尝试将MLX90621 16x4红外传感器阵列的温度原始数据对准面部的前额

Question

我正在一个学校项目中使用MLX90621 16x4红外传感器阵列和带有Python的Raspberry Pi，以获取温度阵列数据并将其转换为热彩色覆盖层。该覆盖层可以使用Haarcascade对准人的前额，并且可以显示前额温度的读数。

我设法用python做了额头跟踪代码，并通过以下链接获取了覆盖相机图像的热数据： https://hackaday.io/project/6416-raspberry-pi-thermal-imaging

但是，我只能使它分开工作，我正在努力使两个代码一起工作。我对该主题进行了大量研究，但似乎只找到Arduino和C ++教程或与理论相关的文章。

我是编程和树莓派的新手。

这是使用Haarcascade和Pi Camera进行额头跟踪的代码：

from picamera.array import PiRGBArray
from picamera import PiCamera
import time
import cv2

# initialize the camera and grab a reference to the raw camera capture
camera = PiCamera()
camera.resolution = (640, 480)
camera.framerate = 32
rawCapture = PiRGBArray(camera, size=(640, 480))

# allow the camera to warmup
time.sleep(0.1)

#Use the trained xml classifier for eyes detection in the video
eye_cascade = cv2.CascadeClassifier('/home/pi/Desktop/mlxd-master_terickson/testScripts/haarcascade_eye.xml')
#Use the trained xml classifier for faces detection in the video
face_cascade = cv2.CascadeClassifier('/home/pi/Desktop/mlxd-master_terickson/testScripts/haarcascade_frontalface_default.xml')



# capture frames from the camera
for frame in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):
    # grab the raw NumPy array representing the image, then initialize the timestamp
    # and occupied/unoccupied text
    image = frame.array
    gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
    font = cv2.FONT_HERSHEY_SIMPLEX

    eyes = eye_cascade.detectMultiScale(gray, 1.3, 6)               # To detect eyes in the video   
    for(ex,ey,ew,eh) in eyes:                                       
        cv2.rectangle(image, (ex,ey), (ex+ew,ey+eh), (0,255,0),2)   # To draw rectangle boxes around the eyes

    faces = face_cascade.detectMultiScale(gray, 1.3, 6)
    for (x,y,w,h) in faces:
        forehead_center = int(x+w/1), int(y+h/4)                    # Location of the forehead in face
        cv2.rectangle(image,(x,y),(x+w,y+h),(255,0,0),2)            # To draw rectangle boxes around the face
        cv2.rectangle(image,(x,y),forehead_center,(255,255,0),2)    # To draw rectangle boxes around the forehead of the face
        cv2.putText(image,'x: {0} | y: {1}'.format(forehead_center[0], forehead_center[1]),(10,50), font, 1.2,(0,0,255),1)  # To put the x and y cord of the forehead

    # show the frame
    cv2.imshow("Eye, Face and Forehead tracking", image)
    key = cv2.waitKey(1) & 0xFF

    # clear the stream in preparation for the next frame
    rawCapture.truncate(0)

    # if the `q` key was pressed, break from the loop
    if cv2.waitKey(1) & 0xFF == ord('q'):  
        break

以下是将温度数组叠加到叠加层并使用Pi Camera在视频预览上显示的代码：

import picamera
import numpy as np
import subprocess
import skimage
from skimage import io, exposure, transform, img_as_float, img_as_ubyte
import matplotlib.pyplot as plt
from time import sleep
import cv2

# IR registration parameters
ROT = np.deg2rad(90)
SCALE = (36.2, 36.4)
OFFSET = (580, 170)

def getImage():
    fn = r'/home/pi/tmp.jpg'
    proc = subprocess.Popen('raspistill -o %s -w 640 -h 480 -n -t 3' % (fn),
                            shell=True, stderr=subprocess.STDOUT)
    proc.wait()
    im = io.imread(fn, as_grey=True)
    im = exposure.equalize_hist(im)
    return skimage.img_as_ubyte(im)


def get_overlay(fifo):
    # get the whole FIFO
    ir_raw = fifo.read()
    # trim to 128 bytes
    ir_trimmed = ir_raw[0:128]
    # go all numpy on it
    ir = np.frombuffer(ir_trimmed, np.uint16)
    # set the array shape to the sensor shape (16x4)
    ir = ir.reshape((16, 4))[::-1, ::-1]
    ir = img_as_float(ir)
    # stretch contrast on our heat map
    p2, p98 = np.percentile(ir, (2, 98))
    ir = exposure.rescale_intensity(ir, in_range=(p2, p98))
    # increase even further? (optional)
    ir = exposure.equalize_hist(ir)

    # turn our array into pretty colors
    cmap = plt.get_cmap('Spectral')
    rgba_img = cmap(ir)
    rgb_img = np.delete(rgba_img, 3, 2)

    # align the IR array with the camera
    tform = transform.AffineTransform(scale=SCALE, rotation=ROT, translation=OFFSET)
    ir_aligned = transform.warp(rgb_img, tform.inverse, mode='constant', output_shape=im.shape)
    # turn it back into a ubyte so it'll display on the preview overlay
    ir_byte = img_as_ubyte(ir_aligned)
    # return buffer
    return np.getbuffer(ir_byte)

    #GaussianBlur = cv2.GaussianBlur(camera, (20,20),0)
    #medianFiltered = cv2.medianBlur(camera,5)

im = getImage()


with picamera.PiCamera() as camera:
    camera.led = True
    camera.resolution = (640, 480)
    camera.framerate = 35
    camera.start_preview()

    # get the temperature array, and align with the image
    fifo = open('/var/run/mlx90621.sock', 'r')
    o = camera.add_overlay(get_overlay(fifo), layer=3, alpha=90)

    # update loop
    while True:
        sleep(0.001)
        o.update(get_overlay(fifo))

    print('Error! Closing...')
    camera.remove_overlay(o)
    fifo.close()