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Welcome to the OpenVino-For-SmartCity wiki!

Documentation links

Openvino inferrence pre-loaded examples:

https://github.com/intel-iot-devkit/inference-tutorials-generic/tree/openvino_toolkit_r4_0

Inference engine samples - (Yolo v3 object detection demo):

https://software.intel.com/en-us/articles/OpenVINO-InferEngine

Model Optimizer to convert Tensorflow models (Yolo v3):

https://software.intel.com/en-us/articles/OpenVINO-Using-TensorFlow

Tensorflow Yolo v3 repo:

https://github.com/mystic123/tensorflow-yolo-v3

Yolo v3 docs:

https://pjreddie.com/darknet/yolo/

Near misses project

In order to successfully detect near misses happening on a intersection, we have splitted the project in 5 stages.

1. Input feed processing.

2. Areas of Interest selection.

3. Object Detection.

4. Object Tracking.

5. Collision Detection.

6. Near Misses.

7. Business logic.

8. Output.

9. QA Approach.