| --- |
| license: cc-by-4.0 |
| task_categories: |
| - object-detection |
| tags: |
| - stamp-detection |
| - document-analysis |
| - object-detection |
| - yolo |
| - computer-vision |
| pretty_name: Clean Core Stamp Detection Dataset |
| size_categories: |
| - 1K<n<10K |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: string |
| splits: |
| - name: train |
| num_examples: 6283 |
| - name: validation |
| num_examples: 785 |
| - name: test |
| num_examples: 786 |
| --- |
| |
| # Clean Core Stamp Detection Dataset |
|
|
| A cleaned document-stamp detection dataset built from curated raw sources only. |
| This version replaces the previous `mapo80/stamps` release and removes noisy or |
| off-target sources such as postage stamps, shape/identity datasets, corrupted |
| multi-class remaps, and duplicated negatives. |
|
|
| ## Overview |
|
|
| | Parameter | Value | |
| |-----------|-------| |
| | Task | Object detection | |
| | Classes | 1 (`stamp`, class id 0) | |
| | Total images | 7854 | |
| | Positive images | 6608 | |
| | Negative images | 1246 | |
| | Total bounding boxes | 12659 | |
| | Annotation format | YOLO txt (`class x_center y_center width height`) | |
|
|
| ## Splits |
|
|
| | Split | Total Images | Positive | Negative | Bounding Boxes | |
| |-------|-------------:|---------:|---------:|---------------:| |
| | Train | 6283 | 5287 | 996 | 10046 | |
| | Val | 785 | 660 | 125 | 1298 | |
| | Test | 786 | 661 | 125 | 1315 | |
|
|
| ## What Changed |
|
|
| - Kept only in-scope document stamp sources |
| - Filtered `stamp_detection_stampa` to the raw `stamp` class only |
| - Removed postage-stamp, shape, identity, and corrupted mixed-class sources |
| - Rebuilt negatives from `RVL-CDIP` and `FUNSD` |
| - Dropped severe negative outliers (blank pages, almost-black pages, heavily degraded scans) |
| - Rebuilt train/val/test from scratch from `data/raw` |
|
|
| ## Included Sources |
|
|
| ### Positive sources |
|
|
| - `stamp_detection_jsam`: 4385 images |
| - `yolo_stamp_classify`: 1397 images |
| - `stamp_detectation_marcos`: 365 images |
| - `stamp_detection_stampa` (filtered): 461 images |
|
|
| ### Negative sources |
|
|
| - `neg_rvl_cdip`: 1048 images |
| - `neg_funsd`: 198 images |
|
|
| ## Excluded Source Families |
|
|
| - `detect_postage_stamp` |
| - `stamp_class` |
| - `stamp_shape` |
| - `stamp_individual` |
| - `stamp_recognition` |
| - `stamp_detection_shujing` |
| - `stamp_warisara` |
| - `staver_yolo` |
| - `neg_tobacco3482` |
|
|
| ## Directory Structure |
|
|
| The repository stores the dataset as zip archives: |
|
|
| ```text |
| train.zip |
| val.zip |
| test.zip |
| dataset.yaml |
| ``` |
|
|
| Each zip contains: |
|
|
| ```text |
| images/<split>/ |
| labels/<split>/ |
| ``` |
|
|
| ## `dataset.yaml` |
|
|
| ```yaml |
| path: . |
| train: images/train |
| val: images/val |
| test: images/test |
| |
| nc: 1 |
| names: |
| - stamp |
| ``` |
|
|
| ## Notes |
|
|
| - Empty label files are valid negatives |
| - This benchmark is intentionally narrower and cleaner than the previous release |
| - It is optimized for document-level stamp detection, not postage stamps or stamp classification |
|
|
