ImageAI

ImageAI is an open-source Python library that provides simple interfaces for developing computer vision applications using deep learning. It aims to enable developers to perform object detection, image classification, and video analysis with minimal code and without requiring deep expertise in neural networks.

Core features include an ObjectDetection module for identifying objects in still images and in video frames, and a CustomObjectDetection module to train detectors on user-provided datasets. It supports multiple detection models, such as RetinaNet and YOLO, and offers tools to export results and to run inferences on streams.

Technical details: ImageAI is built on Keras and TensorFlow and uses OpenCV for image and video input/output. The CustomObjectDetection workflow enables transfer learning from pre-trained models with annotated datasets in common formats. Pre-trained models can be downloaded from the project's repository. Inference can run on CPU or GPU, depending on hardware and drivers.

Licensing and availability: ImageAI is released under the MIT license and is hosted on GitHub, where users can report issues, contribute improvements, and access documentation and examples. The library has been adopted in education, hobby projects, and rapid prototyping of CV-based ideas.

Limitations: As a high-level library, ImageAI abstracts many details of model training and optimization, which may limit flexibility for advanced researchers. Compatibility depends on compatible versions of TensorFlow and Keras, and users should consult the official documentation for setup requirements.