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--- |
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license: mit |
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pretty_name: "Classic Cars" |
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tags: ["image", "computer-vision", "cars", "classic-cars", "high-resolution", "europe", "us"] |
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task_categories: ["image-classification"] |
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language: ["en"] |
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configs: |
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- config_name: train |
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data_files: "train/**/*.arrow" |
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features: |
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- name: image |
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dtype: image |
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- name: unique_id |
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dtype: string |
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- name: width |
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dtype: int32 |
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- name: height |
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dtype: int32 |
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- name: original_file_format |
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dtype: string |
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- name: image_mode_on_disk |
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dtype: string |
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- config_name: preview |
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data_files: "preview/**/*.arrow" |
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features: |
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- name: image |
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dtype: image |
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- name: unique_id |
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dtype: string |
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- name: width |
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dtype: int32 |
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- name: height |
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dtype: int32 |
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- name: image_mode_on_disk |
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dtype: string |
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- name: original_file_format |
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dtype: string |
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--- |
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# Classic Cars |
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High resolution image subset from the Aesthetic-Train-V2 dataset, contains both classic and older generation cars mostly from the US and Europe. |
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## Dataset Details |
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* **Curator:** Roscosmos |
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* **Version:** 1.0.0 |
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* **Total Images:** 660 |
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* **Average Image Size (on disk):** ~5.7 MB compressed |
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* **Primary Content:** Classic cars. |
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* **Standardization:** All images are standardized to RGB mode and saved at 95% quality for consistency. |
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## Dataset Creation & Provenance |
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### 1. Original Master Dataset |
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This dataset is a subset derived from: |
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**`zhang0jhon/Aesthetic-Train-V2`** |
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* **Link:** https://huggingface.co/datasets/zhang0jhon/Aesthetic-Train-V2 |
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* **Providence:** Large-scale, high-resolution image dataset, refer to its original dataset card for full details. |
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* **Original License:** MIT |
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### 2. Iterative Curation Methodology |
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CLIP retrieval / manual curation. |
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## Dataset Structure & Content |
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This dataset is organized into two primary splits: |
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* **`train` split:** Contains the full, high-resolution image data and associated metadata. This is the recommended split for model training and full data analysis. |
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* **`preview` split:** Contains a small, random subset of images from the `train` split. The images in this split are downsampled and re-compressed to be **viewer-compatible** on the Hugging Face Hub. This split is intended for quick browsing and previewing directly in your web browser. |
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Each example (row) in both splits contains the following fields: |
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* `image`: The actual image data. In the `train` split, this is full-resolution. In the `preview` split, this is a viewer-compatible version. |
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* `unique_id`: A unique identifier assigned to each image. |
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* `width`: The width of the image in pixels (from the full-resolution image). |
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* `height`: The height of the image in pixels (from the full-resolution image). |
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## Citation |
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```bibtex |
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@inproceedings{zhang2025diffusion4k, |
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title={Diffusion-4K: Ultra-High-Resolution Image Synthesis with Latent Diffusion Models}, |
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author={Zhang, Jinjin and Huang, Qiuyu and Liu, Junjie and Guo, Xiefan and Huang, Di}, |
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year={2025}, |
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booktitle={IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, |
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} |
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@misc{zhang2025ultrahighresolutionimagesynthesis, |
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title={Ultra-High-Resolution Image Synthesis: Data, Method and Evaluation}, |
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author={Zhang, Jinjin and Huang, Qiuyu and Liu, Junjie and Guo, Xiefan and Huang, Di}, |
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year={2025}, |
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note={arXiv:2506.01331}, |
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} |
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``` |
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## Disclaimer and Bias Considerations |
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Please consider any inherent biases from the original dataset and those potentially introduced by the automated filtering (e.g., CLIP's biases) and manual curation process. |
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## Contact |
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N/A |
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