pasm-yolov3-Android

YOLOv3 implementation with Tensorflow on Android

This project contains an example of YoloV3 implementation on Android, the YoloV3 model was implemented through the library org.tensorflow:tensorflow-android.

Below is a list of steps taken to convert the YoloV3 model from darkflow to tensorflow for Android (command launched on Ubuntu inside Anaconda):

• clone DW2TF repository from here https://github.com/jinyu121/DW2TF to local folder
• ex: /home/user/projects/
• Download (or train) YoloV3 model and weights in darknet format (.cfg and .weights)
• Launch DW2TF conversion as mentioned on the github page of DW2TF: https://github.com/jinyu121/DW2TF:
• python3 main.py \ --cfg 'data/yolov3-tiny.cfg' \ --weights 'data/yolov3-tiny.weights' \ --output 'data/' \ --prefix 'yolov3-tiny/' \ --gpu 0
• launch freeze_graph to have a single bp graph file: freeze_graph \ --input_graph yolov3-tiny.pb \ --input_checkpoint yolov3-tiny.ckpt \ --input_binary=true \ --output_graph=ultimate_yolov3.bp \ --output_node_names=yolov3-tiny/convolutional10/BiasAdd

NOTE: For older version of Yolo you can use darkflow tool https://github.com/thtrieu/darkflow, here an example after clone the repository:

./flow --model ../data/yolov2-tiny.cfg --load ../data/yolov2-tiny.weights --savepb

For more detail about Yolo look at offical page https://pjreddie.com/darknet/yolo/