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Visual clarity: contrast of message selection is extremely low #229
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Me:
ChatGPT:
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According to https://pickcoloronline.com/ The selected message background color is According to https://color.a11y.com/ContrastPair/?bgcolor=1b1c1b&fgcolor=111111 The above pair of colors failed all contrast tests: |
It is simple enough to change these values, documenting it here in case anyone gets to it first or if someone wants to experiment with values to see what would look best: In the
which currently reference the appropriate palette i.e. the ocean dark variant references |
I did some tweaks and came up with a new scheme, shifted
Let's call it plan A
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Plan B
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I submitted two pull requests, will close one of them based on feedback, feel free to comment / vote. |
On first glance Plan B looks better to my eye. but I will raise this with our Graphics and UI team and let you know what they think |
Yeah team agrees on plan B |
Closing after merging fix in oxen-io#1116 |
Code of conduct
Describe the bug
Selected messages have a low contrast compared to unselected messages, making them hard to distinguish.
To reproduce
Fresh install Session Android, default theme, and select some messages.
In the below example, "Hi this is Alice" is selected, "Hi this is Carol" and "Hi this is Bob" are unselected, they look very closely.
The selected messages have a very closed color / darkness compared to unselected messages.
This makes a moderator's life harder because they often need to delete messages in bulk.
Screenshots or logs
Smartphone (please complete the following information):
Additional context
There are users reporting the message selection visual clarity issue was fixed in some earlier version, but then came back again after theming support was implemented. In other words, it might be a visual regression.
However, on 1.16.3 release note there was
So this could be a disagreement on the sense of visibility as well. At least to me the selected message is not very different to unselected messages.
In any case, visual regression testing is tricky itself. According to [1], "This can result in tens or even hundreds of thousands of potential screens to test".
We might want to investigate specialized testing frameworks for visual regression like [2].
[1] https://applitools.com/blog/visual-ai/
[2] https://percy.io/
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