feat: add color search and reusable tooltips

Add dominant-color palette extraction, storage, filtering, and startup backfill so the gallery and Timeline can be filtered from the toolbar color picker.

Introduce a reusable tooltip component and migrate the color filter, update indicator, and gallery filename hover affordances to it.

src-tauri/src/color.rs

@@ -0,0 +1,91 @@
+//! Dominant-color palette extraction for color search.
+//!
+//! Colors are sampled from the already-generated thumbnail (small, fast) rather
+//! than the full image. We coarse-quantize pixels into an RGB histogram, then
+//! return the most populated bins as representative colors with their weight
+//! (fraction of sampled pixels). Search then filters images whose palette has a
+//! color within a distance threshold of the query color.
+
+use image::RgbImage;
+use std::collections::HashMap;
+use std::path::Path;
+
+#[derive(Debug, Clone, Copy)]
+pub struct PaletteColor {
+    pub r: u8,
+    pub g: u8,
+    pub b: u8,
+    /// Fraction of sampled pixels (0.0–1.0) that fell in this color's bin.
+    pub weight: f32,
+}
+
+/// Bits kept per channel when binning. 4 bits → 16 levels/channel → 4096 bins:
+/// coarse enough to group near-identical shades, fine enough to separate hues.
+const QUANT_BITS: u32 = 4;
+/// Cap on sampled pixels so very large frames stay cheap; thumbnails are tiny so
+/// this rarely bites, but the backfill may read arbitrary thumbnail sizes.
+const MAX_SAMPLES: usize = 50_000;
+
+/// Extract up to `k` dominant colors from an RGB image, most-common first.
+pub fn extract_palette(img: &RgbImage, k: usize) -> Vec<PaletteColor> {
+    let pixels = img.as_raw();
+    let pixel_count = pixels.len() / 3;
+    if pixel_count == 0 {
+        return Vec::new();
+    }
+    let step = (pixel_count / MAX_SAMPLES).max(1);
+    let shift = 8 - QUANT_BITS;
+
+    // bin key → (sum_r, sum_g, sum_b, count); summing lets us return the bin's
+    // average color rather than the quantized corner.
+    let mut bins: HashMap<u16, (u64, u64, u64, u64)> = HashMap::new();
+    let mut total: u64 = 0;
+    for pixel in pixels.chunks_exact(3).step_by(step) {
+        let (r, g, b) = (pixel[0], pixel[1], pixel[2]);
+        let key = (((r as u16) >> shift) << (QUANT_BITS * 2))
+            | (((g as u16) >> shift) << QUANT_BITS)
+            | ((b as u16) >> shift);
+        let entry = bins.entry(key).or_insert((0, 0, 0, 0));
+        entry.0 += r as u64;
+        entry.1 += g as u64;
+        entry.2 += b as u64;
+        entry.3 += 1;
+        total += 1;
+    }
+    if total == 0 {
+        return Vec::new();
+    }
+
+    let mut entries: Vec<(u64, u64, u64, u64)> = bins.into_values().collect();
+    entries.sort_unstable_by_key(|entry| std::cmp::Reverse(entry.3));
+    entries
+        .into_iter()
+        .take(k)
+        .map(|(sum_r, sum_g, sum_b, count)| PaletteColor {
+            r: (sum_r / count) as u8,
+            g: (sum_g / count) as u8,
+            b: (sum_b / count) as u8,
+            weight: count as f32 / total as f32,
+        })
+        .collect()
+}
+
+/// Decode a thumbnail file and extract its palette. Used by the backfill pass.
+pub fn extract_palette_from_file(thumbnail_path: &Path, k: usize) -> Option<Vec<PaletteColor>> {
+    let img = image::ImageReader::open(thumbnail_path)
+        .ok()?
+        .decode()
+        .ok()?;
+    Some(extract_palette(&img.into_rgb8(), k))
+}
+
+/// Number of palette colors stored per image.
+pub const PALETTE_SIZE: usize = 5;
+
+/// Max squared RGB distance for a palette color to count as matching a query
+/// color (~70 units in RGB space). Tunable feel/precision of color search.
+pub const MATCH_DISTANCE_SQ: i64 = 4900;
+
+/// Minimum weight (fraction of pixels) a palette color must have to match, so
+/// trivial specks of a color don't trigger a match.
+pub const MATCH_MIN_WEIGHT: f64 = 0.05;