Not all parameters are supported by all cameras - actually, they are one of the most troublesome part of the OpenCV library. Each camera type - from android cameras to USB cameras to professional ones offer a different interface to modify its parameters. There are many branches in OpenCV code to support as many of them, but of course not all possibilities are covered.

What you can do is to investigate your camera driver, write a patch for OpenCV and send it to code.opencv.org. This way others will enjoy your work, the same way you enjoy others'.

There is also a possibility that your camera does not support your request - most USB cams are cheap and simple. Maybe that parameter is just not available for modifications.

If you are sure the camera supports a given param (you say the camera manufacturer provides some code) and do not want to mess with OpenCV, you can wrap that sample code in C++ with boost::python, to make it available in Python. Then, enjoy using it.

i think finally i found a solution, at least for my problem,

capture = cv2.VideoCapture(id)
capture.set(cv2.CAP_PROP_AUTO_EXPOSURE, 3) # auto mode
capture.set(cv2.CAP_PROP_AUTO_EXPOSURE, 1) # manual mode
capture.set(cv2.CAP_PROP_EXPOSURE, desired_exposure_value)

i have to first set the auto_exposure to 3 (auto mode)
then i have to set it to 1 (manual mode)
and then i can set the manual exposure

you can set the settings with shell too
list available options

video_id=1
v4l2-ctl --device /dev/video$video_id -l

def set_manual_exposure(dev_video_id, exposure_time):
    commands = [
        ("v4l2-ctl --device /dev/video"+str(id)+" -c exposure_auto=3"),
        ("v4l2-ctl --device /dev/video"+str(id)+" -c exposure_auto=1"),
        ("v4l2-ctl --device /dev/video"+str(id)+" -c exposure_absolute="+str(exposure_time))
    ]
    for c in commands: 
        os.system(c)
# usage 
set_manual_exposure(1, 18)

There is a method available to change properties of VideoCapture object in OpenCV which can be used to set exposure of input image.

cap = cv2.VideoCapture(0)
cap.set(cv2.CAP_PROP_EXPOSURE, 40) 

However this parameter is not supported by all cameras. Each camera type offers a different interface to set its parameters. There are many branches in OpenCV code to support as many of them, but of course not all the possibilities are covered.

Same is the case with my camera. So I had to find a different solution. That is using v4l2_ctl utility from command line terminal.

v4l2-ctl -d /dev/video0 -c exposure_absolute=40

But this retains its value for current video session only. That means you have to start video preview first and then set this property As soon as VideoCapture is released, the exposure value is restored to default.

I wanted to control exposure within my python script, so I used subprocess module to run linux bash command. e.g.

import subprocess
subprocess.check_call("v4l2-ctl -d /dev/video0 -c exposure_absolute=40",shell=True)

I'm no expert on that topic but I managed to manually set the exposure for an RPi 4 with a camera v2.1. I set the CAP_PROP_AUTO_EXPOSURE to 0.75 and CAP_PROP_EXPOSURE to 0. That left me with a black frame (as expected I guess). Increasing the exposure value gives gradually brighter images. For values above something like 80 it stopped getting any brighter.

This code gradually increases the exposure after each displayed frame and works for me:

import cv2

# Open Pi Camera
cap = cv2.VideoCapture(0)
# Set auto exposure to false
cap.set(cv2.CAP_PROP_AUTO_EXPOSURE, 0.75)

exposure = 0
while cap.isOpened():
    # Grab frame
    ret, frame = cap.read()
    # Display if there is a frame
    if ret:
        cv2.imshow('Frame', frame)
        if cv2.waitKey(25) & 0xFF == ord('q'):
            break
    # Set exposure manually
    cap.set(cv2.CAP_PROP_EXPOSURE, exposure)
    # Increase exposure for every frame that is displayed
    exposure += 0.5

# Close everything
cap.release()
cv2.destroyAllWindows()

Cheers,

Simon