Report a Bug · Request a Feature
A Docker-image that can be used to run easyVmaf from files in an S3-bucket.
docker build . -t easyvmaf-s3
docker run --rm \
-e AWS_ACCESS_KEY_ID=X \
-e AWS_SECRET_ACCESS_KEY=Y \
easyvmaf-s3 \
-r s3://videos/reference.mp4 \
-d s3://videos/640x360_750000.mp4 \
-o s3://videos/640x360_750000_vmaf.json
services:
autovmaf-s3:
build: .
image: easyvmaf-s3
environment:
- AWS_ACCESS_KEY=X
- AWS_SECRET_ACCESS_KEY=Y
command: easyvmaf-s3 -r s3://videos/reference.mp4 -d s3://videos/640x360_750000.mp4 -o s3://videos/640x360_750000_vmaf.json
usage: easyvmaf_s3.py [-h] -r REFERENCE_INPUT -d DISTORTED_INPUT -o
OUTPUT [--phone] [--model MODEL]
Run easyVMAF on file in S3-bucket.
optional arguments:
-h, --help show this help message and exit
-r REFERENCE_INPUT The s3-url of the reference input. Example:
s3://input-bucket/reference.mp4
-d DISTORTED_INPUT The s3-url of the distorted input. Example:
s3://input-bucket/distorted.mp4
-o OUTPUT The s3-url of the output. This file will be
created Example: s3://output-
bucket/file_vmaf.json
--phone Whether or not to use the phone model for VMAF
analysis.
--model MODEL The VMAF-model to use. Either HD or 4K.
Eyevinn Technology is an independent consultant firm specialized in video and streaming. Independent in a way that we are not commercially tied to any platform or technology vendor.
At Eyevinn, every software developer consultant has a dedicated budget reserved for open source development and contribution to the open source community. This gives us room for innovation, team building and personal competence development. And also gives us as a company a way to contribute back to the open source community.
Want to know more about Eyevinn and how it is to work here? Contact us at work@eyevinn.se!