hoernschen/dendrite
1
0
Fork 0
mirror of https://github.com/hoernschen/dendrite.git synced 2025-07-30 04:52:46 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

Update Docker files and remove references to gb (#703)

Browse source 
Fix Docker files which had been forgotten in #594 and update scripts and docs to remove references to gb.

I also removed the `jenkins` directory which is outdated. We can revert f8d7e99 if we realise that it was a mistake to do so.
This commit is contained in:
Brendan Abolivier 2019-05-22 10:44:25 +01:00 • committed by GitHub
parent 74827428bd
commit e1ec98e248
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
8 changed files with 13 additions and 77 deletions
Download patch file Download diff file Expand all files Collapse all files

2
mediaapi/README.md
View file

@ -18,7 +18,7 @@ See the sample below for image quality with nfnt/resize:
### bimg (uses libvips C library)
Alternatively one can use `gb build -tags bimg` to use bimg from https://github.com/h2non/bimg (MIT-licensed) which uses libvips from https://github.com/jcupitt/libvips (LGPL v2.1+ -licensed). libvips is a C library and must be installed/built separately. See the github page for details. Also note that libvips in turn has dependencies with a selection of FOSS licenses.
Alternatively one can use `go build -tags bimg` to use bimg from https://github.com/h2non/bimg (MIT-licensed) which uses libvips from https://github.com/jcupitt/libvips (LGPL v2.1+ -licensed). libvips is a C library and must be installed/built separately. See the github page for details. Also note that libvips in turn has dependencies with a selection of FOSS licenses.
bimg and libvips have significantly better performance than nfnt/resize but produce slightly less-sharp images. bimg uses a box filter for downscaling to within about 200% of the target scale and then uses Lanczos3 for the last bit. This is a much faster approach but comes at the expense of sharpness. (~295ms in total for pre-generating 32x32-crop, 96x96-crop, 320x240-scale, 640x480-scale and 800x600-scale from a given JPEG image on a given machine.)