The TinyYolo network can be used for object recognition and classification. This model was trained with the Pasval VOC data set and can detect up to 20 classes. See https://pjreddie.com/darknet/yolov1/ for more information on this network.
The provided Makefile does the following
The provided Makefile does the following
- Downloads the Caffe prototxt file
- Downloads the .caffemodel weights file.
- Compiles the IR (intermediate representation) files using the Model Optimizer.
- Runs the provided run.py program that does a single inference on a provided image as an example on how to use the network using the Inference Engine Python API.
make run
Provided Makefile describes various targets that help with the above mentioned tasks.
Runs a sample application with the network.
Shows makefile possible targets and brief descriptions.
Makes the follow items: deps, data, compile_model.
Uses the network description and the trained weights files to generate an IR (intermediate representation) format file. This file is later loaded on the Neural Compute Stick where the inferences on the network can be executed.
Checks required packages that aren't installed as part of the OpenVINO installation.
Uninstalls requirements that were installed by the sample program.
Removes all the temporary and target files that are created by the Makefile.