imagemeta

imagemeta is a high-performance Go library for extracting EXIF and XMP metadata from images and camera RAW formats.

It is built for:

ExifTool-aligned decoding behavior
low-allocation parsing on hot paths
broad support for modern and legacy camera formats
structured MakerNote decoding (Canon, Nikon, Sony, Panasonic, Apple)

Features

Decode EXIF from JPEG, TIFF, CR2, CR3, DNG, NEF, ARW, RW2, HEIC/HEIF/AVIF, PNG, and CRW
Parse XMP sidecars and embedded XMP blocks
Read Canon/Nikon/Sony/Panasonic/Apple MakerNotes
Extract embedded CR3 previews
Fast image type detection
Allocation-conscious perceptual image hashing (imagehash)

Install

bash
go get github.com/evanoberholster/imagemeta

Supported Formats

JPEG: .jpg, .jpeg
TIFF + TIFF-based RAW: .tif, .tiff, .cr2, .dng, .nef, .arw, .rw2
ISO-BMFF family: .cr3, .heic, .heif, .avif
PNG (EXIF-in-TIFF payload)
CIFF/CRW: .crw

Quick Start

go
package main

import (
	"fmt"
	"os"

	"github.com/evanoberholster/imagemeta"
)

func main() {
	f, err := os.Open("image.jpg")
	if err != nil {
		panic(err)
	}
	defer f.Close()

	ex, err := imagemeta.Decode(f)
	if err != nil {
		panic(err)
	}

	fmt.Println("type:", ex.ImageType)
	fmt.Println("make:", ex.Make)
	fmt.Println("model:", ex.Model)
	fmt.Println("datetime:", ex.DateTimeOriginal)
}

Decode API

Top-level decode entry points:

Decode(io.ReadSeeker)
DecodeJPEG(io.ReadSeeker)
DecodeTiff(io.ReadSeeker)
DecodeCR3(io.ReadSeeker)
DecodeCRW(io.ReadSeeker)
DecodeHeif(io.ReadSeeker)
DecodePng(io.ReadSeeker)
PreviewCR3(io.ReadSeeker)

XMP Parsing

Parse a sidecar .xmp file:

go
x, err := xmp.ParseXmp(file)

Parse embedded XMP from an image:

go
x, err := xmp.Parse(file)

Package: github.com/evanoberholster/imagemeta/meta/xmp

Image Type Detection

Use imagetype for quick format detection before decode:

go
t, err := imagetype.Scan(r)

Package: github.com/evanoberholster/imagemeta/imagetype

Perceptual Hashing

imagehash provides 64-bit and 256-bit perceptual hashing with low-allocation paths.

Package: github.com/evanoberholster/imagemeta/imagehash

Performance Notes

Designed for low allocation and high throughput
Uses pooled readers and fixed-size parsing structures on hot paths
Suitable for large-batch metadata extraction pipelines

Benchmarks

General benchmarks: bench_test.go

Benchmark	ns/op	B/op	allocs/op
Canon/CR2	6646	2440	20
Canon/CR3	8015	3723	22
Canon/JPG	2058	176	9
Nikon/JPG	1747	104	7
Nikon/NEF	10306	736	19
Sony/ARW	6584	1512	12

Note: benchmark results vary by CPU, Go version, and sample files.

TODO

Expand ExifTool parity coverage across MakerNote fields (Nikon, Sony, Panasonic, Apple, DJI)
Resolve known reverse-offset parsing edge case in MakerNote decoding
Improve malformed metadata resilience with more targeted fuzz and corpus tests
Add more specific benchmarks to compare edge cases
Document compatibility matrix by camera model/format