This repo is a fork of chuanqi305's rscnn, a CNN framework based on RenderScript.

The purpose of this repo is to demonstrate an implementation for deploying prebuilt detection models from Caffe (using MobileNetv1 + SSD) onto an Android device.

1. Android Studio w/ API 28

2. Caffe (w/ssd) : https://github.com/chuanqi305/ssd

3. Anaconda (Recomended)

1. Download MobileNet-SSD model.

git clone https://github.com/chuanqi305/MobileNet-SSD

You'll want to download the pretrained MobileNetSSD_deploy.caffemodel and move it to MobileNet-SSD folder.

2. Use script/convert_caffe_model.py to convert the model to new format, do not forget to change the caffe root path in the converting script.

python script/convert_caffe_model.py --model MobileNet-SSD/deploy.prototxt --weights MobileNet-SSD/MobileNetSSD_deploy.caffemodel --savedir mobilenet-ssd

3. Push the converted model files to src/main/assets folder of your project.

cp -ar mobilenet-ssd demo/src/main/assets/

4. Run this demo, and you can select a photo to see the object detection result.

See Wiki for more documentation details of additional errors you might run into and how to correct them.