ImageAI is an easy to use Computer Vision Python library that empowers developers to easily integrate state-of-the-art Artificial
Intelligence features into their new and existing applications and systems. It is used by thousands of developers, students, researchers,
tutors and experts in corporate organizations around the world. You will find below features supported, links to official documentations
as well as articles on ImageAI
ImageAI in Numbers
1900+ GitHub Stars
230,000+ Article Views
10 months Old
ImageAI provides API to recognize 1000 different objects in a picture using pre-trained models that were trained
on the ImageNet-1000 dataset. The model implementations provided are SqueezeNet, ResNet, InceptionV3 and DenseNet.
ImageAI provides API to detect, locate and identify 80 most common objects in everyday life in a picture using pre-trained models
that were trained on the COCO Dataset. The model implementations provided include RetinaNet, YOLOv3 and TinyYOLOv3.
ImageAI provides an extended API to detect, locate and identify 80 objects in videos and retrieve full analytical data on every frame,
second and minute. This feature is supported for video files, device camera and IP camera live feed.