Error code: ConfigNamesError Exception: FileNotFoundError Message: Couldn't find a dataset script at /src/services/worker/ek826/imagenet-gen-sd1.5/imagenet-gen-sd1.5.py or any data file in the same directory. Couldn't find 'ek826/imagenet-gen-sd1.5' on the Hugging Face Hub either: FileNotFoundError: No (supported) data files or dataset script found in ek826/imagenet-gen-sd1.5. Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 55, in compute_config_names_response for config in sorted(get_dataset_config_names(path=dataset, token=hf_token)) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 351, in get_dataset_config_names dataset_module = dataset_module_factory( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1508, in dataset_module_factory raise FileNotFoundError( FileNotFoundError: Couldn't find a dataset script at /src/services/worker/ek826/imagenet-gen-sd1.5/imagenet-gen-sd1.5.py or any data file in the same directory. Couldn't find 'ek826/imagenet-gen-sd1.5' on the Hugging Face Hub either: FileNotFoundError: No (supported) data files or dataset script found in ek826/imagenet-gen-sd1.5.

ImageNet Generated using Stable Diffusion v1.5

The following repository mimics the size and class structure of the original ImageNet database. The classes can be found in the classes.txt file. This dataset contains approximately 1300 images per class over 1000 classes for a total of 1.3 million images.

Here is an excerpt from classes.txt:

0 tench, Tinca tinca
1 goldfish, Carassius auratus
2 great white shark, white shark, man-eater, man-eating shark, Carcharodon caharias
3 tiger shark, Galeocerdo cuvieri
4 hammerhead, hammerhead shark
5 electric ray, crampfish, numbfish, torpedo
6 stingray
7 cock
8 hen
9 ostrich, Struthio camelus

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.

Below are some randomly sampled images from the dataset:


Class 115, Seed 29	Class 220, Seed 0


Class 714, Seed 509	Class 894, Seed 250

@misc{kim2023generative,
      title={Generative Artificial Intelligence Consensus in a Trustless Network}, 
      author={Edward Kim and Isamu Isozaki and Naomi Sirkin and Michael Robson},
      year={2023},
      eprint={2307.01898},
      archivePrefix={arXiv},
      primaryClass={cs.DC}
}