K210 Handwritten Digit Action

1. Hardware Connection

Physical Connection

Schematic Diagram

2. Code Analysis

Control Principle

K210 Protocol

Control Flow Chart

bsp_k210_use.c

​x
// 处理K210发来的单字节数据 / Process single byte data from K210
void recv_k210msg(uint8_t recv_msg) 
{
    // 检测包头'$'，开始接收新消息 / Detect packet header '$', start receiving new message 
    if (recv_msg == '$')
    {
        new_flag = 1;
    }
    
    // 检测包尾'#'，结束接收并校验 / Detect packet tail '#', end reception and verify 
    if(recv_msg == '#' )
    {
        if( buf_len == r_index)  // 数据长度匹配 / Data length matches 
        {
            new_flag = 0;
            tou_flag = 0;
            len_flag = 0;
            
            // 校验和计算：减去接收的校验和字节 / Checksum calculation: subtract received checksum byte 
            buf_crc -= buf_msg[r_index-1];
            buf_crc %= 256;
            
            if(buf_crc == buf_msg[r_index-1])  // 校验正确 / Checksum correct 
            {
                deal_recvmsg();  // 处理接收数据 / Process received data
            }
            else  // 校验失败 / Checksum failed 
            {
                r_index = 0;
                buf_crc = 0;
            }
        }
    }
    
    // 正在接收新消息时的处理逻辑 / Processing logic when receiving new message
    if(new_flag == 1 )
    {
        // 首次接收包头 / First time receiving packet header 
        if(recv_msg == '$' && tou_flag == 0)  
        {
            tou_flag = 1;
        }
        else
        {
            // 存储数据并递增索引 / Store data and increment index
            buf_msg[r_index++] = recv_msg; 
            buf_crc += recv_msg;            
            // 未获取长度时，从首字节读取长度 / When length not obtained, read length from first byte
            if(len_flag == 0)  
            {
                buf_len = buf_msg[0];
                len_flag = 1;
            }
        }
    }
}
•
// 解析接收的完整消息 / Parse received complete message 
void deal_recvmsg(void)
{
    //长度校验 / Length verification 
    if(r_index!=buf_len)
    {
        buf_len = 0;
        return ;
    }
    
    // 提取有效数据（过滤逗号） / Extract valid data (filter commas)
    for(index = 0 ;index<number;index++)
    {
        if(buf_msg[4+index] == 0x2c && i_duo ==0)//遇到逗号且未过滤 / Encounter comma and not filtered
        {
            i_duo = 1;
            continue;
        }
        data[data_i++]=buf_msg[4+index];//存储有效数据 / Store valid data
        i_duo =0;
    }
    
    // 重置接收状态 / Reset receive state 
    buf_crc = 0;
    r_index = 0;
    memset(buf_msg,0,sizeof(buf_msg));
    // 处理解析后的数据 / Process parsed data 
    deal_data(eg_num);    
​

K210 Partial Source Code

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def send_data(x,y,w,h,msg):
    start = 0x24
    end = 0x23
    length = 5
    class_num = 0x0B #例程编号 / Routine number
    class_group = 0xBB #例程组 / Routine group
    data_num = 0x00 #数据量 / Data amount
    fenge = 0x2c #逗号 / Comma separator
    crc = 0 #校验位 / Checksum
    data = [] #数据组 / Data array
•
    #参数都为0 / All parameters are 0
    if x==0 and y==0 and w==0 and h ==0:
        pass
    else:
        #x(小端模式) / x (little-endian mode)
        low = x & 0xFF #低位 / Low byte
        high = x >> 8& 0xFF #高位 / High byte
        data.append(low)
        data.append(fenge) #增加","
        data.append(high)
        data.append(fenge) #增加","
...
kpu = KPU()
# 加载MNIST手写数字识别模型 / Load MNIST handwritten digit recognition model
kpu.load_kmodel("/sd/KPU/mnist/uint8_mnist_cnn_model.kmodel")
•
•
while True:
    gc.collect()  # 释放内存 / Free memory
    img = sensor.snapshot()  # 捕获图像 / Capture image
    
    # 图像预处理（适配模型输入要求） / Image preprocessing (adapt to model input requirements)
    img_mnist1 = img.to_grayscale(1)
    img_mnist2 = img_mnist1.resize(112, 112)
    img_mnist2.invert()
    img_mnist2.strech_char(1)
    img_mnist2.pix_to_ai()
•
    # 运行模型并获取输出 / Run model and get output
    out = kpu.run_with_output(img_mnist2, getlist=True)
    max_mnist = max(out)  # 最大概率值 / Maximum probability value
    index_mnist = out.index(max_mnist)  # 识别结果（数字索引） / Recognition result (digit index)
    msg_ = str(index_mnist)
    send_data(0,0,0,0,msg_)  # 封装数据（仅发送识别结果） / Package data (only send recognition result)
    
    # 计算置信度（通过sigmoid函数归一化） / Calculate confidence (normalize through sigmoid function)
    score = KPU.sigmoid(max_mnist)
    
    # 当识别为数字8且置信度>0.999时，显示并发送结果 / When recognized as digit 8 and confidence > 0.999, display and send result
    if index_mnist == 8:
        if score > 0.999:
            display_str = "num: %d" % index_mnist
            print(display_str, score)
            img.draw_string(4,3,display_str,color=(0,0,0),scale=2)
            serial.send_bytearray(send_buf)  # 串口发送数据 / Send data via serial port
    # 识别为数字5且置信度>0.999时，仅显示结果 / When recognized as digit 5 and confidence > 0.999, only display result
    elif index_mnist == 5:
        if score > 0.999:
            display_str = "num: %d" % index_mnist
            print(display_str, score)
            img.draw_string(4,3,display_str,color=(0,0,0),scale=2)
    
    lcd.display(img)  # 在LCD上显示图像 / Display image on LCD

3. Main Functions

BSP_Loop

4. K210 Program Burning

After downloading and opening CanMV IDE, we need to first drag the k210_minist.py file from the k210 source code provided in this course to CanMV IDE to open it, then connect the IDE here using helloworld.py as example

After successful IDE connection, the phenomenon is as follows

Here we use helloworld.py as an example, open the top menu bar Tools -> Save currently open script as (main.py) to CanMV Cam

Both Yes/No can be selected here. When the following status appears, the write is successful.

5. Experimental Phenomena

After burning the program, press KEY1 button, the car moves forward continuously. If digit 8 is recognized, the car will reverse for a period of time and then resume forward movement, while the recognized digit will be displayed on the OLED.