83 lines
2.3 KiB
Python
83 lines
2.3 KiB
Python
# -*- coding:utf-8 -*-
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# @Author len
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# @Create 2023/12/5 10:16
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# Untitled - By: nian0 - 周一 11月 20 2023
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import sensor, image, lcd, time
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from fpioa_manager import fm
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import KPU as kpu
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import gc
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from Maix import GPIO
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from machine import Timer, PWM, UART, Timer
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# 摄像头初始化
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sensor.reset()
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sensor.set_pixformat(sensor.RGB565)
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sensor.set_framesize(sensor.QVGA)
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sensor.set_vflip(1) # 摄像头后置方式
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sensor.set_pixformat(sensor.RGB565) # 设置像素格式为彩色 RGB565
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#sensor.set_pixformat(sensor.GRAYSCALE) # 设置像素格式为灰色
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sensor.set_framesize(sensor.QVGA) # 设置帧大小为 QVGA (320x240)
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sensor.set_auto_gain(False)
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sensor.set_auto_whitebal(False)
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sensor.set_auto_gain(0,0)
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# 初始化 LCD
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lcd.init()
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def Servo(angle):
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'''
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说明：舵机控制函数
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功能：180度舵机：angle:-90至90 表示相应的角度
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360连续旋转度舵机：angle:-90至90 旋转方向和速度值。
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【duty】占空比值：0-100
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'''
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#PWM通过定时器配置，接到IO17引脚
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tim_pwm = Timer(Timer.TIMER0, Timer.CHANNEL0, mode=Timer.MODE_PWM)
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S1 = PWM(tim_pwm, freq=50, duty=0, pin=17)
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S1.duty((angle+90)/180*10+2.5)
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Servo(15)
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# 从SD卡加载模型
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# task = kpu.load("/sd/model-96249.kmodel")
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labels = ['green', 'light', 'yellow', 'red']
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anchors = [0.88, 3.47, 0.69, 0.81, 0.97, 3.47, 1.12, 3.75, 1.25, 4.19]
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while True:
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task = None
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task = kpu.load(0x300000)
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# 初始化yolo2网络，识别可信概率为0.7（70%）
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a = kpu.init_yolo2(task, 0.7, 0.3, 5, anchors)
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img = sensor.snapshot()
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# 调整图像大小
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img = img.resize(224, 224)
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# # 在LCD屏幕上显示图像
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# lcd.display(img)
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# 准备图像进行推理
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img.pix_to_ai()
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code = kpu.run_yolo2(task, img) # 运行yolo2网络
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print(code)
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if code:
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for obj in code:
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pos = obj.rect()
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print(labels[obj.classid()])
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img.draw_rectangle(pos)
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img.draw_string(pos[0], pos[1], "%s : %.2f" %(labels[obj.classid()], obj.value()), scale=2, color=(255, 0, 0))
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#comm.send_detect_result(code, classes)
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#img.draw_string(0, 200, "t:%dms" %(t), scale=2, color=(255, 0, 0))
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a = lcd.display(img)
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else:
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a = lcd.display(img)
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if not task is None:
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kpu.deinit(task)
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