This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems.
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This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems.
EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything
3D U-Net model for volumetric semantic segmentation written in pytorch
Objectron is a dataset of short, object-centric video clips. In addition, the videos also contain AR session metadata including camera poses, sparse point-clouds and planes. In each video, the camera moves around and above the object and captures it from different views. Each object is annotated with a 3D bounding box. The 3D bounding box describes the object’s position, orientation, and dimensions. The dataset contains about 15K annotated video clips and 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes
I took Andrew Ng's Machine Learning course on Coursera and did the homework assigments... but, on my own in python because I love jupyter notebooks!
WFGY is heading toward WFGY 5.0 Polaris Protocol, a major open-source release for AI reasoning, RAG, agents, and real-world workflows. Includes Problem Map, Global Debug Card, WFGY 4.0, and the CFV Easter Egg.
TorchXRayVision: A library of chest X-ray datasets and models. Classifiers, segmentation, and autoencoders.
Segment Anything for Microscopy
Usiigaci: stain-free cell tracking in phase contrast microscopy enabled by supervised machine learning
InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
General Modeling Network Specification
A database of paths that represent the mechanism of action from a drug to a disease in an indication.
SplineDist: Automated Cell Segmentation with Spline Curves
🗺 General purpose U-Network implemented in Keras for image segmentation