This module analyzes JPEG/JPEG 2000/PNG/GIF/TIFF/SVG/Netpbm/WebP/BMP/AVIF/HEIC/HEIF image headers and returns image size, DPI, and related metadata.

import imagesize width, height = imagesize.get("test.png") print(width, height) xdpi, ydpi = imagesize.getDPI("test.png") print(xdpi, ydpi) info = imagesize.get_info("test.png") print(info.width, info.height, info.rotation, info.xdpi, info.ydpi, info.colors, info.channels)

This module is a pure Python module. You can use file like object like file or something like io.BytesIO.

Supported Python versions: 3.10-3.14

pip install imagesize

For local development setup:

python -m venv .venv source .venv/bin/activate pip install -e .

Version 2.0 includes the following updates:

• Added/expanded support for BMP.
• Added support for AVIF.
• Added support for HEIC/HEIF.
• imagesize.get_info() now returns richer metadata including color depth, channel count, and rotation information.
• Improved EXIF orientation handling so JPEG, TIFF, AVIF, and HEIC/HEIF return sizes that correctly reflect EXIF rotation metadata.
• Added type hints for the public API and related input/output types.

Backward incompatible behavior in 2.0:

• imagesize.get() now returns (-1, -1) when parsing fails.
• imagesize.getDPI() now returns (-1, -1) when parsing fails.

If your existing code relied on exceptions during parse failures, update it to explicitly check return values.

• imagesize.get(filepath: FileInput, *, exif_rotation: bool = True) -> tuple[int, int]

  Returns image size as (width, height). By default, orientation metadata is applied for rotated JPEG/TIFF images; pass exif_rotation=False to get the stored size as-is. On parsing errors it returns (-1, -1).

• imagesize.getDPI(filepath: FileInput) -> tuple[int, int]

  Returns image DPI as (xdpi, ydpi). On parsing errors it returns (-1, -1).

• imagesize.get_info(filepath: FileInput, *, size: bool = True, dpi: bool = True, colors: bool = True, exif_rotation: bool = True, channels: bool = True) -> ImageInfo

  Returns an ImageInfo named tuple with width, height, rotation, xdpi, ydpi, colors and channels fields. rotation contains orientation metadata (e.g. EXIF Orientation tag, or -1 when unavailable).

It only parses headers, and ignores pixel data. So it is much faster than Pillow.

I tested on MacBookPro (2014/Core i7) with 125kB PNG files.

Run test with the following command:

python -m unittest

MIT License

• test/images/test.heic: https://nokiatech.github.io/heif/examples.html
• test/images/test.avif: https://libre-software.net/image/avif-test/

I referred to the following code:

• http://markasread.net/post/17551554979/get-image-size-info-using-pure-python-code
• https://stackoverflow.com/questions/8032642/how-to-obtain-image-size-using-standard-python-class-without-using-external-lib

I use sample image from here:

• https://www.nightprogrammer.org/development/multipage-tiff-example-download-test-image-file/

Thank you for feedback:

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