Omkar2118/datasets huggingface dataset:
PAXRay
Full name: PAXRay: A Projected dataset for the segmentation of Anatomical structures in X-Ray data

Projection of RibFrac CT dataset to a 2D plane to imitate X-Ray data for a total of 880 images with multi-label segmentation masks. 
The dataset contains fine-grained 92 individual labels of anatomical structures, which, when including super-classes, lead to a total of 166 labels in both lateral
and frontal view.
Avalon

**Avalon** is a benchmark for generalization in Reinforcement Learning (RL). The benchmark consists of a set of tasks in which embodied agents in highly diverse procedural 3D worlds must survive by navigating terrain, hunting or gathering food, and avoiding hazards. Avalon is unique among existing RL benchmarks in that the reward function, world dynamics, and action space are the same for every task, with tasks differentiated solely by altering the environment; its 20 tasks, ranging in complexity from eat and throw to hunt and navigate, each create worlds in which the agent must perform specific skills in order to survive. This benchmark setup enables investigations of generalization within tasks, between tasks, and to compositional tasks that require combining skills learned from previous tasks.

Source: [Avalon: A Benchmark for RL Generalization Using
Procedurally Generated Worlds](https://arxiv.org/pdf/2210.13417v1.pdf)

Image Source: [https://arxiv.org/pdf/2210.13417v1.pdf](https://arxiv.org/pdf/2210.13417v1.pdf)

Introducing paper: Avalon: A Benchmark for RL Generalization Using Procedurally Generated Worlds