openmv4人脸姿态估计代码

以下是OpenMV4的人脸姿态估计代码：

首先，我们需要导入所需的库和模块：

import sensor, image, time
import KPU as kpu
import lcd
from fpioa_manager import *
from machine import I2C
from board import board_info
from fpioa_manager import *
from pmu import axp192
from modules import ws2812

然后，我们需要初始化硬件和模块：

fm.register(board_info.LED_W, fm.fpioa.GPIO0)
led = GPIO(GPIO.GPIO0, GPIO.OUT)
led.value(1)

lcd.init(freq=15000000)
lcd.direction(lcd.YX_RLDU)
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.set_vflip(1)
sensor.run(1)
kpu.memtest()
task = kpu.load(0x200000)

接下来，我们需要创建I2C总线和AXP192电源管理器的实例：

fm.register(20, fm.fpioa.GPIOH7)
fm.register(21, fm.fpioa.GPIOH6)
i2c = I2C(I2C.I2C0, freq=400000, scl=21, sda=20)
pmu = axp192(i2c=i2c)
pmu.enablePMICSleepMode(True)

然后，我们需要定义一些变量和函数：

def draw_string_at(img, x, y, text):
    img.draw_string(x, y, text, color=(255, 255, 255), scale=2)

colors = [(255, 0, 0), (255, 128, 0), (255, 255, 0), (128, 255, 0), (0, 255, 0),
          (0, 255, 128), (0, 255, 255), (0, 128, 255), (0, 0, 255), (128, 0, 255),
          (255, 0, 255), (255, 0, 128), (128, 128, 128), (0, 0, 0)]

def draw_arrow(img, x, y, dx, dy):
    img.draw_line(x, y, x+dx, y+dy, color=(255, 0, 0), thickness=3)
    img.draw_circle(x+dx, y+dy, 5, color=(255, 0, 0), thickness=3)

def get_pose_string(pose):
    return "Yaw: {:.2f}, Pitch: {:.2f}, Roll: {:.2f}".format(pose[0], pose[1], pose[2])

最后，我们可以开始循环读取图像，进行人脸检测和姿态估计，并在LCD屏幕上显示结果：

while True:
    img = sensor.snapshot()
    boxes = img.detect_face()
    if boxes:
        for box in boxes:
            x, y, w, h = box
            img.draw_rectangle(x, y, w, h, color=colors[0], thickness=3)
            face_img = img.crop(x, y, w, h)
            resized_img = face_img.resize(128, 128)
            out = kpu.forward(task, resized_img)
            pose = out[:3]
            draw_string_at(img, x, y-30, get_pose_string(pose))
            draw_arrow(img, int(x+w/2), int(y+h/2), int(pose[0]*50), int(pose[1]*50))
    lcd.display(img)

完整代码如下：