Calculate quality metrics with FFmpeg (SSIM, PSNR, VMAF)
Project description
Simple script for calculating quality metrics with FFmpeg.
Currently supports PSNR, SSIM and VMAF. It will output:
the per-frame metrics
metrics for each component (Y, U, V)
global statistics (min/max/average/standard deviation)
Author: Werner Robitza werner.robitza@gmail.com
Contents:
Requirements
Python 3.6 or higher
FFmpeg:
download a static build from their website)
put the ffmpeg executable in your $PATH
Optionally, you may install FFmpeg with libvmaf support to run VMAF score calculation. Under Linux and macOS, this can be done with the following steps:
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install.sh)"
brew tap homebrew-ffmpeg/ffmpeg
brew install homebrew-ffmpeg/ffmpeg/ffmpeg --with-libvmaf
This may take a while.
Under Windows, you have to install ffmpeg and VMAF manually, or using helper scripts.
Installation
pip3 install ffmpeg_quality_metrics
Or clone this repository, then run the tool with python3 -m ffmpeg_quality_metrics
Usage
In the simplest case, if you have a distorted (encoded, maybe scaled) version and the reference:
ffmpeg_quality_metrics distorted.mp4 reference.avi
The distorted file will be automatically scaled to the resolution of the reference.
Extended Options
See ffmpeg_quality_metrics -h:
usage: ffmpeg_quality_metrics [-h] [-n] [-v] [-ev] [-m MODEL_PATH] [-p] [-dp] [-s {fast_bilinear,bilinear,bicubic,experimental,neighbor,area,bicublin,gauss,sinc,lanczos,spline}] [-of {json,csv}] [-r FRAMERATE] dist ref positional arguments: dist input file, distorted ref input file, reference optional arguments: -h, --help show this help message and exit -n, --dry-run Do not run command, just show what would be done (default: False) -v, --verbose Show verbose output (default: False) -ev, --enable-vmaf Enable VMAF computation; calculates VMAF as well as SSIM and PSNR (default: False) -m MODEL_PATH, --model-path MODEL_PATH Set path to VMAF model file (.pkl) (default: None) -p, --phone-model Enable VMAF phone model (default: False) -dp, --disable-psnr-ssim Disable PSNR/SSIM computation. Use VMAF to get YUV estimate. (default: False) -s {fast_bilinear,bilinear,bicubic,experimental,neighbor,area,bicublin,gauss,sinc,lanczos,spline}, --scaling-algorithm {fast_bilinear,bilinear,bicubic,experimental,neighbor,area,bicublin,gauss,sinc,lanczos,spline} Scaling algorithm for ffmpeg (default: bicubic) -of {json,csv}, --output-format {json,csv} output in which format (default: json) -r FRAMERATE, --framerate FRAMERATE force an input framerate (default: None)
Specifying VMAF Model
If you are running Windows, or if you want to specify a different VMAF model file than the default, you need both a .pkl and a .pkl.model file in the same path for VMAF to be able to load the model.
Use the -m/--model-path option to set the path to the model file, by pointing it to the .pkl file (not the .pkl.model file!).
For example, if you have the model files saved at:
/usr/local/opt/libvmaf/share/model/vmaf_v0.6.1.pkl /usr/local/opt/libvmaf/share/model/vmaf_v0.6.1.pkl.model
Run the command with:
ffmpeg_quality_metrics dist.mkv ref.mkv -m /usr/local/opt/libvmaf/share/model/vmaf_v0.6.1.pkl
Running with Docker
If you don’t want to deal with dependencies, build the image with Docker:
docker build -t ffmpeg_quality_metrics .
This installs ffmpeg with all dependencies. You can then run the container, which basically calls the Python script. To help you with mounting the volumes (since your videos are not stored in the container), you can run a helper script:
./docker_run.sh
Check the output of the above command for more help.
Output
JSON or CSV, including individual fields for Y, U, V, and averages, as well as frame numbers.
JSON example:
➜ ffmpeg_quality_metrics test/dist-854x480.mkv test/ref-1280x720.mkv --enable-vmaf { "vmaf": [ { "adm2": 0.69908, "motion2": 0.0, "ms_ssim": 0.89698, "psnr": 18.58731, "ssim": 0.92415, "vif_scale0": 0.53962, "vif_scale1": 0.71805, "vif_scale2": 0.75205, "vif_scale3": 0.77367, "vmaf": 14.07074, "n": 1 }, { "adm2": 0.69846, "motion2": 0.35975, "ms_ssim": 0.89806, "psnr": 18.60299, "ssim": 0.9247, "vif_scale0": 0.54025, "vif_scale1": 0.71961, "vif_scale2": 0.75369, "vif_scale3": 0.77607, "vmaf": 14.48034, "n": 2 }, { "adm2": 0.69715, "motion2": 0.35975, "ms_ssim": 0.89879, "psnr": 18.6131, "ssim": 0.92466, "vif_scale0": 0.5391, "vif_scale1": 0.71869, "vif_scale2": 0.75344, "vif_scale3": 0.77616, "vmaf": 14.27326, "n": 3 } ], "psnr": [ { "n": 1, "mse_avg": 536.71, "mse_y": 900.22, "mse_u": 234.48, "mse_v": 475.43, "psnr_avg": 20.83, "psnr_y": 18.59, "psnr_u": 24.43, "psnr_v": 21.36 }, { "n": 2, "mse_avg": 535.29, "mse_y": 896.98, "mse_u": 239.4, "mse_v": 469.49, "psnr_avg": 20.84, "psnr_y": 18.6, "psnr_u": 24.34, "psnr_v": 21.41 }, { "n": 3, "mse_avg": 535.04, "mse_y": 894.89, "mse_u": 245.8, "mse_v": 464.43, "psnr_avg": 20.85, "psnr_y": 18.61, "psnr_u": 24.22, "psnr_v": 21.46 } ], "ssim": [ { "n": 1, "ssim_y": 0.934, "ssim_u": 0.96, "ssim_v": 0.942, "ssim_avg": 0.945 }, { "n": 2, "ssim_y": 0.934, "ssim_u": 0.96, "ssim_v": 0.943, "ssim_avg": 0.946 }, { "n": 3, "ssim_y": 0.934, "ssim_u": 0.959, "ssim_v": 0.943, "ssim_avg": 0.945 } ], "global": { "ssim": { "average": 0.9453333333333332, "stdev": 0.00047140452079103207, "min": 0.945, "max": 0.946 }, "psnr": { "average": 20.84, "stdev": 0.008164965809278536, "min": 20.83, "max": 20.85 }, "vmaf": { "average": 14.27478, "stdev": 0.16722195390159322, "min": 14.07074, "max": 14.48034 } }, "input_file_dist": "test/dist-854x480.mkv", "input_file_ref": "test/ref-1280x720.mkv" }
CSV example:
➜ ffmpeg_quality_metrics test/dist-854x480.mkv test/ref-1280x720.mkv --enable-vmaf -of csv n,adm2,motion2,ms_ssim,psnr,ssim,vif_scale0,vif_scale1,vif_scale2,vif_scale3,vmaf,mse_avg,mse_u,mse_v,mse_y,psnr_avg,psnr_u,psnr_v,psnr_y,ssim_avg,ssim_u,ssim_v,ssim_y,input_file_dist,input_file_ref 1,0.70704,0.0,0.89698,18.58731,0.92415,0.53962,0.71805,0.75205,0.77367,15.44212,536.71,234.48,475.43,900.22,20.83,24.43,21.36,18.59,0.945,0.96,0.942,0.934,test/dist-854x480.mkv,test/ref-1280x720.mkv 2,0.7064,0.35975,0.89806,18.60299,0.9247,0.54025,0.71961,0.75369,0.77607,15.85038,535.29,239.4,469.49,896.98,20.84,24.34,21.41,18.6,0.946,0.96,0.943,0.934,test/dist-854x480.mkv,test/ref-1280x720.mkv 3,0.70505,0.35975,0.89879,18.6131,0.92466,0.5391,0.71869,0.75344,0.77616,15.63546,535.04,245.8,464.43,894.89,20.85,24.22,21.46,18.61,0.945,0.959,0.943,0.934,test/dist-854x480.mkv,test/ref-1280x720.mkv
License
ffmpeg_quality_metrics, Copyright (c) 2019 Werner Robitza
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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