H1K0
88849cc16b
Adds a 64-bit dHash perceptual hash (internal/imagehash, built on the existing disintegration/imaging — no new dependency) and starts populating the long-unused data.files.phash column: - Upload sets phash inline for images (cheap, from the in-memory bytes). - Replace recomputes it from new content for images and clears it for anything else, so a stale hash never survives a content swap. - FileRepo.SetPHash sets/clears the hash (used by Replace and, later, the dedup backfill). - DiskStorage.VideoFrameMiddle extracts a frame from the middle of a clip (ffprobe duration -> ffmpeg -ss duration/2), avoiding the shared-intro collision a fixed early offset causes. It is a concrete method, not part of the storage port: only the dedup CLI needs it, keeping ffmpeg off the upload path. Video phashes are therefore computed by that CLI, not at upload time. - DUPLICATE_HASH_THRESHOLD config (default 10/64) for the later pair rescan. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
100 lines
2.7 KiB
Go
100 lines
2.7 KiB
Go
package imagehash
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import (
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"bytes"
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"image"
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"image/color"
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"image/jpeg"
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"image/png"
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"math"
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"testing"
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)
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// radial renders a smooth grayscale image whose brightness falls off with
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// distance from (cx, cy). Smooth gradients are the realistic case for perceptual
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// hashing and survive JPEG re-encoding well, so they make stable test fixtures.
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func radial(w, h int, cx, cy float64) image.Image {
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img := image.NewRGBA(image.Rect(0, 0, w, h))
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maxD := math.Hypot(float64(w), float64(h))
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for y := 0; y < h; y++ {
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for x := 0; x < w; x++ {
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d := math.Hypot(float64(x)-cx, float64(y)-cy)
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v := uint8(255 * (1 - d/maxD))
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img.Set(x, y, color.RGBA{v, v, v, 255})
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}
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}
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return img
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}
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func encodePNG(t *testing.T, img image.Image) []byte {
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t.Helper()
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var buf bytes.Buffer
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if err := png.Encode(&buf, img); err != nil {
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t.Fatalf("png encode: %v", err)
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}
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return buf.Bytes()
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}
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func encodeJPEG(t *testing.T, img image.Image, quality int) []byte {
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t.Helper()
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var buf bytes.Buffer
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if err := jpeg.Encode(&buf, img, &jpeg.Options{Quality: quality}); err != nil {
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t.Fatalf("jpeg encode: %v", err)
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}
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return buf.Bytes()
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}
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// The same image re-encoded as PNG (lossless) and JPEG (lossy) must hash to a
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// small Hamming distance — that is the whole point of a perceptual hash.
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func TestFromBytes_SameImageAcrossEncodings(t *testing.T) {
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img := radial(64, 64, 32, 32)
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pngHash, ok := FromBytes(encodePNG(t, img))
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if !ok {
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t.Fatal("FromBytes(PNG): ok=false")
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}
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jpgHash, ok := FromBytes(encodeJPEG(t, img, 90))
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if !ok {
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t.Fatal("FromBytes(JPEG): ok=false")
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}
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if d := Distance(pngHash, jpgHash); d > 8 {
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t.Errorf("same image, different encodings: distance = %d, want <= 8", d)
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}
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}
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// Visually different images must be far apart, and clearly farther than the same
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// image across encodings.
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func TestDistance_DifferentImagesAreFarApart(t *testing.T) {
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a := FromImage(radial(64, 64, 32, 32)) // centred
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b := FromImage(radial(64, 64, 0, 0)) // corner
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same, _ := FromBytes(encodeJPEG(t, radial(64, 64, 32, 32), 90))
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d := Distance(a, b)
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if d < 12 {
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t.Errorf("different images: distance = %d, want >= 12", d)
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}
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if d <= Distance(a, same) {
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t.Errorf("different images (%d) not farther than re-encoded same image (%d)", d, Distance(a, same))
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}
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}
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func TestDistance_SymmetricAndZeroForEqual(t *testing.T) {
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a := FromImage(radial(64, 64, 20, 40))
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b := FromImage(radial(64, 64, 40, 20))
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if Distance(a, a) != 0 {
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t.Errorf("Distance(a, a) = %d, want 0", Distance(a, a))
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}
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if Distance(a, b) != Distance(b, a) {
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t.Errorf("Distance not symmetric: %d vs %d", Distance(a, b), Distance(b, a))
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}
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}
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func TestFromBytes_RejectsNonImage(t *testing.T) {
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if _, ok := FromBytes([]byte("definitely not an image")); ok {
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t.Error("FromBytes on garbage: ok=true, want false")
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}
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}
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