.
Both
and
are commonly used in computer vision projects. Below, we compare and contrast
and
This architecture provides good realtime results on limited compute. It's designed to run in realtime (30 frames per second) even on mobile devices.
How to AugmentHow to LabelHow to Plot PredictionsHow to Filter PredictionsHow to Create a Confusion MatrixYOLOv4 has emerged as the best real time object detection model. YOLOv4 carries forward many of the research contributions of the YOLO family of models along with new modeling and data augmentation techniques. This implementation is in PyTorch.
How to AugmentHow to LabelHow to Plot PredictionsHow to Filter PredictionsHow to Create a Confusion Matrix
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