Operation "linear" does not work with uncompressed TIFF

[stefanpieper]

Possible bug

Is this a possible bug in a feature of sharp, unrelated to installation?

• Running npm install sharp completes without error.
• Running node -e "require('sharp')" completes without error.

Are you using the latest version of sharp?

• I am using the latest version of sharp as reported by npm view sharp dist-tags.latest.

What is the output of running npx envinfo --binaries --system --npmPackages=sharp --npmGlobalPackages=sharp?

  System:
    OS: macOS 12.6.1
    CPU: (10) arm64 Apple M1 Max
    Memory: 3.44 GB / 32.00 GB
    Shell: 5.8.1 - /bin/zsh
  Binaries:
    Node: 16.16.0 - ~/.nvm/versions/node/v16.16.0/bin/node
    npm: 8.11.0 - ~/.nvm/versions/node/v16.16.0/bin/npm
  npmPackages:
    sharp: ^0.31.2 => 0.31.2 

What are the steps to reproduce?

When doing a conversion to uncompressed tiff and "linear" in the same pipeline, the resulting image is not as expected.

What is the expected behaviour?

The image should be output by the sample code below "as is" (linear(1, 0) being an idempotent operation). This works well with other formats than uncompressed TIFF.

Please provide a minimal, standalone code sample, without other dependencies, that demonstrates this problem

  let buffer = await fs.readFileSync(path.join(__dirname, "resources/images/random-small.jpeg"));
  buffer = await sharp(buffer)
    .tiff({compression: 'none'})
    .linear(1, 0)
    .toBuffer();
  await sharp(buffer)
    .jpeg()
    .toFile(path.join(__dirname, "resources/transformed/linear-fail.jpeg"));

Please provide sample image(s) that help explain this problem

This is my test image that I would expect to remain basically unchanged in output with the code above:

This is what the code actually produces (the image is nearly all-white and can therefore hardly be seen):

[lovell]

Thanks for reporting, commit 0265d30 ensures the output is integral rather than float, plus adds a couple of tests that would have caught this.

[stefanpieper]

Beautiful - thanks a lot!

[lovell]

v0.31.3 now available, thanks again for reporting.