Eran Feit Blog posts

Object detection heatmap is a simple idea with a lot of power behind it.Instead of just drawing bounding boxes around objects, you aggregate all those detections into a colorful map that shows where activity is concentrated.Each new detection slightly “warms up” the corresponding region of the frame, so after processing many frames you get a

Yolov8 dog detection is all about teaching a modern deep learning model to find dogs in images the same way your eyes do: quickly, accurately, and in real time.Instead of just answering “is there a dog here?”, the model learns to say “there’s a dog here, here, and here” and wrap each one with a

Automatic image annotation is all about teaching machines to tag images for us.Instead of a human drawing every bounding box and typing every label, models learn to recognize patterns and automatically assign classes like horse, car, or person to each object in a picture or video frame.This drastically reduces the manual work needed to build

When you train yolo nas on custom dataset, you’re taking an object detection model that was designed as a strong, general-purpose detector and adapting it to your specific problem. Instead of relying only on COCO-style everyday scenes, you can teach YOLO-NAS to recognize underwater creatures like fish, jellyfish, sharks, or penguins in noisy, low-contrast aquarium