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Android 4.0+ support
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ARMv7 and x86 based devices
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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.
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Build with Gradle. You can use Android studio to build
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Object detection - Region-based Convolutional Networks detection Selective Search on Android + FastRCNN
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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 = ".."; }
- Send pull request
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