Software for Raspberry Pi to capture and overlay data from an AMG8833 infrared thermal camera with images from the RPi optical camera

camera_overlay.py

#######################################################
#
#    Thermal/optical camera overlay (main program)
#
#    by Caden Gobat
#       PHYS 2152 | The George Washington University
#
#######################################################

from datetime import datetime
import numpy as np, time, matplotlib.pyplot as plt

from optical_cam import capture_optical
from IR_cam import capture_thermal

if __name__ == "__main__":
    px_dim = 256
    XX,YY = np.meshgrid(np.arange(0,px_dim,1),np.arange(0,px_dim,1))
    # edit these values based on physical positions of the cameras relative to one another
    x_shift = -30
    y_shift = 10
    with open("./timeseries/datafile.csv","w+") as file:
        file.write("ID, Timestamp, Ambient temp")
    for i in range(3):
        image_arr = np.rot90(capture_optical(),2,(0,1))
        therm,temp = capture_thermal(interp_dim=(px_dim,px_dim), return_ambient=True)
        fig,ax = plt.subplots(figsize=(10,9),num="Camera overlay")
        ax.set(xticks=[],yticks=[])
        img = ax.imshow(image_arr)
        tcont = ax.contour(XX+x_shift,YY+y_shift,therm-temp,cmap="hot")
        #cbar = fig.colorbar(tcont,label="Temperature above/below ambient")
        ts = datetime.now()
        fig.savefig(f"./timeseries/ID-{i+1}.png",bbox_inches="tight",dpi=300)
        np.savetxt(f"./timeseries/ID-{i+1}",therm)
        print("captured/saved image",i+1)
        with open("./timeseries/datafile.csv","a") as file:
            file.write(f"\n{i+1}, {ts}, {temp}")
        time.sleep(0.5)

IR_cam.py

#######################################################
#
#    Thermal camera display for AMG8833 IR camera
#
#    by Caden Gobat
#       PHYS 2152 | The George Washington University
#
#######################################################

import time, sys
import numpy as np
import matplotlib.pyplot as plt
from scipy import interpolate
from amg8833_i2c import AMG8833

# initialize AMG8833 sensor
t0 = time.time()
sensor = None
while (time.time()-t0)<1: # wait 1sec for sensor to start
    try:
        sensor = AMG8833(addr=0x68) # start AMG8833
    except:
        sensor = AMG8833(addr=0x69)
    finally:
        pass
time.sleep(0.1) # wait for sensor to settle

if not sensor:
    print("Thermal camera not found.")
    sys.exit();

pix_res = (8,8) # sensor pixel resolution
xx,yy = (np.linspace(0,pix_res[0],pix_res[0]),
         np.linspace(0,pix_res[1],pix_res[1]))
zz = np.random.random(pix_res) # initialize array

# new resolution
pix_mult = 6 # multiplier for interpolation 
interp_res = (int(pix_mult*pix_res[0]),int(pix_mult*pix_res[1]))
grid_x,grid_y = (np.linspace(0,pix_res[0],interp_res[0]),
                 np.linspace(0,pix_res[1],interp_res[1]))

# interpolation function
def interp(z_var,grid=(grid_x,grid_y)):
    # new resolution will be (8*pix_mult x 8*pix_mult)
    f = interpolate.interp2d(xx,yy,z_var,kind='cubic')
    return f(grid[0],grid[1])

grid_z = interp(zz) # interpolated image

def capture_thermal(interp_dim=(8,8),return_ambient=False):
    status,pixels = sensor.read_temp(64) # read all 64 pixels with status
    if status: # if error in pixel, re-enter loop and try again
        print(status)
        return None
    interp_grid = (np.linspace(0,8,interp_dim[0]),
                   np.linspace(0,8,interp_dim[1]))
    if return_ambient:
        T = sensor.read_thermistor()
        return interp(np.reshape(pixels,(8,8)),grid=interp_grid), T
    else:
        return interp(np.reshape(pixels,(8,8)),grid=interp_grid)

# real-time sensor reading
if __name__ == "__main__":
    
    # matplotlib display setup
    plt.rcParams.update({'font.size':16})
    fig_dims = (10,9) # figure size
    fig,ax = plt.subplots(figsize=fig_dims,num="AMG8833 thermal camera") # start figure
    ax.set(xticks=[],yticks=[])
    im1 = ax.imshow(grid_z,cmap=plt.cm.RdBu_r,vmin=16,vmax=30) # plot image, with temperature bounds
    cbar = fig.colorbar(im1,fraction=0.0475,pad=0.03) # colorbar for scale
    cbar.set_label('Temperature [°C]',labelpad=10) 
    fig.canvas.draw() # draw figure

    ax_bgnd = fig.canvas.copy_from_bbox(ax.bbox) # background for speeding up runs
    fig.show() # show figure

    while True:
        status,pixels = sensor.read_temp(64) # read all 64 pixels with status
        if status: # if error in pixel, re-enter loop and try again
            print(status)
            continue
        
        T_thermistor = sensor.read_thermistor() # read thermistor temp (ambient)
        fig.canvas.restore_region(ax_bgnd) # restore background (speeds up run)
        new_z = interp(np.reshape(pixels,pix_res)) # interpolated thermal image
        im1.set_data(new_z) # update image object with new data
        ax.draw_artist(im1) # redraw image
        fig.canvas.blit(ax.bbox) # blitting - for speeding up run
        fig.canvas.flush_events() # for real-time plot

optical_cam.py

#######################################################
#
#    Optical camera display for Raspberry Pi camera
#
#    by Caden Gobat
#       PHYS 2152 | The George Washington University
#
#######################################################

import time
import picamera
import numpy as np
import matplotlib.pyplot as plt

camera = picamera.PiCamera()
camera.resolution = (256, 256)
camera.framerate = 24
time.sleep(2)
output = np.empty((256, 256, 3), dtype=np.uint8)

def capture_optical():
    output = np.empty((256,256,3), dtype=np.uint8)
    camera.capture(output,'rgb')
    return output

if __name__ == "__main__":
    plt.rcParams.update({'font.size':16})
    fig,ax = plt.subplots(figsize=(10,9),num="PiCamera") # start figure
    ax.set(xticks=[],yticks=[])
    #plt.set_window_title('PiCamera')
    im1 = ax.imshow(output) # plot image
    fig.canvas.draw() # draw figure

    ax_bgnd = fig.canvas.copy_from_bbox(ax.bbox) # background for speeding up runs
    fig.show() # show figure

    while True:
        camera.capture(output, 'rgb')

        fig.canvas.restore_region(ax_bgnd) # restore background (speeds up run)
        im1.set_data(output) # update plot with new interpolated temps
        ax.draw_artist(im1) # draw image again
        fig.canvas.blit(ax.bbox) # blitting - for speeding up run
        fig.canvas.flush_events() # for real-time plot