#vectorization
Live, measured metrics for the hashtag #vectorization from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #vectorization
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Day-by-day usage
measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-29 14:31 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · fosstodon.org (Mastodon public search API) · fetched 2026-07-29 14:31 UTCNo related tags with measured usage found for #vectorization.
Live pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-29 14:31 UTCEverything below is measured over the latest 32 public posts (spanning ~31303 hours).
Posting hours (UTC) — busiest: 12:00
Languages: English (28) · Russian (4)
Avg boosts / post: 0.5
Top of the latest posts
I'm working on a Rust library for explicitly *non-portable* SIMD intrinsics, called `npsimd` <https://docs.rs/npsimd>. The idea is that high-performance vectorized code needs to take advantage of platform-specific functionality, and we need
Version 0.2.0 of `npsimd` is now published, with a new low-level API that supports runtime feature detection (currently only SSE2 is implemented). I'm going to slowly migrate all the existing functionality over to it, and then work on a bet
Inkscape has an impressive feature that allows users to convert images to SVG objects. This process is called "tracing" or "vectorization." But if you expect a 100% faithful representation of your picture, you will be disappointed. https://
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/vectorization