Firebase object detection

android-yolo is the first implementation of YOLO for TensorFlow on an Android device. It is compatible with Android Studio and usable out of the box .

MobilenetSSD is an object detection model that computes the bounding box and category of an object from an input image . This Single Shot Detector (SSD) object detection model uses Mobilenet as backbone and can achieve fast object detection optimized for mobile devices.

MobilenetSSD is an object detection model that computes the bounding box and category of an object from an input image . This Single Shot Detector (SSD) object detection model uses Mobilenet as backbone and can achieve fast object detection optimized for mobile devices.

It forms the basis of many other downstream computer vision tasks, for example, instance segmentation, image captioning, object tracking, and more. Specific object detection applications include pedestrian detection, people counting, face detection, text detection, pose detection, or number-plate recognition.

It forms the basis of many other downstream computer vision tasks, for example, instance segmentation, image captioning, object tracking, and more. Specific object detection applications include pedestrian detection, people counting, face detection, text detection, pose detection, or number-plate recognition.

This model detects objects defined in the COCO dataset, which is a large-scale object detection, segmentation, and captioning dataset . You can find more information here. The model is capable of detecting 80 classes of objects. (SSD stands for Single Shot MultiBox Detection).