• Android 4.0+ support

• ARMv7 and x86 based devices

• Get the Caffe model and push it to Phone SDCard. For object detection, network(*.prototxt) should use ROILayer, you can refer to Fast-RCNN. For scene recognition(object recognition), it can use any caffe network and weight with memory input layer.

• Build with Gradle. You can use Android studio to build

• Object detection - Region-based Convolutional Networks detection Selective Search on Android + FastRCNN

• Scene recognition - Convolutional neural networks trained on Places Input a picture of a place or scene and predicts it.

• Download and push the neccessary file to your phone. There should be model and weight in /sdcard/fastrcnn and /sdcard/vision_scene.

$ ./setup.sh

• Build and run the application using gradlew or you can open AndroidStudio to import this project

$ ./gradlew assembleDebug

$ adb install -r ./app/build/outputs/apk

Besides, you can change deep learning's model, weight, etc in VisionClassifierCreator.java

public class VisionClassifierCreator {
    private final static String SCENE_MODEL_PATH = "..";
    private final static String SCENE_WIEGHTS_PATH = "..";
    private final static String SCENE_MEAN_FILE = "..";
    private final static String SCENE_SYNSET_FILE = "..";

    private final static String DETECT_MODEL_PATH = "..";
    private final static String DETECT_WIEGHTS_PATH = "..";
    private final static String DETECT_MEAN_FILE = "..";
    private final static String DETECT_SYNSET_FILE = "..";
 }

Speed up object detection

    Copyright (C) 2015-2016 TzuTaLin

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,
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See the License for the specific language governing permissions and
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