Tensorflow 2 YOLOv3-Tiny object detection implementation

In this tutorial, you will learn how to utilize YOLOv3-Tiny the same as we did for YOLOv3 for near real-time object detection. The YOLO object detector is often cited as being one of the fastest deep learning-based object detectors, achieving a higher FPS rate than computationally expensive two-stage detectors (ex. Faster R-CNN) and some single-stage detectors (ex. RetinaNet and some, but not all, variations of SSDs). However, even with all that speed, YOLOv3 is still not fast enough to run on some specific tasks or embedded devices such as the Raspberry Pi. To help make YOLOv3 even faster, Redmon et al. (the creators of YOLO), defined a variation of the YOLO architecture called YOLOv3-Tiny. ✅ Support My Channel Through Patreon: ✅ One-Time Contribution Through PayPal: