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EXIF Metadata Stripped (JPEG)

The same photo with all EXIF metadata removed: the stripped twin of the EXIF-present JPEG, for verifying that a metadata-scrubbing tool actually removed everything.

Preview of EXIF Metadata Stripped (JPEG)

Specifications

Width
512
Height
512
Exif
none (stripped)
Subject
fruit still life
Alt Text
The same photo with all EXIF metadata removed: the stripped twin of the EXIF-present JPEG, for verifying that a metadata-scrubbing tool actually removed everything
Alt Text Source
description

Testing contract

Expected to pass
Scenario
Exercise EXIF Metadata Stripped (JPEG) in its color and metadata workflow. The same photo with all EXIF metadata removed: the stripped twin of the EXIF-present JPEG, for verifying that a metadata-scrubbing tool actually removed everything.
Expected result
Decoded geometry is 512×512 pixels in RGB mode; frame count is 1. Declared feature checks: exif=none (stripped); subject=fruit still life. The declared comparison counterpart is img-pipe-exif-present; preserve the stated difference instead of expecting the container bytes to match.

What is a .jpg file?

JPG is the common extension for JPEG, a lossy raster format that uses discrete cosine transform compression tuned for photographic images. It is 8-bit truecolor with no alpha channel, and quality is traded against file size via a compression factor. It is ubiquitous for photos on the web and from cameras.

How to use this file

Use an example JPG to test decoders, EXIF/metadata parsers, re-encoding quality, and orientation handling, or to confirm converters and image pipelines process baseline and progressive scans correctly.

How to use this file for testing

“EXIF Metadata Stripped (JPEG)” is a deterministic Testaroo fixture for EXIF & orientation testing, Metadata testing. Images with embedded EXIF orientation flags for testing whether your tool respects rotation metadata.

Documented properties for this file: 512×512. Compare results against paired or grouped companions on this page when present (clean↔damaged, searchable↔scanned, or format twins) so scores stay reproducible across runs.

Download the file once, keep the path stable in CI or local scripts, and treat the spec table as the contract: dimensions, seeds, field lists, and roles are intentional. Corrupt or invalid samples are labelled as such, expect parsers to fail loudly rather than silently accept them.

For image AI or enhancement tools, run the model or filter on this file and diff against the clean or ground-truth companion in the same group when available. Keep seeds and documented damage parameters in your evaluation notes so regressions are attributable.

Code examples

<img src="fruit-exif-stripped.jpg" alt="Example image" width="640" loading="lazy">

Generated by generation/images_pipeline.py. Free for any use, no attribution required, license.