Upload IJB-A HF-ready dataset (frame/ packed as frame.tar)

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README.md

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+---
+license: other
+task_categories:
+- image-classification
+- zero-shot-image-classification
+tags:
+- face-recognition
+- face-verification
+- face-identification
+- ijb-a
+- janus
+- template-based
+pretty_name: IJB-A HF-ready
+size_categories:
+- 10K<n<100K
+---
+
+# IJB-A HF-ready
+
+This repo packages the IARPA Janus Benchmark-A (IJB-A) face recognition dataset
+in its CleanData layout, plus the official 10-split 1:1 verification and 1:N
+identification protocols.
+
+Unlike LFW-style benchmarks, IJB-A is **template-based**: each subject is
+represented by a *template* aggregating multiple still images and/or video
+frames. Protocol CSVs map every (template, file) row to a face annotation with
+bounding box, landmarks, and demographic attributes.
+
+## Layout
+
+```
+ijba/
+├── README.md
+├── files.csv
+├── img/                              # 5396 still images (flat)
+├── frame.tar                         # 20369 video frames packed into a single tar (~817 MB)
+├── img.txt                           # upstream bbox annotations subset (still images)
+├── frame.txt                         # upstream bbox annotations subset (video frames)
+└── protocols/
+    ├── IJB-A_11_sets/split{1..10}/    # 1:1 verification protocol inputs
+    │   ├── train_<n>.csv
+    │   ├── verify_metadata_<n>.csv
+    │   └── verify_comparisons_<n>.csv
+    ├── IJB-A_11_output/split{1..10}/  # baseline 1:1 outputs (.matches)
+    ├── IJB-A_1N_sets/split{1..10}/    # 1:N identification protocol inputs
+    │   ├── train_<n>.csv
+    │   ├── search_gallery_<n>.csv
+    │   └── search_probe_<n>.csv
+    └── IJB-A_1N_output/split{1..10}/  # baseline 1:N outputs (.candidate_lists)
+```
+
+## Protocol CSV columns
+
+`train_*.csv`, `verify_metadata_*.csv`, `search_gallery_*.csv`, `search_probe_*.csv`
+all share the same schema:
+
+`TEMPLATE_ID, SUBJECT_ID, FILE, MEDIA_ID, SIGHTING_ID, FRAME, FACE_X, FACE_Y,
+FACE_WIDTH, FACE_HEIGHT, RIGHT_EYE_X, RIGHT_EYE_Y, LEFT_EYE_X, LEFT_EYE_Y,
+NOSE_BASE_X, NOSE_BASE_Y, FACE_YAW, FOREHEAD_VISIBLE, EYES_VISIBLE,
+NOSE_MOUTH_VISIBLE, INDOOR, GENDER, SKIN_TONE, AGE, FACIAL_HAIR`
+
+The `FILE` column resolves relative to the dataset root, e.g. `img/8565.jpg` or
+`frame/28065_00000.png`.
+
+`verify_comparisons_*.csv` is a header-less file with two columns:
+`enroll_template_id, verify_template_id`.
+
+`*.matches` (verification baseline) and `*.candidate_lists` (identification
+baseline) preserve the upstream output schema — see the IJB-A documentation for
+details.
+
+## files.csv
+
+A flat index of every image with columns `file_name, kind, extension, size_bytes,
+referenced_in_protocols`. Use it for quick joins or coverage checks without
+walking the filesystem.
+
+## Local Stats
+
+- Still images (`img/`): 5396
+- Video frames (`frame/`): 20369
+- Total images: 25765
+- Distinct files referenced by protocols: 25791
+- Verification splits: 10 (`IJB-A_11_sets/split1..split10`, 30 CSVs total)
+- Verification baseline outputs: 10 (`IJB-A_11_output/`, 10 files total)
+- Identification splits: 10 (`IJB-A_1N_sets/split1..split10`, 30 CSVs total)
+- Identification baseline outputs: 10 (`IJB-A_1N_output/`, 10 files total)
+
+## Missing protocol references
+
+The upstream CleanData drop is missing 26 frames that are
+referenced by at least one protocol CSV. Filter rows on these `FILE` values
+before loading them, or skip silently:
+
+- `frame/28264_00000.png`
+- `frame/28296_00337.png`
+- `frame/28296_00397.png`
+- `frame/28296_00448.png`
+- `frame/28296_00508.png`
+- `frame/28296_00928.png`
+- `frame/28296_00983.png`
+- `frame/28296_01011.png`
+- `frame/28296_01079.png`
+- `frame/28296_01375.png`
+- `frame/28296_01380.png`
+- `frame/28296_01440.png`
+- `frame/28296_01500.png`
+- `frame/28296_01560.png`
+- `frame/28317_01035.png`
+- `frame/28332_01020.png`
+- `frame/28496_00000.png`
+- `frame/28552_00660.png`
+- `frame/28593_00000.png`
+- `frame/28789_00000.png`
+- `frame/28928_00000.png`
+- `frame/29192_00000.png`
+- `frame/29387_00125.png`
+- `frame/29563_00000.png`
+- `frame/30369_00000.png`
+- `frame/30387_00060.png`
+
+## Unpacking video frames
+
+Video frames are shipped as a single `frame.tar` archive (uploading 20k tiny
+PNGs to the Hub triggered server-side commit failures). After downloading the
+repo, extract it once so the protocol `FILE` paths resolve:
+
+```bash
+tar xf frame.tar     # creates frame/<video_id>_<frame_offset>.png
+```
+
+## Loading
+
+```python
+import pandas as pd
+import tarfile
+from huggingface_hub import snapshot_download
+from pathlib import Path
+from PIL import Image
+
+root = Path(snapshot_download(repo_id="marcelohaps/ijb-a", repo_type="dataset"))
+
+# Extract frame.tar in place if not already extracted
+if not (root / "frame").exists():
+    with tarfile.open(root / "frame.tar") as tf:
+        tf.extractall(root)
+
+# 1:1 verification, split 1
+metadata = pd.read_csv(root / "protocols/IJB-A_11_sets/split1/verify_metadata_1.csv")
+comparisons = pd.read_csv(
+    root / "protocols/IJB-A_11_sets/split1/verify_comparisons_1.csv",
+    header=None, names=["enroll_template_id", "verify_template_id"],
+)
+
+# Open the first face referenced by template_id 109
+row = metadata[metadata["TEMPLATE_ID"] == 109].iloc[0]
+image = Image.open(root / row["FILE"])
+```
+
+## Notes
+
+IJB-A is distributed under the IARPA Janus benchmark license. Check the original
+dataset terms before publishing or redistributing it. This package preserves the
+upstream filenames (case included), bounding boxes, and protocol files verbatim.

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