croppy 0.0.1

Image cropper that Flutter deserves

croppy

An image cropper that Flutter deserves.

Big difference of this package from other popular ones (such as image_cropper) is that croppy runs completely in Flutter, so there's no need to launch a separate activity/view when you want to crop an image. Another benefit is that croppy can be completely customized to fit any of your image cropping needs.

Features

• iOS Photos app-like image cropper
• Supports any linear transformations on the image: scaling, rotating, skewing, flipping, etc
• Completely customizable (will create documentation with later releases)

In progress:

• Material image cropper (something similar to Google Photos)
• Image editing module (?) (brightness, contrast, etc)
• Fixed aspect ratios
• Custom cropping shapes
• Localization
• Kickass animations

Getting started

Install croppy from pub:

dependencies:
  croppy: <latest_version>

Enjoy using it :)

Usage

Currently croppy supports an iOS-like image cropper:

final result = await showCupertinoImageCropper(
  context,
  imageProvider: const NetworkImage('MY_IMAGE_URL'), // Or any other image provider
  initialData: CroppableImageData.initial(imageSize: const Size(1080, 1080)),
);

The image size has to be known before launching the cropper. One way to obtain it is to use obtainImage:

final image = await obtainImage(myProvider);
final size = (image.width, image.height);

In the future this will be a bit more streamlined. Still thinking of a clean way of doing this.

The return value of showCupertinoImageCropper is CropImageResult, which contains the image data encoded with the image package. To convert it to dart:ui's Image, you can use await result.asUiImage. Check out the image package to convert the image to any of the supported formats (png, jpg, etc).

For a complete runnable example, see ./example.

Additional information

This package is still WIP, so expect some major updates along the way. Feel free to report bugs/issues on GitHub.

If you have questions, you can contact me directly at [e-mail].

Credits:

• https://github.com/daniyarzt for the FitAabbInQuadSolver class