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add UNIT-V
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@@ -47,6 +47,12 @@
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<img src="assets/img/related_documents/UIFlow_Desktop_IDE/Desktop_IDE_05.jpg">
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!>If you are using M5StickC, please follow the instructions below
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>Press and hold the power key on the left side of the fuselage for 2 seconds to start the machine. After the uiflow logo appears, quickly click the home key (center M5 key) to enter the configuration page. Press the button on the right side of the fuselage to switch the option to setting, and press home to confirm. Press the right key to switch to USB mode, press home key to confirm, enter USB programming mode, select the corresponding COM port and device in IDE, and click Connect.
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<img src="assets/img/related_documents/UIFlow_Desktop_IDE/Desktop_IDE_00.jpg">
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## Example
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>After the connection is completed, you can start programming. Drag and drop the block in the block list on the left to the programming area. After editing the program, click the Run button in the upper right corner to execute the program..
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@@ -268,7 +268,7 @@ Stop timer.
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<img src="assets/img/related_documents/UIFlow_Desktop_IDE/Desktop_IDE_05.jpg">
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!>If you are using m5stickc, please follow the instructions below
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!>If you are using M5StickC, please follow the instructions below
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>Press and hold the power key on the left side of the fuselage for 2 seconds to start the machine. After the uiflow logo appears, quickly click the home key (center M5 key) to enter the configuration page. Press the button on the right side of the fuselage to switch the option to setting, and press home to confirm. Press the right key to switch to USB mode, press home key to confirm, enter USB programming mode, select the corresponding COM port and device in IDE, and click Connect.
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+63
-99
@@ -1,36 +1,17 @@
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# UNIT-V {docsify-ignore-all}
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<img src="assets\img\product_pics\unit\unit-v/unit_v_01.jpg" width="30%" height="30%">
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<img src="assets\img\product_pics\unit\unit-v/unit_v_02.jpg" width="30%" height="30%">
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<img src="assets\img\product_pics\unit\unit-v/unit_v_03.jpg" width="30%" height="30%">
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<img src="assets/img/product_pics/unit/unit-v/unit_v_01.webp" width="30%" height="30%">
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<img src="assets/img/product_pics/unit/unit-v/unit_v_02.webp" width="30%" height="30%">
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<img src="assets/img/product_pics/unit/unit-v/unit_v_04.webp" width="30%" height="30%">
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***
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:memo:**[Description](#Description)** :bulb:**[Quick Start](en/quick_start/unit-v/unit-v_quick_start)** :electric_plug:**[Schematic](#Schematic)** 🛒**[Purchase](https://m5stack.com/collections/m5-unit/products/unit-v)** <img src="https://m5stack.oss-cn-shenzhen.aliyuncs.com/image/EasyLoader_logo-min.jpg">**[EasyLoader](#EasyLoader)** :camera:**[V-Training](en/related_documents/v-training)**
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:memo:**[Description](#Description)** 🛒**[Purchase](https://m5stack.com/collections/m5-unit/products/unit-v)** :clapper:**[Videos](#Videos)**
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## Description
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**UNIT-V** is the new AI Camera powered by Kendryte K210 .An edge computing system-on-chip(SoC) with dual-core 64bit RISC-V CPU and state-of-art neural network processor.
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<br><br>
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UNIT-V AI Camera features its integration with machine vision capabilities, featuring the unprocessed acceptability to AI Visioning with high energy efficiency and low cost. We co-oped with Sipeed providing the MicroPython environment makes programming on UNIT-V easier.
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<br><br>
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Support MicroPython development environment, which makes the program code more concise when you use uint-v for project development.
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<br><br>
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Equipped with OV2640 (2 megapixel) image sensor, it is an ideal choice for machine vision project.
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<br><br>
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It is equipped with two programmable keys and an RGB LED indicator on the front for convenient status display.
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<br><br>
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At the bottom, there is a PH2.0*4P interface and a type-C interface compatible with grove, which is convenient to connect with the main controllor.
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<br><br>
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Support TF card to expand memory, related material and model file call more convenient.
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<img src="assets\img\product_pics\unit\unit-v/unit_v_04.jpg" width="30%" height="30%">
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<img src="assets\img\product_pics\unit\unit-v/unit_v_05.jpg" width="30%" height="30%">
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<img src="assets\img\product_pics\unit\unit-v/unit_v_06.jpg" width="30%" height="30%"><br>
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**UNIT-V** is the new AI Camera powered by Kendryte K210 .An edge computing system-on-chip(SoC) with dual-core 64bit RISC-V CPU and state-of-art neural network processor.UNIT-V AI Camera features its integration with machine vision capabilities, featuring the unprocessed acceptability to AI Visioning with high energy efficiency and low cost. We co-oped with Sipeed providing the MicroPython environment makes programming on UNIT-V easier.
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Support MicroPython development environment, which makes the program code more concise when you use UNIT-V for project development.Equipped with OV2640 (2 megapixel) image sensor, it is an ideal choice for machine vision project.It is equipped with two programmable keys and an RGB LED indicator on the front for convenient status display.At the bottom, there is a PH2.0*4P interface and a type-C interface compatible with grove, which is convenient to connect with the main controllor. Support TF card to expand memory, related material and model file call more convenient.
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### Features:
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- Dual-Core 64-bit RISC-V RV64IMAFDC (RV64GC) CPU / 400Mhz(Normal)
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@@ -51,17 +32,67 @@ Support TF card to expand memory, related material and model file call more conv
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- External storage: TF card/Micro SD
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- Interface: PH2.0/compatible GROVE
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### Applications/What can UNIT-V do?
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- Face recognition/detection
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- Object detection/classification
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- Obtaining size and coordinates of the target in real-time
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- Obtaining the type of detected target in real-time
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- Shape recognition
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- Video recoder
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### Size and Weight
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- Size: 4mm * 2.5mm * 1.5mm
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- Weight: 4g
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### Package Includes
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- 1x UNIT-V(include connecting cable)
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- 1x UNIT-V(include connecting cable)
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### About KENDRYTE K210
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The Kendryte K210 is a system-on-chip (SoC) that integrates machine vision. Using TSMC’s ultra-low-power 28-nm advanced process with dualcore 64-bit processors for better power efficiency, stability and reliability. The SoC strives for ”zero threshold” development and to be deployable in the user’s products in the shortest possible time, giving the product artificial intelligence
|
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- Machine Vision
|
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- Better low power vision processing speed and accuracy
|
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- KPU high performance Convolutional Neural Network (CNN) hardware accelerator
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- Advanced TSMC 28nm process, temperature range -40°C to 125°C
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- Firmware encryption support
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- Unique programmable IO array maximises design flexibility
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- Low voltage, reduced power consumption compared to other systems with the same processing power
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- 3.3V/1.8V dual voltage IO support eliminates need for level shifters
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The chip contains a high-performance, low power RISC-V ISA-based dual core 64-bit CPU with the following features:
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- Core Count: Dual-core processor
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- Bit Width: 64-bit CPU 400MHz
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- Frequency: 400MHz
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- ISA extensions: IMAFDC
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- FPU: Double Precision
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- Platform Interrupts: PLIC
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- Local Interrupts: CLINT
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- I-Cache: 32KiB x 2
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- D-Cache: 32KiB x 2
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- On-Chip SRAM: 8MiB
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### About OV2640
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- Output Formats(8-bit):
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- YUV(422/420)/YCbCr422
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- RGB565/555
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- 8-bit compressed data
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- 8-/10-bit Raw RGB data
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- Maximum Image Transfer Rate according to specific format
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- UXGA/SXGA: 15fps
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- SVGA: 30fps
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- CIF: 60fps
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- Scan Mode: Progressive
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- Camera specifications
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- CCD size : 1/4 inch
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- Field of View : 65 degree
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- Maxmium Pixel: 2M
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### SD card test
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UNIT-V does not currently recognize all types of MicroSD cards. We have tested some common SD cards. The test results are as follows.
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<img src="assets\img\product_pics\unit\unit-v/unit_v_08.jpg" width="30%" height="30%"><br>
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<img src="assets\img\product_pics\unit\unit-v/unit-v-08.jpg" width="40%" height="40%"><br>
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<table class="table_center">
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<tr style="font-weight:bold" >
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@@ -170,80 +201,13 @@ UNIT-V does not currently recognize all types of MicroSD cards. We have tested s
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</tr>
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</table>
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## EasyLoader
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<img src="https://m5stack.oss-cn-shenzhen.aliyuncs.com/image/EasyLoader_logo.png" width="100px" style="margin-top:20px">
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<a href="https://m5stack.oss-cn-shenzhen.aliyuncs.com/EasyLoader/M5Core/M5StickV/EasyLoader_M5StickV_1022_beta.exe"><button type="button" class="btn btn-primary">click to download EasyLoader</button></a>
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>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**)
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>2.After downloading the software, double-click to run the application, connect the M5 device to the computer via the data cable, select the port parameters, and click **"Burn"** to start burning.
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### FUNCTIONAL DESCRIPTION
|
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#### 1.1 KENDRYTE K210
|
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The Kendryte K210 is a system-on-chip (SoC) that integrates machine vision. Using TSMC’s ultra-low-power 28-nm advanced process with dualcore 64-bit processors for better power efficiency, stability and reliability. The SoC strives for ”zero threshold” development and to be deployable in the user’s products in the shortest possible time, giving the product artificial intelligence<br><br>
|
||||
- Machine Vision
|
||||
- Better low power vision processing speed and accuracy
|
||||
- KPU high performance Convolutional Neural Network (CNN) hardware accelerator
|
||||
- Advanced TSMC 28nm process, temperature range -40°C to 125°C
|
||||
- Firmware encryption support
|
||||
- Unique programmable IO array maximises design flexibility
|
||||
- Low voltage, reduced power consumption compared to other systems with the same processing power
|
||||
- 3.3V/1.8V dual voltage IO support eliminates need for level shifters
|
||||
|
||||
The chip contains a high-performance, low power RISC-V ISA-based dual core 64-bit CPU with the following features:
|
||||
|
||||
- Core Count: Dual-core processor
|
||||
- Bit Width: 64-bit CPU 400MHz
|
||||
- Frequency: 400MHz
|
||||
- ISA extensions: IMAFDC
|
||||
- FPU: Double Precision
|
||||
- Platform Interrupts: PLIC
|
||||
- Local Interrupts: CLINT
|
||||
- I-Cache: 32KiB x 2
|
||||
- D-Cache: 32KiB x 2
|
||||
- On-Chip SRAM: 8MiB
|
||||
|
||||
|
||||
#### 1.2 OV2640
|
||||
- Output Formats(8-bit):
|
||||
- YUV(422/420)/YCbCr422
|
||||
- RGB565/555
|
||||
- 8-bit compressed data
|
||||
- 8-/10-bit Raw RGB data
|
||||
- Maximum Image Transfer Rate according to specific format
|
||||
- UXGA/SXGA: 15fps
|
||||
- SVGA: 30fps
|
||||
- CIF: 60fps
|
||||
- Scan Mode: Progressive
|
||||
- Camera specifications
|
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- CCD size : 1/4 inch
|
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- Field of View : 65 degree
|
||||
- Maxmium Pixel: 2M
|
||||
|
||||
|
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## Applications/What can UNIT-V do?
|
||||
- Face recognition/detection
|
||||
- Object detection/classification
|
||||
- Obtaining size and coordinates of the target in real-time
|
||||
- Obtaining the type of detected target in real-time
|
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- Shape recognition
|
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- Video/Display
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- Game simulator
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## Links
|
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- **Web page** - [sipeed](https://maixpy.sipeed.com/en/)
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- **Quick Start Guide** - [M5StickV Guide](https://docs.m5stack.com/#/en/quick_start/m5stickv/m5stickv_quick_start)
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- **Github** - [API](https://github.com/sipeed/MaixPy/tree/master/projects/maixpy_m5stickv)
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- **datasheet** - [K210](https://m5stack.oss-cn-shenzhen.aliyuncs.com/resource/docs/datasheet/core/kendryte_datasheet_en.pdf)
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- **datasheet**
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- [K210]](https://m5stack.oss-cn-shenzhen.aliyuncs.com/resource/docs/datasheet/core/kendryte_datasheet.pdf)
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## Schematic
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<img src="assets\img\product_pics\unit\unit-v/unit_v_09.jpg" width="30%" height="30%"><br>
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## Video
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<video class="video_size" controls>
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<source src="https://m5stack.oss-cn-shenzhen.aliyuncs.com/video/Product_example_video/Unit/unitV.mp4" type="video/mp4">
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</video>
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+1
-1
@@ -147,7 +147,7 @@
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{a:"/#/en/unit/m5camera", img:"https://m5stack.oss-cn-shenzhen.aliyuncs.com/image/m5-docs_homepage/unit/unit_m5camera_01.png", p:"M5Camera"},
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{a:"#/en/unit/m5camera_f", img:"https://m5stack.oss-cn-shenzhen.aliyuncs.com/image/m5-docs_homepage/unit/unit_m5camera_f_01.png", p:"M5CameraF"},
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{a:"/#/en/unit/m5camera_x", img:"https://m5stack.oss-cn-shenzhen.aliyuncs.com/image/m5-docs_homepage/unit/unit_m5camera_x_01.png", p:"M5CameraX"},
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// {a:"/#/en/unit/unitv", img:"https://m5stack.oss-cn-shenzhen.aliyuncs.com/image/m5-docs_homepage/unit/unit_m5camera_x_01.png", p:"UNIT-V"},
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{a:"/#/en/unit/unitv", img:"https://m5stack.oss-cn-shenzhen.aliyuncs.com/image/m5-docs_homepage/unit/unit-v-01.webp", p:"UNIT-V"},
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//Sensor class
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{a:"/#/en/unit/earth", img:"https://m5stack.oss-cn-shenzhen.aliyuncs.com/image/m5-docs_homepage/unit/unit_earth_01.png", p:"EARTH"},
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{a:"/#/en/unit/env", img:"https://m5stack.oss-cn-shenzhen.aliyuncs.com/image/m5-docs_homepage/unit/unit_env_01.png", p:"ENV"},
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@@ -147,7 +147,7 @@
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{a:"/#/zh_CN/unit/m5camera", img:"https://m5stack.oss-cn-shenzhen.aliyuncs.com/image/m5-docs_homepage/unit/unit_m5camera_01.png", p:"M5Camera"},
|
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{a:"#/zh_CN/unit/m5camera_f", img:"https://m5stack.oss-cn-shenzhen.aliyuncs.com/image/m5-docs_homepage/unit/unit_m5camera_f_01.png", p:"M5CameraF"},
|
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{a:"/#/zh_CN/unit/m5camera_x", img:"https://m5stack.oss-cn-shenzhen.aliyuncs.com/image/m5-docs_homepage/unit/unit_m5camera_x_01.png", p:"M5CameraX"},
|
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// {a:"/#/zh_CN/unit/unitv", img:"https://m5stack.oss-cn-shenzhen.aliyuncs.com/image/m5-docs_homepage/unit/unit_m5camera_x_01.png", p:"UNIT-V"},
|
||||
{a:"/#/zh_CN/unit/unitv", img:"https://m5stack.oss-cn-shenzhen.aliyuncs.com/image/m5-docs_homepage/unit/unit-v-01.webp", p:"UNIT-V"},
|
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//Sensor class
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{a:"/#/zh_CN/unit/earth", img:"https://m5stack.oss-cn-shenzhen.aliyuncs.com/image/m5-docs_homepage/unit/unit_earth_01.png", p:"EARTH"},
|
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{a:"/#/zh_CN/unit/env", img:"https://m5stack.oss-cn-shenzhen.aliyuncs.com/image/m5-docs_homepage/unit/unit_env_01.png", p:"ENV"},
|
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||||
@@ -29,7 +29,7 @@ void loop() {
|
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|
||||
<mark>isPressed();</mark> // for arduino
|
||||
|
||||
**功能:返回键值。如果指定按键奇数次数按下后,一直返回 1,偶数次数按下,一直返回 0。**
|
||||
**功能:返回键值。如果按键按下,总是返回true,否则总是返回false**
|
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|
||||
**例程**
|
||||
```arduino
|
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|
||||
@@ -64,6 +64,13 @@
|
||||
|
||||
<img src="assets/img/related_documents/UIFlow_Desktop_IDE/Desktop_IDE_05.jpg">
|
||||
|
||||
!>如果你使用的是M5StickC请按以下说明操作
|
||||
|
||||
>长按机身左侧的电源键2秒进行开机,在出现UIFlow Logo后,快速单击Home键(中心M5按键),进入配罝页面。按机身右侧按键将选项切换至Setting,按下Home键确认。按右侧按键切换选项至USB mode,
|
||||
按下Home键确认,进入USB编程模式.在IDE中选择相应的COM口与设备,点击连接。
|
||||
|
||||
<img src="assets/img/related_documents/UIFlow_Desktop_IDE/Desktop_IDE_00.jpg">
|
||||
|
||||
## 使用案例
|
||||
|
||||
>完成连接后,就可以开始编程创作了,拖拽左侧的程序块列表中的程序块到编程区域,完成程序编辑后点击右上角的运行按钮,执行程序.
|
||||
|
||||
+76
-104
@@ -1,61 +1,100 @@
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# UNIT-V {docsify-ignore-all}
|
||||
# UnitV {docsify-ignore-all}
|
||||
|
||||
<img src="assets/img/product_pics/unit/unit-v/unit_v_01.webp" width="30%" height="30%">
|
||||
<img src="assets/img/product_pics/unit/unit-v/unit_v_02.webp" width="30%" height="30%">
|
||||
<img src="assets/img/product_pics/unit/unit-v/unit_v_04.webp" width="30%" height="30%">
|
||||
|
||||
<img src="assets\img\product_pics\unit\unit-v/unit_v_01.jpg" width="30%" height="30%">
|
||||
<img src="assets\img\product_pics\unit\unit-v/unit_v_02.jpg" width="30%" height="30%">
|
||||
<img src="assets\img\product_pics\unit\unit-v/unit_v_03.jpg" width="30%" height="30%">
|
||||
|
||||
***
|
||||
|
||||
:memo:**[描述](#描述)** :bulb:**[上手指南](zh_CN/quick_start/m5stickv/m5stickv_quick_start)** :electric_plug:**[原理图](#原理图)** 🛒**[购买链接](https://m5stack.com/collections/m5-unit/products/unit-v** <img src="https://m5stack.oss-cn-shenzhen.aliyuncs.com/image/EasyLoader_logo-min.jpg">**[EasyLoader](#EasyLoader)** :camera:**[V-Training](zh_CN/related_documents/v-training)**
|
||||
:memo:**[描述](#描述)** 🛒**[购买链接](https://m5stack.com/collections/m5-unit/products/unit-v)** :clapper:**[Videos](#Videos)**
|
||||
|
||||
|
||||
## 描述
|
||||
|
||||
**UNIT-V**是一款搭载Kendryte K210的AI视觉处理传传感器单元,集成双核64位RISC-V CPU和最先进的神经网络处理器边缘计算片上系统.
|
||||
<br><br>
|
||||
UNIT-V AI摄像头体积非常小巧,适合嵌入到各种设备当中,具备机器视觉处理能力,支持多种图像识别能力( 如实时获取被检测目标的大小与坐标 • 实时获取被检测目标的种类),并且能够在低功耗情况下进行卷积神经网络计算,因此UNIT-V会是一个很好的零门槛机器视觉嵌入式解决方案.
|
||||
<br><br>
|
||||
支持MicroPython开发环境,这使得你在使用UINT-V上进行项目开发时,程序代码将会更加精简.
|
||||
<br><br>
|
||||
配备OV2640 200万像素图像传感器,是机器视觉项目的理想选择.
|
||||
<br><br>
|
||||
配备两个可编程按键,正面有一颗RGB LED指示灯,方便进行状态显示.
|
||||
<br><br>
|
||||
底部提供一个兼容GROVE的PH2.0*4P接口和一个TYPE-C接口,方便与主控设备进行连接.
|
||||
<br><br>
|
||||
支持TF卡扩展内存,相关素材及模型文件调用使用更方便.
|
||||
<br><br><br>
|
||||
<img src="assets\img\product_pics\unit\unit-v/unit_v_04.jpg" width="30%" height="30%">
|
||||
<img src="assets\img\product_pics\unit\unit-v/unit_v_05.jpg" width="30%" height="30%">
|
||||
<img src="assets\img\product_pics\unit\unit-v/unit_v_06.jpg" width="30%" height="30%"><br>
|
||||
**UNIT-V**是一款搭载Kendryte K210的AI视觉处理摄像头单元,集成双核64位RISC-V CPU和最先进的神经网络处理器边缘计算片上系统.UNIT-V AI摄像头体积非常小巧,适合嵌入到各种设备当中,具备机器视觉处理能力,支持多种图像识别能力( 如实时获取被检测目标的大小与坐标 • 实时获取被检测目标的种类),并且能够在低功耗情况下进行卷积神经网络计算,因此UNIT-V会是一个很好的零门槛机器视觉嵌入式解决方案.它支持MicroPython开发环境,这使得你在使用UNIT-V上进行项目开发时,程序代码将会更加精简.搭载OV2640 200万像素图像传感器,是机器视觉项目的理想选择.机身配备两个可编程按键,正面有一颗RGB LED指示灯,方便进行状态显示.底部提供一个兼容GROVE的PH2.0*4P接口和一个TYPE-C接口,可以与主控设备进行连接.支持TF卡扩展内存,相关素材及模型文件调用使用更方便.
|
||||
|
||||
### 产品特性:
|
||||
- 双核 64-bit RISC-V RV64IMAFDC (RV64GC) CPU / 400Mhz(Normal)
|
||||
- 双精度 FPU
|
||||
- 8MiB 64bit 片上 SRAM
|
||||
- 神经网络处理器(KPU) / 0.8Tops
|
||||
- 可编程 IO 阵列 (FPIOA)
|
||||
- 可编程 I/O 阵列 (FPIOA)
|
||||
- AES, SHA256 加速器
|
||||
- 直接内存存取控制器 (DMAC)
|
||||
- 支持 Micropython
|
||||
- 支持 MicroPython
|
||||
- 固件加密支持
|
||||
- 板载硬件资源:
|
||||
- Flash: 16M.
|
||||
- Flash: 16M
|
||||
- 摄像头 :OV2640
|
||||
- 按键: button * 2
|
||||
- 指示灯: RGB
|
||||
- 指示灯: RGB LED
|
||||
- 外部存储: TF card/Micro SD
|
||||
- 接口: PH2.0/兼容GROVE.
|
||||
- 接口: PH2.0/兼容GROVE
|
||||
|
||||
## 应用/UNIT-V可以做什么
|
||||
- 面部识别/检测
|
||||
- 物体检测/分类
|
||||
- 实时获取目标的大小和坐标
|
||||
- 实时获取检测到的目标类型
|
||||
- 形状识别
|
||||
- 视频录制
|
||||
|
||||
### 尺寸重量
|
||||
|
||||
- 尺寸:4mm * 2.5mm * 1.5mm
|
||||
- 重量:4g
|
||||
|
||||
|
||||
### 包含
|
||||
|
||||
- 1x UNIT-V(包含连接线)
|
||||
- 1x Unit V(包含连接线)
|
||||
|
||||
### 关于 KENDRYTE K210
|
||||
Kendryte K210 是集成机器视觉能力的系统级芯片 (SoC)。使用台积电 (TSMC) 超低功耗的 28 纳米先进制程,具有双核 64 位处理器,拥有较好的功耗性能,稳定性与可靠性。该方案力求零门槛开发,可在最短时效部署于用户的产品中,赋予人工智能应用.
|
||||
- 具备机器视觉能力
|
||||
- 更好的低功耗视觉处理速度与准确率
|
||||
- 具备卷积人工神经网络硬件加速器 KPU,可高性能进行卷积人工神经网络运算
|
||||
- TSMC 28nm 先进制程,温度范围-40°C 到 125°C,稳定可靠
|
||||
- 支持固件加密,难以使用普通方法破解
|
||||
- 独特的可编程 IO 阵列,使产品设计更加灵活
|
||||
- 低电压,与相同处理能力的系统相比具有更低功耗
|
||||
- 3.3V/1.8V 双电压支持,无需电平转换,节约成本
|
||||
|
||||
本产品搭载基于 RISC-V ISA 的双核心 64 位的高性能低功耗 CPU,具备以下特性
|
||||
- 核心数量: 双核处理器
|
||||
- 处理器位宽: 64-bit CPU 400MHz
|
||||
- 标称频率: 400MHz
|
||||
- 指令集扩展: IMAFDC
|
||||
- 浮点处理单元(FPU): 双精度
|
||||
- 平台中断管理: PLIC
|
||||
- 本地中断管理: CLINT
|
||||
- 指令缓存: 32KiB x 2
|
||||
- 数据缓存: 32KiB x 2
|
||||
- 片上 SRAM: 8MiB
|
||||
|
||||
### 关于 OV2640
|
||||
- 支持输出格式(8位):
|
||||
- YUV(422/420)/YCbCr422
|
||||
- RGB565/555
|
||||
- 8位压缩数据
|
||||
- 8-/10位Raw RGB数据
|
||||
- 根据特定格式的最大图像传输速率
|
||||
- UXGA/SXGA: 15fps
|
||||
- SVGA: 30fps
|
||||
- CIF: 60fps
|
||||
- 扫描模式: 渐进式
|
||||
- 相机规格
|
||||
- CCD 尺寸 : 1/4 inch
|
||||
- 视野 : 65 °
|
||||
- 最大像素: 2M
|
||||
- 传感器最佳分辨率: 1600 * 1200
|
||||
- 尺寸: 40 × 49 × 13mm
|
||||
|
||||
### SD卡测试
|
||||
|
||||
UNIT-V目前并不能识别所有类型的MicroSD卡,我们对一些常见的MicroSD卡进行了测试,测试结果如下.
|
||||
Unit V目前并不能识别所有类型的MicroSD卡,我们对一些常见的MicroSD卡进行了测试,测试结果如下.
|
||||
|
||||
<img src="assets\img\product_pics\core\minicore\m5stickv/m5stickv_08.jpg" width="30%" height="30%">
|
||||
<img src="assets\img\product_pics\unit\unit-v/unit-v-08.jpg" width="40%" height="40%">
|
||||
|
||||
<table class="table_center">
|
||||
<tr style="font-weight:bold" >
|
||||
@@ -165,81 +204,14 @@ UNIT-V目前并不能识别所有类型的MicroSD卡,我们对一些常见的M
|
||||
</table>
|
||||
|
||||
|
||||
## EasyLoader
|
||||
|
||||
<img src="https://m5stack.oss-cn-shenzhen.aliyuncs.com/image/EasyLoader_logo.png" width="100px" style="margin-top:20px">
|
||||
|
||||
<a href="https://m5stack.oss-cn-shenzhen.aliyuncs.com/EasyLoader/M5Core/M5StickV/EasyLoader_M5StickV_1022_beta.exe"><button type="button" class="btn btn-primary">点击下载EasyLoader</button></a>
|
||||
|
||||
>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)**
|
||||
|
||||
>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
|
||||
|
||||
|
||||
### 功能描述
|
||||
#### 1.1 KENDRYTE K210
|
||||
Kendryte K210 是集成机器视觉能力的系统级芯片 (SoC)。使用台积电 (TSMC) 超低功耗的 28 纳米先进制程,具有双核 64 位处理器,拥有较好的功耗性能,稳定性与可靠性。该方案力求零门槛开发,可在最短时效部署于用户的产品中,赋予产品人工智能.<br><br>
|
||||
- 具备机器视觉能力
|
||||
- 更好的低功耗视觉处理速度与准确率
|
||||
- 具备卷积人工神经网络硬件加速器 KPU,可高性能进行卷积人工神经网络运算
|
||||
- TSMC 28nm 先进制程,温度范围-40°C 到 125°C,稳定可靠
|
||||
- 支持固件加密,难以使用普通方法破解
|
||||
- 独特的可编程 IO 阵列,使产品设计更加灵活
|
||||
- 低电压,与相同处理能力的系统相比具有更低功耗
|
||||
- 3.3V/1.8V 双电压支持,无需电平转换,节约成本
|
||||
|
||||
本芯片搭载基于 RISC-V ISA 的双核心 64 位的高性能低功耗 CPU,具备以下特性<br><br>
|
||||
|
||||
- 核心数量: 双核处理器
|
||||
- 处理器位宽: 64-bit CPU 400MHz
|
||||
- 标称频率: 400MHz
|
||||
- 指令集扩展: IMAFDC
|
||||
- 浮点处理单元(FPU): 双精度
|
||||
- 平台中断管理: PLIC
|
||||
- 本地中断管理: CLINT
|
||||
- 指令缓存: 32KiB x 2
|
||||
- 数据缓存: 32KiB x 2
|
||||
- 片上 SRAM: 8MiB
|
||||
|
||||
#### 1.2 OV2640
|
||||
- 支持输出格式(8位):
|
||||
YUV(422/420)/YCbCr422
|
||||
RGB565/555
|
||||
8位压缩数据
|
||||
8- / 10位Raw RGB数据
|
||||
- 根据特定格式的最大图像传输速率
|
||||
UXGA/SXGA: 15fps
|
||||
SVGA: 30fps
|
||||
CIF: 60fps
|
||||
- 扫描模式: 渐进式
|
||||
- 相机规格
|
||||
CCD 尺寸 : 1/4 inch
|
||||
视野 : 65 °
|
||||
最大像素: 2M
|
||||
传感器最佳分辨率: 1600 * 1200
|
||||
尺寸: 40 × 49 × 13mm
|
||||
|
||||
## 应用/UNIT-V可以做什么
|
||||
- 面部识别/检测
|
||||
- 物体检测/分类
|
||||
- 实时获取目标的大小和坐标
|
||||
- 实时获取检测到的目标类型
|
||||
- 形状识别
|
||||
- 视频/显示
|
||||
- 游戏模拟器
|
||||
|
||||
## 相关链接
|
||||
|
||||
- **Web page** - [sipeed](https://maixpy.sipeed.com/en/)
|
||||
- **Quick Start Guide** - [M5StickV Guide](https://docs.m5stack.com/#/en/quick_start/m5stickv/m5stickv_quick_start)
|
||||
- **Github** - [API](https://github.com/sipeed/MaixPy/tree/master/projects/maixpy_m5stickv)
|
||||
- **Web page** - [sipeed](https://maixpy.sipeed.com/zh/)
|
||||
- **数据手册** - [K210](https://m5stack.oss-cn-shenzhen.aliyuncs.com/resource/docs/datasheet/core/kendryte_datasheet.pdf)
|
||||
|
||||
- **数据手册**
|
||||
|
||||
- [K210]](https://m5stack.oss-cn-shenzhen.aliyuncs.com/resource/docs/datasheet/core/kendryte_datasheet.pdf)
|
||||
|
||||
## 原理图
|
||||
|
||||
<img src="assets\img\product_pics\unit\unit-v/unit_v_09.jpg" width="30%" height="30%"><br>
|
||||
## Video
|
||||
|
||||
<video class="video_size" controls>
|
||||
<source src="https://m5stack.oss-cn-shenzhen.aliyuncs.com/video/Product_example_video/Unit/unitV.mp4" type="video/mp4">
|
||||
</video>
|
||||
|
||||
|
||||
Reference in New Issue
Block a user