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README.md

@@ -1,66 +1,84 @@
 ---
-dataset_info:
-  features:
-  - name: image
-    dtype: image
-  - name: image_id
-    dtype: int64
-  - name: width
-    dtype: int64
-  - name: height
-    dtype: int64
-  - name: file_name
-    dtype: string
-  - name: pan_seg
-    dtype: image
-  - name: pan_seg_file_name
-    dtype: string
-  - name: objects
-    sequence:
-    - name: id
-      dtype: int64
-    - name: bbox
-      sequence: float64
-      length: 4
-    - name: category_id
-      dtype: int64
-    - name: area
-      dtype: float64
-    - name: iscrowd
-      dtype: int64
-    - name: isthing
-      dtype: int64
-    - name: segment_id
-      dtype: int64
-  - name: relations
-    sequence:
-    - name: id
-      dtype: int64
-    - name: subject_id
-      dtype: int64
-    - name: object_id
-      dtype: int64
-    - name: predicate_id
-      dtype: int64
-  - name: neg_relations
-    sequence:
-    - name: id
-      dtype: int64
-    - name: subject_id
-      dtype: int64
-    - name: object_id
-      dtype: int64
-    - name: predicate_id
-      dtype: int64
-  splits:
-  - name: test
-    num_bytes: 8252954078.104
-    num_examples: 11368
-  download_size: 8217330405
-  dataset_size: 8252954078.104
-configs:
-- config_name: default
-  data_files:
-  - split: test
-    path: data/test-*
+license: other
+license_name: sa-1b-dataset-research-license
+license_link: https://huggingface.co/datasets/maelic/Haystack-coco-format/blob/main/LICENSE_SA-1B
+task_categories:
+  - object-detection
+tags:
+  - scene-graph-generation
+  - panoptic-scene-graph
+  - negative-annotations
+  - haystack
+  - sa-1b
+  - coco-format
+language:
+  - en
+pretty_name: Haystack (COCO format)
+size_categories:
+  - 10K<n<100K
 ---
+
+# Haystack (COCO format)
+
+A mirror of **Haystack** (Lorenz, Barthel, Kienzle and Lienhart, *Haystack: A Panoptic Scene Graph
+Dataset to Evaluate Rare Predicate Classes*, ICCV 2023 workshops), reformatted in the
+same COCO-style schema as the other `maelic/*-coco-format` datasets. Haystack's distinguishing
+feature is **explicit negative relation annotations**: for an annotated subject–object pair, an
+annotator also confirmed predicates that do *not* hold, so evaluation does not have to treat
+missing labels as negatives.
+
+It is used by axis A2 (precision against adjudicated negatives) of OV-SGG-Bench.
+
+## Why this mirror exists
+
+The original download location (`myweb.rz.uni-augsburg.de/~lorenjul/haystack/v1/`) returns HTTP 404
+as of November 2026. This repository preserves the v1 release byte-for-byte where possible so that
+results on Haystack remain reproducible. The authors' code is at
+<https://github.com/lorjul/haystack>.
+
+## Licenses
+
+* **Images** are a subset of Meta's SA-1B dataset and are provided under the **SA-1B Dataset
+  Research License** (`LICENSE_SA-1B`, with Meta's notice in `NOTICE_SA-1B.md`): research,
+  non-commercial use only. By downloading the images you agree to that license. See
+  <https://ai.meta.com/datasets/segment-anything/>.
+* **Annotations** (relations, negative relations, panoptic masks) are the Haystack authors' work.
+  Their release did not state a license. Cite their paper when you use them.
+
+## Contents
+
+One split, `test`, with 11,368 images, 2,870 positive relations and 23,174 negative relations over
+133 categories (80 things, 53 stuff) and the 56 predicates of PSG. `categories.json` holds
+`thing_classes`, `stuff_classes`, `categories` (things then stuff, the index used by `category_id`)
+and `predicates` (the index used by `predicate_id`).
+
+| Field | Description |
+|---|---|
+| `image` | the SA-1B JPEG, original bytes |
+| `image_id`, `width`, `height`, `file_name` | as in the source (`sa_XXXXXX/sa_N.jpg`) |
+| `pan_seg`, `pan_seg_file_name` | the panoptic segmentation PNG, original bytes |
+| `objects` | `id` (index in the image), `bbox` (COCO `[x, y, w, h]`, pixels), `category_id`, `area` (segment area), `iscrowd`, `isthing`, `segment_id` (the segment's id in `pan_seg`) |
+| `relations` | positive relations: `id`, `subject_id`, `object_id` (indices into `objects`), `predicate_id` |
+| `neg_relations` | adjudicated negative relations, same fields |
+
+## Changes from the source
+
+All mechanical: boxes converted from Detectron2 `XYXY_ABS` to COCO `[x, y, w, h]`; object and
+relation ids made image-local indices; images and masks stored with their original bytes, not
+re-encoded. A random sample of 50 images was checked byte-for-byte against the source archives.
+Source archive SHA-256: `sa1b-subset.zip`
+`cff441c94ba7ce3af5b000a5b1648e9610e3357241338698e3bd79cb396bb919`, `v1.zip`
+`07401be66aa4f048a3d52e12b624f393166654b42a4275cb5a051de7fe7ebee4`.
+
+## Citation
+
+```bibtex
+@inproceedings{lorenz2023haystack,
+  title     = {Haystack: A Panoptic Scene Graph Dataset to Evaluate Rare Predicate Classes},
+  author    = {Lorenz, Julian and Barthel, Florian and Kienzle, Daniel and Lienhart, Rainer},
+  booktitle = {IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)},
+  pages     = {62--70},
+  year      = {2023},
+  doi       = {10.1109/ICCVW60793.2023.00013}
+}
+```