I have created code with a MLX90640 Thermal Camera with a Raspberry Pi.

The code is shown below:

import time,board,busio
import numpy as np
import adafruit_mlx90640
import matplotlib.pyplot as plt

print("Initializing MLX90640")
i2c = busio.I2C(board.SCL, board.SDA, frequency=800000) # setup I2C
mlx = adafruit_mlx90640.MLX90640(i2c) # begin MLX90640 with I2C comm
mlx.refresh_rate = adafruit_mlx90640.RefreshRate.REFRESH_2_HZ # set refresh rate
mlx_shape = (24,32)
print("Initialized")

# setup the figure for plotting
plt.ion() # enables interactive plotting
fig,ax = plt.subplots(figsize=(12,7))
therm1 = ax.imshow(np.zeros(mlx_shape),vmin=0,vmax=60) #start plot with zeros
cbar = fig.colorbar(therm1) # setup colorbar for temps
cbar.set_label('Temperature [$^{\circ}$C]',fontsize=14) # colorbar label

frame = np.zeros((24*32,)) # setup array for storing all 768 temperatures
t_array = []
print("Starting loop")
while True:
    t1 = time.monotonic()
    try:
        mlx.getFrame(frame) # read MLX temperatures into frame var
        data_array = (np.reshape(frame,mlx_shape)) # reshape to 24x32
        therm1.set_data(np.fliplr(data_array)) # flip left to right
        therm1.set_clim(vmin=np.min(data_array),vmax=np.max(data_array)) # set bounds
        cbar.update_normal(therm1) # update colorbar range
        plt.title(f"Max Temp: {np.max(data_array):.1f}C")
        plt.pause(0.001) # required
        #fig.savefig('mlx90640_test_fliplr.png',dpi=300,facecolor='#FCFCFC', bbox_inches='tight') # comment out to speed up
        t_array.append(time.monotonic()-t1)
        print('Sample Rate: {0:2.1f}fps'.format(len(t_array)/np.sum(t_array)))
    except ValueError:
        continue # if error, just read again

It showcases this output:

Is this what you want?

In [76]: fig, ax = plt.subplots(layout='constrained')
    ...: ax.imshow(img, extent=(-12.5,11.5,-17.5,18.5))
    ...: ax.spines[["left", "bottom"]].set_position(("data", 0))
    ...: ax.spines[["top", "right"]].set_visible(False)
    ...: ax.spines[["left", "bottom"]].set_color('w')
    ...: ax.tick_params(axis='both', which='both', color='w')
    ...: for label in ax.xaxis.get_majorticklabels():
    ...:     label.set_color('w')
    ...:     label.set_bbox(dict(facecolor='k', alpha=.3))
    ...: for label in ax.yaxis.get_majorticklabels():
    ...:      label.set_color('w')
    ...:      label.set_bbox(dict(facecolor='k', alpha=.3))

Oh yes, the darker edges around the tick labels are annoying, but at the moment I don't know how to remove them: I could investigate if the OP tells me that this is almost what they want...