot.md index dcd3e8d2..40caeced 100644 --- a/docs/zh_CN/app/lidarbot.md +++ b/docs/zh_CN/app/lidarbot.md @@ -79,9 +79,9 @@ - + - + >1.EasyLoader是一个简洁快速的程序烧录器，每一个产品页面里的EasyLoader都提供了一个与产品相关的案例程序.**(目前EasyLoader仅适用于Windows操作系统)** diff --git a/docs/zh_CN/core/fire.md b/docs/zh_CN/core/fire.md index 9b011098..e10b47b9 100644 --- a/docs/zh_CN/core/fire.md +++ b/docs/zh_CN/core/fire.md @@ -36,7 +36,7 @@ M5Stack Fire 配有三个可分离部件. 顶部与其他的M5主机一样，放 **注意2:** -目前发售的Fire主机存在两种IMU传感器版本（MPU6886与SH200Q），它们在功能上基本一致. +目前发售的Fire主机存在两种IMU传感器版本（MPU6886与SH200Q），它们在功能上基本一致.要识别IMU传感器，可以使用python代码扫描I2C地址 MPU6886(0x68)/SH200Q（0x6c) **注意3：** diff --git a/docs/zh_CN/hat/hat-neoflash.md b/docs/zh_CN/hat/hat-neoflash.md new file mode 100644 index 00000000..43986ace --- /dev/null +++ b/docs/zh_CN/hat/hat-neoflash.md @@ -0,0 +1,66 @@ +# Neoflash HAT {docsify-ignore-all} + + + +*** + +:memo:**[描述](#描述)**     🛒**[购买链接](https://m5stack.com/products/m5stickc-proto-plus-hat)**  + + +## 描述 + +**Neoflash HAT** 是一款专为M5SticKC设计的矩阵RGB LED灯板.这块尺寸面积仅有pass*pass的PCB板总共嵌入了126颗可编程RGB LED灯，除了实现一般的灯光效果以外，高密度矩阵设计的它还可以作为一个小型点阵LED显示屏使用. + +提供两种安装方式， + +除了已经焊接完成的平行排针以外.90°弯曲排针. + +在使用灯板制作一些数据显示应用时，使用配套的黑茶色亚克力板，能够有效增强显示效果. + +如果你打算为你的项目添加一个精致小巧的LED矩阵屏幕的话，Neoflash HAT 会是一个不错的选择. + + + + +## 产品特性 + +- 单像素点的三基色颜色： + - 可实现256级亮度显示 + - 完成16777216种颜色的全真色彩显示. +- 孔尺寸: 0.039" 1mm (CNC工艺) +- 孔间距: 0.1 in - (2.54 mm) +- RGB LED数量: 126 个 + + +## 重量尺寸 + +- 单品尺寸：54mm x 23.5mm x 1mm +- 单品重量：2g + +## 包含 + +- 1x Neoflash HAT +- 2x 8 pin 排针（90°） +- 1x 黑茶色亚克力板 +- 2x 15cm导线(71号、0.4mm) + +## 应用 + +- LED矩阵显示屏 +- 数字时钟 + + +## 相关视频 + + + +## 例程 + +*以下代码仅为片段，如需获取完整代码，[请点击此处.](https://github.com/ShashaDDD/EC11Encoder).* + +```arduino +#include + +``` \ No newline at end of file diff --git a/docs/zh_CN/hat/hat-proto-plus.md b/docs/zh_CN/hat/hat-proto-plus.md index 14850b09..2a119178 100644 --- a/docs/zh_CN/hat/hat-proto-plus.md +++ b/docs/zh_CN/hat/hat-proto-plus.md @@ -10,7 +10,7 @@ ## 描述 -**PROTO PLUS HAT** 是一款兼容M5SticKC的万能板.相比前代产品PROTO HAT，"PLUS"在设计上提供了更大的电路板面积. 结合配套的8 pin 排针能够将M5StickC顶部的拓展接口全部连接至万能板内，使得用户可以自由的在板上进行电路设计. 90°形状的排针能够使万能板以多种角度与M5StickC进行拼接.如果你打算为你的项目添加简单的电路设计并希望通过改变电路板的拼接方式以达到节省空间的目的, HAT PROTO PLUS 会是一个不错的选择. +**PROTO PLUS HAT** 是一款兼容M5SticKC的万能板.相比前代产品PROTO HAT，"PLUS"在设计上提供了更大的电路板面积. 结合配套的8 pin 排针能够将M5StickC顶部的拓展接口全部连接至万能板内，使得用户可以自由的在板上进行电路设计. 90°排针能够使万能板以多种角度与M5StickC进行拼接.如果你打算为你的项目添加简单的电路设计并希望通过改变电路板的拼接方式以达到节省空间的目的, HAT PROTO PLUS 会是一个不错的选择. diff --git a/docs/zh_CN/related_documents/v-training.md b/docs/zh_CN/related_documents/v-training.md index 9423e183..0fc22190 100644 --- a/docs/zh_CN/related_documents/v-training.md +++ b/docs/zh_CN/related_documents/v-training.md @@ -1,20 +1,26 @@ # V-Training {docsify-ignore-all} -**[1. 下载固件](#下载固件)** + -**[2. 烧录固件](#烧录固件)** +**[1. 烧录固件](#烧录固件)** + +**[2. 插入SD卡](#使用SD卡)** **[3. 训练素材拍摄](#训练素材拍摄)** **[4. 数据上传云端](#数据上传云端)** -**[5. 运行识别程序](#运行识别程序)** +**[5. 下载识别模型](#下载识别模型)** + +**[6. 运行识别程序](#运行识别程序)** -

已经烧录了固件程序的用户请直接从第三步开始

+## 烧录固件 -## EasyLoader 可选 +

已经烧录了固件程序的用户请直接从第二步开始

+ +### EasyLoader 可选 @@ -24,14 +30,13 @@ >2.下载软件后，双击运行应用程序，将M5设备通过数据线连接至电脑,选择端口参数，点击 **"Burn"** 即可开始烧录 -## 下载固件 可选 +### 下载固件 > 需要指定烧录文件的用户可以选用**Kflash**进行固件烧录. - -## 烧录固件 +### Kflash GUI >1.点击下方对应自己操作系统的 Kflash_GUI烧录工具进行下载. @@ -43,7 +48,7 @@ Linux

->2.将设备通过Tpye-C数据线连接至电脑，双击打开烧录工具**Kflash_GUI**应用程序,选择对应的设备端口、开发板类型(M5StickV)、固件程序、波特率. 点击下载，开始烧录 . +>2.将设备通过Tpye-C数据线连接至电脑，双击打开**Kflash_GUI**应用程序,选择对应的设备端口、开发板类型(M5StickV)、固件程序、波特率. 点击下载，开始烧录 . @@ -51,17 +56,20 @@ >3.对于习惯使用命令行操作的用户来说还可以选择Kflash作为固件烧录工具.[点击此处查看详情](https://github.com/kendryte/kflash.py) -## 训练素材拍摄 +## 插入SD卡 ### boot程序 > 拍摄训练素材需要使用到SD卡，用户需下载boot程序压缩包，并将压缩包内的所有文件解压放置到SD卡中（M5StickV对SD卡的选型有所要求，[点击此处查看支持类型](zh_CN/core/m5stickv?id=sd卡测试)） - + + +## 训练素材拍摄 + ### 素材拍摄 >开机前插入SD卡，用于储存图片素材，长按左侧电源键进行开机，当屏幕出现，如下图Training字样时，则表示成功进入拍摄程序. @@ -81,7 +89,7 @@ 注意：为了保证识别的准确率，每组Class拍摄素材张数需要超过35张，否则在进行云端训练时将不给予通过. 素材的数量越多，识别训练的效果越好，识别率越高 -## 素材检查与压制 +### 素材检查与压制 >素材拍摄完成后，将M5StickV关机，取出SD卡，通过读卡器将SD中的图片素材（"train"、"vaild"两个文件夹），复制至电脑端. @@ -101,15 +109,19 @@ ->等待训练完成，程序文件下载地址将会以邮件的形式发送到上传文件时预留的邮箱中去.复制邮件中的下载地址，下载程序文件到本地. + +## 下载识别模型 + +>等待训练完成，程序文件下载地址将会以邮件的形式发送到上传文件时预留的邮箱中去.复制邮件中的下载地址，下载程序文件到本地进行解压，并复制到SD卡中去. + + ## 运行识别程序 ->将下载好的程序文件压缩包解压，并复制到SD卡中去，最后将SD卡插入M5StickV，开机即可自动运行程序. +>最后将SD卡插入M5StickV，开机即可自动运行程序. - diff --git a/docs/zh_CN/unit/vibrator.md b/docs/zh_CN/unit/vibrator.md index 1a7881b8..40f15f65 100644 --- a/docs/zh_CN/unit/vibrator.md +++ b/docs/zh_CN/unit/vibrator.md @@ -29,7 +29,7 @@ ## 原理图 - + ## EasyLoader