This android application uses YOLOv2 model for object detection. It uses tensorflow mobile to run neural networks. I would like to use tensorflow lite later. Probably, it is the first open source implementation of the second version of YOLO for Tensorflow on Android device. The demo application detects 20 classes of Pascal VOC dataset. Please read this paper for more information about the YOLOv2 model: YOLO9000 Better, Faster, Stronger.
Train YOLO for your own dataset
Please find more information about retraining the model on my site: https://sites.google.com/view/tensorflow-example-java-api/complete-guide-to-train-yolo. I've also added several Google Colab interactive sample for the step-by-step tutorial, so the training process can be tried out on Google virtual machines.
Steps to compile and run the application:
Prerequirements:
Compile and run the project:
git clone https://github.com/szaza/android-yolo-v2.git;How it works?
If you would like a more accurate solution, create a server application. See my related projects here:
The current solution doesn't support the YoloV3 model and unfortunately, I do not have time to implement it, however I would be very happy if I could help to implement and I could review a PR with this feture. For this reason I've started a new branch here: https://github.com/szaza/tensorflow-java-examples-spring/tree/feature/add-yolov3-support; If you are interested in this feature and you would like to be a collabortor, please add a comment for this thread: https://github.com/szaza/tensorflow-java-examples-spring/issues/2;
Many-many thank for any support!