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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/
In order to successfully detect near misses happening on a intersection, we have splitted the project in 5 stages.
Input feed processing.
Areas of Interest selection.
Object Detection.
Object Tracking.
Collision Detection.
Near Misses.
Business logic.
Output.
QA Approach.