xe1gyq/pynq-ncs-yolo

YOLO object detector for Movidius Neural Compute Stick (NCS)

YOLO for PYNQ-Z1 and Intel/Movidius Neural Compute Stick (NCS)

This project is derived from yoloNCS and is intended to be used on the PYNQ-Z1 board.

Using this repo on your PYNQ-Z1

To use this code on your PYNQ-Z1, just follow these steps:

1. Install NCSDK in API-mode on your PYNQ-Z1 as explained here: Setting up the PYNQ-Z1 for the Intel Movidius NCS

2. Clone this repo onto your PYNQ-Z1 in this directory: /home/xilinx/jupyter_notebooks

3. Boot the PYNQ-Z1, open Jupyter in a web browser (http://pynq:9090) and open one of the notebooks

News

• Camera App is working.
• YOLOv1 Tiny is working.

Protobuf Model files

./prototxt/

Download Pretrained Caffe Models to ./weights/

• YOLO_tiny: https://drive.google.com/file/d/0Bzy9LxvTYIgKNFEzOEdaZ3U0Nms/view?usp=sharing

Compilation

• Compile .prototxt and corresponding .caffemodel (with the same name) to get NCS graph file. For example: "mvNCCompile prototxt/yolo_tiny_deploy.prototxt -w weights/yolo_tiny_deploy.caffemodel -s 12"
• The compiled binary file "graph" has to be in main folder after this step.

Single Image Script

• Run "yolo_example.py" to process a single image. For example: "python3 py_examples/yolo_example.py images/dog.jpg" to get detections as below.

Camera Input Script

• Run "object_detection_app.py" to process a videos from your camera. For example: "python3 py_examples/object_detection_app.py" to get camera detections as below.
• Modify script arguments if needed.
• Press "q" to exit app.