Datasets:
Tasks:
Image Segmentation
Modalities:
Image
Formats:
imagefolder
Sub-tasks:
semantic-segmentation
Size:
1K - 10K
| task_categories: | |
| - image-segmentation | |
| task_ids: | |
| - semantic-segmentation | |
| pretty_name: DLCV Final Dataset | |
| size_categories: | |
| - medium | |
| # DLCV Final Dataset | |
| This dataset is used for the **Deep Learning for Computer Vision (DLCV) final project**. | |
| It contains ground-truth layers organized per sample and is designed for training and evaluating computer vision models. | |
| --- | |
| ## π Dataset Structure | |
| The dataset is organized as follows: | |
| dlcv_final/ | |
| βββ gt_layers/ | |
| β βββ sample_0000/ | |
| β β βββ layer_0.png | |
| β β βββ layer_1.png | |
| β β βββ ... | |
| β βββ sample_0001/ | |
| β βββ sample_0002/ | |
| β βββ ... | |
| βββ README.md | |
| - Each `sample_xxxx` directory corresponds to **one data sample** | |
| - Files inside each sample directory represent **ground-truth layers** | |
| - Folder structure is preserved to simplify indexing and loading | |
| --- | |
| ## π How to Use | |
| You can access this dataset using the π€ `datasets` library: | |
| ```python | |
| from datasets import load_dataset | |
| dataset = load_dataset("dereklin1205/dlcv_final") | |