Update dataset card for VizFlyt

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by nielsr HF Staff - opened
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  1. README.md +3 -44
README.md CHANGED
@@ -3,50 +3,9 @@ license: openrail
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  size_categories:
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  - 1M<n<10M
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  task_categories:
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- - image-classification
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- - text-to-image
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  ---
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- # ImageNet Generated using Stable Diffusion v1.5
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- The following repository mimics the size and class structure of the original ImageNet database. The classes can be found in the `classes.txt` file.
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- This dataset contains approximately 1300 images per class over 1000 classes for a total of 1.3 million images.
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- Here is an excerpt from `classes.txt`:
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-
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- ```plaintext
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- 0 tench, Tinca tinca
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- 1 goldfish, Carassius auratus
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- 2 great white shark, white shark, man-eater, man-eating shark, Carcharodon caharias
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- 3 tiger shark, Galeocerdo cuvieri
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- 4 hammerhead, hammerhead shark
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- 5 electric ray, crampfish, numbfish, torpedo
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- 6 stingray
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- 7 cock
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- 8 hen
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- 9 ostrich, Struthio camelus
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- ```
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-
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- Each category contains approximately 1300 images generated with the text prompt "A photo of {}" using seeds ranging from 1 to 1300. Stable diffusion v1.5 was used to generate all the images using the UniPCMultistepScheduler with 20 inference steps and the safety checker turned off. Images are 512x512 in resolution.
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-
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- Below are some randomly sampled images from the dataset:
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-
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-
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- | ![Sample Image 1](seed_29.jpg) | ![Sample Image 2](seed_0.jpg) |
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- |:---:|:---:|
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- | Class 115, Seed 29 | Class 220, Seed 0 |
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-
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- | ![Sample Image 3](seed_509.jpg) | ![Sample Image 4](seed_250.jpg) |
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- |:---:|:---:|
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- | Class 714, Seed 509 | Class 894, Seed 250 |
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-
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-
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- ```plaintext
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- @misc{kim2023generative,
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- title={Generative Artificial Intelligence Consensus in a Trustless Network},
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- author={Edward Kim and Isamu Isozaki and Naomi Sirkin and Michael Robson},
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- year={2023},
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- eprint={2307.01898},
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- archivePrefix={arXiv},
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- primaryClass={cs.DC}
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- }
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- ```
 
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  size_categories:
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  - 1M<n<10M
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  task_categories:
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+ - robotics
 
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  ---
 
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+ This repository contains the data, code and models for the VizFlyt framework, as described in the paper [VizFlyt: Perception-centric Pedagogical Framework For Autonomous Aerial Robots](https://huggingface.co/papers/2503.22876).
 
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+ More information, code, datasets, hardware guides and demo videos are available at https://pear.wpi.edu/research/vizflyt.html