tensornets 0.4.6

Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.

OpenMMLab Detection Toolbox and Benchmark

StarDist is a Python package designed for object detection with star-convex shapes, particularly useful in microscopy. It provides implementations for both 2D and 3D images and uses a model trained to predict distances to the object boundary along fixed rays and object probabilities. These predictions produce an overcomplete set of candidate polygons for a given image, with the final result obtained via non-maximum suppression.

StarDist is compatible with Python 3.6 to 3.10, requires TensorFlow, and provides pre-trained models for 2D images and example workflows via Jupyter notebooks, making it a versatile tool for cell detection and segmentation in microscopy.

The Deezer source separation library with pretrained models based on tensorflow.

PyTorch Image Models

Neural Networks Compression Framework

Flower: A Friendly Federated Learning Framework

Deep Lake is a Database for AI powered by a unique storage format optimized for deep-learning and Large Language Model (LLM) based applications. It simplifies the deployment of enterprise-grade LLM-based products by offering storage for all data types (embeddings, audio, text, videos, images, pdfs, annotations, etc.), querying and vector search, data streaming while training models at scale, data versioning and lineage for all workloads, and integrations with popular tools such as LangChain, LlamaIndex, Weights & Biases, and many more.

Distributed Deep learning with Apache Spark with Keras.