Workaround to avoid way to bright frame while using Lepton camera

capture.py

import cv2
import subprocess
import numpy as np
# I'm using this package for convenience detecting and capturing Lepton camera. It's not neccessary tho.
from flirpy.camera.lepton import Lepton


def ktoc(val):
    return (val - 27315) / 100.0

def ctok(val):
    return val * 100 + 27315

def generate_colour_map():
    lut = np.zeros((256, 1, 3), dtype=np.uint8)

    colourmap_ironblack = [
        255, 255, 255, 253, 253, 253, 251, 251, 251, 249, 249, 249, 247, 247,
        247, 245, 245, 245, 243, 243, 243, 241, 241, 241, 239, 239, 239, 237,
        237, 237, 235, 235, 235, 233, 233, 233, 231, 231, 231, 229, 229, 229,
        227, 227, 227, 225, 225, 225, 223, 223, 223, 221, 221, 221, 219, 219,
        219, 217, 217, 217, 215, 215, 215, 213, 213, 213, 211, 211, 211, 209,
        209, 209, 207, 207, 207, 205, 205, 205, 203, 203, 203, 201, 201, 201,
        199, 199, 199, 197, 197, 197, 195, 195, 195, 193, 193, 193, 191, 191,
        191, 189, 189, 189, 187, 187, 187, 185, 185, 185, 183, 183, 183, 181,
        181, 181, 179, 179, 179, 177, 177, 177, 175, 175, 175, 173, 173, 173,
        171, 171, 171, 169, 169, 169, 167, 167, 167, 165, 165, 165, 163, 163,
        163, 161, 161, 161, 159, 159, 159, 157, 157, 157, 155, 155, 155, 153,
        153, 153, 151, 151, 151, 149, 149, 149, 147, 147, 147, 145, 145, 145,
        143, 143, 143, 141, 141, 141, 139, 139, 139, 137, 137, 137, 135, 135,
        135, 133, 133, 133, 131, 131, 131, 129, 129, 129, 126, 126, 126, 124,
        124, 124, 122, 122, 122, 120, 120, 120, 118, 118, 118, 116, 116, 116,
        114, 114, 114, 112, 112, 112, 110, 110, 110, 108, 108, 108, 106, 106,
        106, 104, 104, 104, 102, 102, 102, 100, 100, 100, 98, 98, 98, 96, 96,
        96, 94, 94, 94, 92, 92, 92, 90, 90, 90, 88, 88, 88, 86, 86, 86, 84, 84,
        84, 82, 82, 82, 80, 80, 80, 78, 78, 78, 76, 76, 76, 74, 74, 74, 72, 72,
        72, 70, 70, 70, 68, 68, 68, 66, 66, 66, 64, 64, 64, 62, 62, 62, 60, 60,
        60, 58, 58, 58, 56, 56, 56, 54, 54, 54, 52, 52, 52, 50, 50, 50, 48, 48,
        48, 46, 46, 46, 44, 44, 44, 42, 42, 42, 40, 40, 40, 38, 38, 38, 36, 36,
        36, 34, 34, 34, 32, 32, 32, 30, 30, 30, 28, 28, 28, 26, 26, 26, 24, 24,
        24, 22, 22, 22, 20, 20, 20, 18, 18, 18, 16, 16, 16, 14, 14, 14, 12, 12,
        12, 10, 10, 10, 8, 8, 8, 6, 6, 6, 4, 4, 4, 2, 2, 2, 0, 0, 0, 0, 0, 9,
        2, 0, 16, 4, 0, 24, 6, 0, 31, 8, 0, 38, 10, 0, 45, 12, 0, 53, 14, 0,
        60, 17, 0, 67, 19, 0, 74, 21, 0, 82, 23, 0, 89, 25, 0, 96, 27, 0, 103,
        29, 0, 111, 31, 0, 118, 36, 0, 120, 41, 0, 121, 46, 0, 122, 51, 0, 123,
        56, 0, 124, 61, 0, 125, 66, 0, 126, 71, 0, 127, 76, 1, 128, 81, 1, 129,
        86, 1, 130, 91, 1, 131, 96, 1, 132, 101, 1, 133, 106, 1, 134, 111, 1,
        135, 116, 1, 136, 121, 1, 136, 125, 2, 137, 130, 2, 137, 135, 3, 137,
        139, 3, 138, 144, 3, 138, 149, 4, 138, 153, 4, 139, 158, 5, 139, 163,
        5, 139, 167, 5, 140, 172, 6, 140, 177, 6, 140, 181, 7, 141, 186, 7,
        141, 189, 10, 137, 191, 13, 132, 194, 16, 127, 196, 19, 121, 198, 22,
        116, 200, 25, 111, 203, 28, 106, 205, 31, 101, 207, 34, 95, 209, 37,
        90, 212, 40, 85, 214, 43, 80, 216, 46, 75, 218, 49, 69, 221, 52, 64,
        223, 55, 59, 224, 57, 49, 225, 60, 47, 226, 64, 44, 227, 67, 42, 228,
        71, 39, 229, 74, 37, 230, 78, 34, 231, 81, 32, 231, 85, 29, 232, 88,
        27, 233, 92, 24, 234, 95, 22, 235, 99, 19, 236, 102, 17, 237, 106, 14,
        238, 109, 12, 239, 112, 12, 240, 116, 12, 240, 119, 12, 241, 123, 12,
        241, 127, 12, 242, 130, 12, 242, 134, 12, 243, 138, 12, 243, 141, 13,
        244, 145, 13, 244, 149, 13, 245, 152, 13, 245, 156, 13, 246, 160, 13,
        246, 163, 13, 247, 167, 13, 247, 171, 13, 248, 175, 14, 248, 178, 15,
        249, 182, 16, 249, 185, 18, 250, 189, 19, 250, 192, 20, 251, 196, 21,
        251, 199, 22, 252, 203, 23, 252, 206, 24, 253, 210, 25, 253, 213, 27,
        254, 217, 28, 254, 220, 29, 255, 224, 30, 255, 227, 39, 255, 229, 53,
        255, 231, 67, 255, 233, 81, 255, 234, 95, 255, 236, 109, 255, 238, 123,
        255, 240, 137, 255, 242, 151, 255, 244, 165, 255, 246, 179, 255, 248,
        193, 255, 249, 207, 255, 251, 221, 255, 253, 235, 255, 255, 24]

    def chunk(
        ulist, step): return map(
            lambda i: ulist[i: i + step],
        range(0, len(ulist),
               step))

    chunks = chunk(colourmap_ironblack, 3)

    red = []
    green = []
    blue = []

    for chunk in chunks:
        red.append(chunk[0])
        green.append(chunk[1])
        blue.append(chunk[2])

    lut[:, 0, 0] = blue

    lut[:, 0, 1] = green

    lut[:, 0, 2] = red

    return lut

def raw_to_8bit(data):
  cv2.normalize(data, data, 0, 65535, cv2.NORM_MINMAX)
  np.right_shift(data, 8, data)
  return cv2.cvtColor(np.uint8(data), cv2.COLOR_GRAY2RGB)

def display_temperature(img, val_k, loc, color):
  val = ktoc(val_k)
  cv2.putText(img,"{0:.1f} C".format(val), loc, cv2.FONT_HERSHEY_SIMPLEX, 0.75, color, 2)
  x, y = loc
  cv2.line(img, (x - 2, y), (x + 2, y), color, 1)
  cv2.line(img, (x, y - 2), (x, y + 2), color, 1)

cam = Lepton()
colour_map = generate_colour_map()

while True:
    img_raw = cam.grab()
    # Getting numpy array to further process
    arr_raw = np.array(img_raw)
    # Replacing array values if the !value > 0
    arr_processed = np.where(arr_raw > 0, arr_raw, ctok(20))
    arr_resized = cv2.resize(arr_processed[:,:], (640, 480))
    minVal, maxVal, minLoc, maxLoc = cv2.minMaxLoc(arr_resized)
    img = raw_to_8bit(arr_resized)
    img_ironblack = cv2.LUT(img, colour_map)
    display_temperature(img, maxVal, maxLoc, (0, 0, 255))
    display_temperature(img_ironblack, maxVal, maxLoc, (0, 0, 255))

    cv2.imshow('Lepton', img)
    cv2.imshow('Lepton(ironblack)', img_ironblack)

    if cv2.waitKey(5) == 27:
        break

cv2.destroyAllWindows()
cam.close()