A memory efficient Android image processor library providing cropping above Face Detection (Face Centering) for Fresco.
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README.md

Fresco face detection processor

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An Android image processor library providing cropping above Face Detection (Face Centering) for Fresco

Are you using Picasso? PicassoFaceDetectionTransformation.

Are you using Glide? GlideFaceDetectionTransformation.

Results

Original Image

original image 1

Results after cropping

resulting image 1

Original Image

original image 2

Results after cropping

resulting image 2

Original Image

original image 3

Results after cropping

resulting image 3

Original Image

original image 4

Results after cropping

resulting image 4

You can read more on my Medium article.

How to use it?

STEP 1:

Grab via Gradle

repositories {
    jcenter()
}
dependencies {
    compile 'com.github.aryarohit07:fresco-facedetection-processor:0.1.1'
}

Or via Maven

<dependency>
  <groupId>com.github.aryarohit07</groupId>
  <artifactId>fresco-facedetection-processor</artifactId>
  <version>0.1.1</version>
</dependency>

STEP 2:

Initialize the detector (May be in onCreate() method)

FrescoFaceDetector.initialize(context);

STEP 3:

Set fresco processor

ImageRequest request = ImageRequestBuilder
  .newBuilderWithSource(uri)
  .setPostprocessor(new FaceCenterCrop(900, 900))
  .build();

PipelineDraweeController controller = (PipelineDraweeController)
  Fresco.newDraweeControllerBuilder()
    .setImageRequest(request)
    .setOldController(image2.getController())
    // other setters as you need
    .build();
mSimpleDraweeView.setController(controller);

STEP 4:

The face detector uses native resources in order to do detection. For this reason, it is necessary to release the detector instance once it is no longer needed (May be in onDestory() method)

FrescoFaceDetector.releaseDetector();

Note: If no face is detected, it will fallback to CENTER CROP.

Library dependencies:

com.google.android.gms:play-services-vision:9.4.0
com.facebook.fresco:fresco:0.12.0

If you liked it, please Star it.

TODO

  • Making it generic for any point.

Performance: Time taken to detect faces in the original image.

width height time taken(ms)
640 360 60-150
900 600 100-200
1280 720 250-350
1920 1080 350-400
2048 1536 500-550

License

Copyright 2016 Rohit Arya

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

   http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.