VQM is a command line program that has 2 main features.
It can calculate the VMAF, SSIM and PSNR of a transcoded video as long as you have the original video as well. Example:
python main.py -ntm -iv original.mp4 -tv transcoded.mp4 -ssim -psnr
It can transcode a video using the x264 (H.264), x265 (H.265) or libaom (AV1) encoder with specified presets (if using x264 or x265) or CRF values.
When using this feature, VQM will transcode the video with each preset/CRF value and calculate the VMAF/SSIM/PSNR of each transcode. A table will be created as well as graphs, so you can see how the values of the quality metrics change depending on the preset/CRF value.
You can find more details about feature 2 as well as example commands, under the Feature 2 section.
VQM creates a table in a file named Table.txt
, and it contains the following:
-psnr
argument.-ssim
argument.-msssim
argument.If feature [2] is used, in addition to the above, the following colums are present:
You can find an example table below. Please note that when feature [1] is used, the first two columns will not exist as they are not applicable.
+-----------+-------------------+----------+-----------+----------------------+
| Preset | Encoding Time (s) | Size | Bitrate | VMAF |
+-----------+-------------------+----------+-----------+----------------------+
| veryslow | 68.12 | 18.70 MB | 2.48 Mbps | 89.75 | 2.51 | 97.62 |
| slower | 32.57 | 20.43 MB | 2.71 Mbps | 89.54 | 2.44 | 97.72 |
| slow | 17.84 | 20.62 MB | 2.74 Mbps | 89.08 | 2.55 | 97.58 |
| medium | 12.16 | 21.24 MB | 2.82 Mbps | 88.88 | 2.56 | 97.57 |
| fast | 10.39 | 22.85 MB | 3.04 Mbps | 88.59 | 2.72 | 97.37 |
| faster | 8.37 | 21.11 MB | 2.80 Mbps | 88.66 | 2.83 | 97.18 |
| veryfast | 5.78 | 17.71 MB | 2.35 Mbps | 84.75 | 4.00 | 95.18 |
| superfast | 3.83 | 34.95 MB | 4.64 Mbps | 88.52 | 3.19 | 96.71 |
| ultrafast | 2.34 | 49.38 MB | 6.56 Mbps | 90.03 | 2.11 | 98.24 |
+-----------+-------------------+----------+-----------+----------------------+
File Transcoded: aqp60.mkv
Bitrate: 12.34 Mbps
Encoder used for the transcodes: x264
CRF 23 was used.
Filter(s) used: None
n_subsample: 1
The following command was used to produce such a table:
python main.py -iv aqp60.mkv -p veryslow slower slow medium fast faster veryfast superfast ultrafast
When using feature [2], two types of graphs are created:
_Example SSIM and PSNR graphs can be found in the example_graphs folder._
There are two modes; CRF comparison mode and presets comparison mode. You must specify multiple CRF values OR presets and this program will automatically transcode the video with each preset/CRF value, and the quality of each transcode is calculated using the VMAF and (optionally) the SSIM and PSNR metrics.
CRF comparison mode example:
python main.py -iv original.mp4 -crf 18 19 20 -p veryfast -ssim -psnr
You must specify the CRF values that you want to compare and (optionally) one preset. If you do not specify a preset, the medium
preset will be used.
Presets comparison mode example:
python main.py -iv original.mp4 -p medium fast faster -crf 18 -ssim -psnr
You must specify the presets that you want to compare and (optionally) one CRF value. If you do specify a CRF value, a CRF of 23 will be used.
Overview Mode:
A recent addition to this program is "overview mode", which can be used with feature [2] by specifying the --interval
and --clip-length
arguments. The benefit of this mode is especially apparent with long videos, such as movies. What this mode does is create a lossless "overview video" by grabbing a <clip length>
seconds long segment every <interval>
seconds from the original video. The transcodes and computation of the quality metrics are done using this overview video instead of the original video. As the overview video can be much shorter than the original, the process of trancoding and computing the quality metrics is much quicker, while still being a fairly accurate representation of the original video as the program goes through the whole video and grabs, say, a two-second-long segment every 60 seconds.
Example: python main.py -iv original.mp4 -crf 17 18 19 --interval 60 --clip-length 2
In the example above, we're grabbing a two-second-long clip (--clip-length 2
) every minute (--interval 60
) in the video. These 2-second long clips are concatenated to make the overview video. A 1-hour long video is turned into an overview video that is 1 minute and 58 seconds long. The benefit of overview mode should now be clear - transcoding and computing the quality metrics of a <2 minutes long video is much quicker than doing so with an hour long video.
An alternative method of reducing the execution time of this program is by only using the first x seconds of the original video (you can do this with the -t
argument), but Overview Mode provides a better representation of the whole video.
You can check the available arguments with python main.py -h
:
usage: main.py [-h] [--av1-cpu-used <1-8>] [-cl <1-60>] [-crf <0-51> [<0-51> ...]] [-dp DECIMAL_PLACES] [-e {x264,x265,libaom-av1}] [-i <1-600>] [-subsample SUBSAMPLE]
[--n-threads N_THREADS] [-ntm] [-o OUTPUT_FOLDER] -iv INPUT_VIDEO [-p <preset/s> [<preset/s> ...]] [--phone-model] [-sc] [-psnr] [-ssim] [-msssim]
[-t SECONDS] [-tv TRANSCODED_VIDEO_PATH] [-vf VIDEO_FILTERS]
optional arguments:
-h, --help show this help message and exit
Encoding Arguments:
--av1-cpu-used <1-8> Only applicable if the libaom-av1 (AV1) encoder is chosen. Set the quality/encoding speed tradeoff. Lower values mean slower encoding but better
quality, and vice-versa (default: 5)
-crf <0-51> [<0-51> ...]
Specify the CRF value(s) to use
-e {x264,x265,libaom-av1}, --video-encoder {x264,x265,libaom-av1}
Specify whether to use the x264 (H.264), x265 (H.265) or libaom-av1 (AV1) encoder (default: x264)
-p <preset/s> [<preset/s> ...], --preset <preset/s> [<preset/s> ...]
Specify the preset(s) to use (default: medium)
VMAF Arguments:
-subsample SUBSAMPLE Set a value for libvmaf's n_subsample option if you only want the VMAF/SSIM/PSNR to be calculated for every nth frame. Without this argument,
VMAF/SSIM/PSNR scores will be calculated for every frame (default: 1)
--n-threads N_THREADS
Specify the number of threads to use when calculating VMAF
--phone-model Enable VMAF phone model (default: False)
Overview Mode Arguments:
-cl <1-60>, --clip-length <1-60>
When using Overview Mode, a X seconds long segment is taken from the original video every --interval seconds and these segments are concatenated to
create the overview video. Specify a value for X (in the range 1-60) (default: 1)
-i <1-600>, --interval <1-600>
To activate Overview Mode, this argument must be specified. Overview Mode creates a lossless overview video by grabbing a --clip-length long segment
every X seconds from the original video. Specify a value for X (in the range 1-600) (default: None)
General Arguments:
-dp DECIMAL_PLACES, --decimal-places DECIMAL_PLACES
The number of decimal places to use for the data in the table (default: 2)
-ntm, --no-transcoding-mode
Enable "no transcoding mode", which allows you to calculate the VMAF/SSIM/PSNR for a video that you have already transcoded. The original and
transcoded video paths must be specified using the -iv and -tv arguments, respectively. Example: python main.py -ntm -iv original.mp4 -tv
transcoded.mp4 (default: False)
-o OUTPUT_FOLDER, --output-folder OUTPUT_FOLDER
Use this argument if you want a specific name for the output folder. If you want the name of the output folder to contain a space, the string must
be surrounded in double quotes (default: None)
-iv INPUT_VIDEO, --input-video INPUT_VIDEO
Input video. Can be a relative or absolute path, or an URL. If the path contains a space, it must be surrounded in double
quotes (default: None)
-sc, --show-commands Show the FFmpeg commands that are being run. (default: False)
-t SECONDS, --encode-length SECONDS
Create a lossless version of the original video that is just the first x seconds of the video. This cut version of the original video is what will
be transcoded and used as the reference video. You cannot use this option in conjunction with the -i or -cl arguments (default: None)
-tv TRANSCODED_VIDEO, --transcoded-video TRANSCODED_VIDEO
Transcoded video. Can be a relative or absolute path, or an URL. Only applicable when using the -ntm mode.
-vf VIDEO_FILTERS, --video-filters VIDEO_FILTERS
Add FFmpeg video filter(s). Each filter must be separated by a comma. Example: -vf bwdif=mode=0,crop=1920:800:0:140 (default: None)
Optional Metrics:
-psnr, --calculate-psnr
Enable PSNR calculation in addition to VMAF (default: False)
-ssim, --calculate-ssim
Enable SSIM calculation in addition to VMAF (default: False)
-msssim, --calculate-msssim
Enable MS-SSIM calculation in addition to VMAF (default: False)
pip install -r requirements.txt
You can check whether your build of FFmpeg has libvmaf/libx264/libx265/libaom with ffmpeg -buildconf
.
Look for --enable-libvmaf
, --enable-libx265
, --enable-libx264
and --enable-libaom
.
Windows: https://www.gyan.dev/ffmpeg/builds/ffmpeg-git-essentials.7z
macOS: https://evermeet.cx/ffmpeg - download both ffmpeg and ffprobe and add the binaries to your PATH.
Alternatively, you can install FFmpeg using Homebrew - brew install ffmpeg
Linux (kernels 3.2.0+): https://johnvansickle.com/ffmpeg.
Download the git master build. Installation instructions, as well as how to add FFmpeg and FFprobe to your PATH, can be found here.
Two model files are provided, vmaf_v0.6.1.json
and vmaf_4k_v0.6.1.json
. There is also the phone model that can be enabled by using the -pm
argument.
This program uses the vmaf_v0.6.1.json
model file by default, which is "based on the assumption that the viewers sit in front of a 1080p display in a living room-like environment with the viewing distance of 3x the screen height (3H)."
The phone model was created because the original model "did not accurately reflect how a viewer perceives quality on a phone. In particular, due to smaller screen size and longer viewing distance relative to the screen height (>3H), viewers perceive high-quality videos with smaller noticeable differences. For example, on a mobile phone, there is less distinction between 720p and 1080p videos compared to other devices. With this in mind, we trained and released a VMAF phone model."
The 4K model (vmaf_4k_v0.6.1.json
) "predicts the subjective quality of video displayed on a 4K TV and viewed from a distance of 1.5H. A viewing distance of 1.5H is the maximum distance for the average viewer to appreciate the sharpness of 4K content. The 4K model is similar to the default model in the sense that both models capture quality at the critical angular frequency of 1/60 degree/pixel. However, the 4K model assumes a wider viewing angle, which affects the foveal vs peripheral vision that the subject uses."
The source of the quoted text, plus additional information about VMAF (such as the correct way to calculate VMAF), can be found here.
If you are transcoding a video that will be viewed on a mobile phone, you can add the -pm
argument which will enable the phone model.
If you are transcoding a video that will be viewed on a 4K display, the default model (vmaf_v0.6.1.json
) is fine if you are only interested in relative VMAF scores, i.e. the score differences between different presets/CRF values, but if you are interested in absolute scores, it may be better to use the 4K model file which predicts the subjective quality of video displayed on a 4K screen at a distance of 1.5x the height of the screen. To use the 4K model, replace the value of the model_file_path
variable in libvmaf.py with 'vmaf_models/vmaf_4k_v0.6.1.json'
.