| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: mask |
| dtype: image |
| - name: label |
| dtype: image |
| splits: |
| - name: train |
| num_bytes: 1269680775.5 |
| num_examples: 3025 |
| - name: test |
| num_bytes: 229042164.0 |
| num_examples: 553 |
| download_size: 1464680989 |
| dataset_size: 1498722939.5 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| - split: test |
| path: data/test-* |
| --- |
| |
| ChestX-Det is a chest X-Ray dataset with instance-level annotations (boxes and masks). ChestX-Det is a subset of the public dataset NIH ChestX-ray14. It contains ~3500 images of 13 common disease categories labeled by three board-certified radiologists. |
|
|
| I created segmentation masks for each image in the dataset. Each image is mapped to a unique RGB value. |
|
|
| The repository from Deepwise AILab can be found at: https://github.com/Deepwise-AILab/ChestX-Det-Dataset. |
|
|
| More information at: https://paperswithcode.com/dataset/chestx-det. |
