You can see all the flags here.

It looks like cv2.CAP_OPENCV_MJPEG is what you are looking for.

The following test creates MJPEG synthetic AVI video file, and reads the video using cv2.CAP_OPENCV_MJPEG backend:

import numpy as np
import cv2

#availableBackends = [cv2.videoio_registry.getBackendName(b) for b in cv2.videoio_registry.getBackends()]
#print(availableBackends)

print('cv2.CAP_OPENCV_MJPEG = ' + str(cv2.CAP_OPENCV_MJPEG))


intput_filename = 'vid.avi'

# Generate synthetic video files to be used as input:
###############################################################################
width, height, n_frames = 640, 480, 100  # 100 frames, resolution 640x480

# Use motion JPEG codec (for testing)
synthetic_out = cv2.VideoWriter(intput_filename, cv2.VideoWriter_fourcc(*'MJPG'), 25, (width, height))

for i in range(n_frames):
    img = np.full((height, width, 3), 60, np.uint8)
    cv2.putText(img, str(i+1), (width//2-100*len(str(i+1)), height//2+100), cv2.FONT_HERSHEY_DUPLEX, 10, (30, 255, 30), 20)  # Green number
    synthetic_out.write(img)

synthetic_out.release()
###############################################################################


# Read the video using CV_MJPEG backend
###############################################################################
cap = cv2.VideoCapture(intput_filename, cv2.CAP_OPENCV_MJPEG)

# Keep iterating break
while True:
    ret, frame = cap.read()  # Read frame from first video

    if ret:
        cv2.imshow('frame', frame)  # Display frame for testing
        cv2.waitKey(100) #Wait 100msec (for debugging)
    else:
        break

cap.release() #Release must be inside the outer loop
###############################################################################

For anyone who is facing with the same issue. After deeper search I have found that intel also has a function does BGR->YUV conversion using hardware acceleration. It is fast comparing the above cvtBGRtoTwoPlaneYUV() function(~4x times faster). However, it was still slow for my use case. I had to get 30FPS using Intel(R) UDH Graphics 620, apparently the only solution for now is getting a better GPU. The samples for use case: https://github.com/sivabudh/intel-media-sdk-tutorials/tree/master/simple_6_encode_vmem_vpp_preproc

I just have added OpenCV X86 lib and I have written my own function that reads from CV::MAT rather than a file.