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• Revision 35243 : suivre [35095]

  16 février 2010, par brunobergot@… — Log

  suivre [35095]

• Why is ffmpeg biased when converting to 16-bit integer or 32-bit float RGB output ?

  8 mars 2023, par F.X.

  Consider the following Python invocations, that exercise ffmpeg's ability to convert a 8-bit input into 16-bit integer values or 32-bit float values :

  


  import cv2
import subprocess
import numpy as np

ffmpeg = "ffmpeg -hide_banner -loglevel error -y"
flags = "-sws_flags accurate_rnd+bitexact+full_chroma_int+neighbor -sws_dither none"

for input_color_range in ("tv", "pc"):

    # Generate YUV444 video and encode it losslessly
    subprocess.check_call(rf"{ffmpeg} -y {flags} -color_range {input_color_range} -f lavfi -i yuvtestsrc {flags} -pix_fmt yuv444p -color_range {input_color_range} -x264-params qp=0 -frames 1 -c:v libx264 video_temp.mp4")

    # Extract YUV444 frame, as well as 8-bit int, 16-bit int and 32-bit float frame
    subprocess.check_call(rf"{ffmpeg} -y {flags} -i video_temp.mp4 {flags} -f rawvideo video_temp_444_frame1.yuv")
    subprocess.check_call(rf"{ffmpeg} -y {flags} -i video_temp.mp4 {flags} -color_range pc -pix_fmt rgb24 video_temp_444_frame1_8u.png")
    subprocess.check_call(rf"{ffmpeg} -y {flags} -i video_temp.mp4 {flags} -color_range pc -pix_fmt rgb48be video_temp_444_frame1_16u.png")
    subprocess.check_call(rf"{ffmpeg} -y {flags} -i video_temp.mp4 {flags} -color_range pc -pix_fmt gbrpf32be -f rawvideo video_temp_444_frame1_32f.gbrpf32be")

    # Reead these frames into (height, width, 3) Numpy arrays containing YUV or RGB data
    data_8u = cv2.imread("video_temp_444_frame1_8u.png", cv2.IMREAD_UNCHANGED)[..., ::-1]
    data_16u = cv2.imread("video_temp_444_frame1_16u.png", cv2.IMREAD_UNCHANGED)[..., ::-1]
    data_yuv = np.rollaxis(np.frombuffer(open("video_temp_444_frame1.yuv", "rb").read()).view(np.uint8).reshape((3, 240, 320)), 0, 3).copy()
    data_32f = np.rollaxis(np.frombuffer(open("video_temp_444_frame1_32f.gbrpf32be", "rb").read()).view(np.dtype(">f4")).reshape((3, 240, 320)), 0, 3).copy()
    data_32f[..., (0, 1, 2)] = data_32f[..., (2, 0, 1)]

    # This pixel in yuvtestsrc corresponds to limited-range YUV=(235, 128,
    # 128)=(100%, 0.0, 0.0), which should correspond to 100% white, i.e.
    # RGB=(100%, 100%, 100%).
    if input_color_range == "tv":
        i, j = 10, 294
    # This pixel in yuvtestsrc corresponds to full-range YUV=(255, 128,
    # 128)=(100%, 0.0, 0.0), which should correspond to 100% white, i.e.
    # RGB=(100%, 100%, 100%).
    elif input_color_range == "pc":
        i, j = 10, 319
    else:
        raise Exception(input_color_range)

    # Print pixel values
    print("")
    print(f"Values for {input_color_range}-range input video at ({i}, {j}):")
    print("- 8-bit YUV input   = %s" % data_yuv[i, j, :])
    print("- 8-bit RGB output  = %s (= %s)" % (data_8u[i, j, :], data_8u[i, j, :] / 255))
    print("- 16-bit RGB output = %s (= %s)" % (data_16u[i, j, :], data_16u[i, j, :] / 65535))
    print("- Float RGB output  = %s" % data_32f[i, j, :])


  


  The script first generates a video frame from ffmpeg's YUV test source, encoded with no chroma subsampling (4:4:4) as losslessly as possible.

  


  That video is then used as a reference source to extract the following frames :

  


  

  • The input reference YUV data

  


  • A 8-bit RGB conversion

  


  • A 16-bit RGB conversion

  


  • A 32-bit floating-point RGB conversion

  


  


  One pixel is extracted from each frame, which should contain a 100% white value. The output of the last series of print statements is the following :

  


  Values for tv-range input video at (10, 294):
- 8-bit YUV input   = [235 128 128]
- 8-bit RGB output  = [255 255 255] (= [1. 1. 1.])
- 16-bit RGB output = [65283 65283 65283] (= [0.99615473 0.99615473 0.99615473])
- Float RGB output  = [0.9961547 0.9961547 0.9961547]

Values for pc-range input video at (10, 319):
- 8-bit YUV input   = [255 128 128]
- 8-bit RGB output  = [255 255 255] (= [1. 1. 1.])
- 16-bit RGB output = [65280 65280 65280] (= [0.99610895 0.99610895 0.99610895])
- Float RGB output  = [0.99610895 0.99610895 0.99610895]


  


  While the 8-bit RGB output values are correct, none of the others correctly output a 100% white signal. Why is that ?

  


• Revision 3327 : Le modèle pour les images prenant en compte les largeurs et autres ...

  25 avril 2010, par kent1 — Log

  Le modèle pour les images prenant en compte les largeurs et autres hauteurs fixées au modèle