Articles

Using YOLOv5 in PyTorch

YOLO, an acronym for ‘You only look once,’ is an open-source software tool utilized for its efficient capability of detecting objects in a given image in real time. The YOLO algorithm uses convolutional neural network (CNN) models to detect objects in an image. 

The algorithm requires only one forward propagation through a given neural network to detect all objects in the image. This gives the YOLO algorithm an edge in speed over others, making it one of the most well-known detection algorithms to date.

Source de l’article sur DZONE

In preparation for my talk at the Philadelphia Open Source Conference, Apache Deep Learning 201, I wanted to have some good images for running various Apache MXNet Deep Learning Algorithms for Computer Vision. 

Using Apache open source tools – Apache NiFi 1.8 and Apache MXNet 1.3 with GluonCV I can easily ingest live traffic camera images and run Object Detection, Semantic Segmentation and Instance Segmentation.


Source de l’article sur DZONE (AI)