Release FOTBCD-CC caption annotations

README.md

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+---
+pretty_name: FOTBCD-CC
+license: cc-by-4.0
+language:
+  - en
+annotations_creators:
+  - machine-generated
+task_categories:
+  - image-to-text
+tags:
+  - image
+  - text
+  - geospatial
+  - remote-sensing
+  - aerial-imagery
+  - change-detection
+  - change-captioning
+  - temporal
+  - parquet
+  - arxiv:2601.22596
+size_categories:
+  - 100K<n<1M
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: data/train-*.parquet
+      - split: validation
+        path: data/val-*.parquet
+      - split: test
+        path: data/test-*.parquet
+---
+
+# FOTBCD-CC
+
+FOTBCD-CC adds natural-language change descriptions to the before-and-after aerial image pairs in [FOTBCD](https://huggingface.co/datasets/abdevd/FOTBCD). It contains **321,200 English captions for 223,675 temporal pairs** covering 28 departments across mainland France.
+
+This repository contains the caption annotations only. The corresponding images remain in FOTBCD and are linked through a pinned dataset revision, shard path, and WebDataset sample key. The imagery is not duplicated here.
+
+## Dataset summary
+
+| Split | Temporal pairs | Captions | Durable change | No durable change |
+| --- | ---: | ---: | ---: | ---: |
+| Train | 221,712 | 318,162 | 132,720 | 88,992 |
+| Validation | 984 | 1,532 | 704 | 280 |
+| Test | 979 | 1,506 | 692 | 287 |
+| **Total** | **223,675** | **321,200** | **134,116** | **89,559** |
+
+Every pair has between one and five captions. Captions average 26.13 words.
+
+## Annotation format
+
+Each row represents one before-and-after pair:
+
+| Field | Description |
+| --- | --- |
+| `sample_id` | Globally unique split and sample identifier |
+| `split` | `train`, `val`, or `test` |
+| `image_id` | Image-pair ID from FOTBCD |
+| `sample_key` | Key used inside the FOTBCD WebDataset shard |
+| `image_shard` | Path of the corresponding TAR shard in FOTBCD |
+| `before_member` / `after_member` | Image member names inside that shard |
+| `department` | French department code |
+| `before_year` / `after_year` | Acquisition years |
+| `epsg` | Spatial reference identifier; all samples use EPSG:2154 |
+| `crop_stratum` | Sampling stratum used during caption generation |
+| `patch_category` | Patch category from FOTBCD |
+| `building_annotation_count` | Number of FOTBCD building instances in the pair |
+| `durable_change` | Whether the captioner identified a lasting physical change |
+| `captions` | One to five generated descriptions |
+| `caption_count` | Number of descriptions in `captions` |
+
+The published Parquet files intentionally exclude inference-only logs such as latency, token usage, retries, duplicated raw responses, and empty error fields.
+
+## Durable change
+
+A durable change is a lasting physical alteration visible between the two dates, such as construction, demolition, a new paved road, an expanded building, or cleared woodland converted to another use.
+
+Differences caused only by shadows, parked vehicles, seasonal vegetation, cultivation cycles, or surface appearance are treated as no durable change. No-change rows still contain a scene description.
+
+## Load the captions
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("abdevd/FOTBCD-CC")
+row = dataset["train"][0]
+
+print(row["durable_change"])
+print(row["captions"])
+print(row["image_shard"], row["sample_key"])
+```
+
+## Join captions with the FOTBCD images
+
+The Parquet rows point to the exact WebDataset shards and members in the pinned FOTBCD revision:
+
+```python
+from datasets import load_dataset
+import webdataset as wds
+
+BASE_REVISION = "92b677c881f0d973d76460204431c711ccbac25b"
+BASE_URL = (
+    "https://huggingface.co/datasets/abdevd/FOTBCD/resolve/"
+    f"{BASE_REVISION}/"
+)
+
+captions = load_dataset("abdevd/FOTBCD-CC", split="train")
+caption_by_key = {row["sample_key"]: row for row in captions}
+shards = sorted({BASE_URL + row["image_shard"] for row in captions})
+
+images = wds.WebDataset(shards, shardshuffle=True).decode("pil")
+
+for sample in images:
+    annotation = caption_by_key[sample["__key__"]]
+    before_image = sample["before.png"]
+    after_image = sample["after.png"]
+    pair_captions = annotation["captions"]
+    # Train or evaluate your model here.
+```
+
+Install the required libraries with:
+
+```bash
+pip install datasets webdataset pillow
+```
+
+## Generation process
+
+The full annotations were generated by a Qwen3-VL-8B model adapted from Qwen3.8-Max teacher outputs.
+
+Qwen3.8-Max first annotated a selected teacher set of 19,997 temporal pairs, producing 29,447 captions. Those responses and durable-change decisions were then used for supervised LoRA response distillation into Qwen3-VL-8B. During fine-tuning, the vision tower and visual aligner were frozen while the language model was adapted. The resulting model was served through vLLM to annotate all 223,675 FOTBCD pairs.
+
+The student examines the complete before-and-after crops, predicts whether a durable change occurred, and produces one or more descriptions of the visible events or stable scene. Global annotation provenance, including the prompt hash, is recorded in `provenance.json` rather than repeated in every Parquet row.
+
+The source JSONL contained one successful, valid response for every FOTBCD pair. Before export, all 223,675 split/image identifiers and image paths were checked against the FOTBCD manifests. No missing pairs, duplicate keys, path mismatches, invalid responses, empty caption lists, or blank captions were found.
+
+## Licensing
+
+The FOTBCD-CC caption annotations are licensed under **CC BY 4.0**.
+
+The corresponding imagery and building data are provided by the **Institut national de l’information géographique et forestière** through BD ORTHO and BD TOPO, under the [Etalab Open Licence 2.0](https://www.etalab.gouv.fr/wp-content/uploads/2017/04/ETALAB-Licence-Ouverte-v2.0.pdf). See the [FOTBCD dataset card](https://huggingface.co/datasets/abdevd/FOTBCD) for the base dataset's documentation and attribution.
+
+## Citation
+
+When using the paired FOTBCD imagery, please cite:
+
+```bibtex
+@article{moubane2026fotbcd,
+  title   = {FOTBCD: A Large-Scale Building Change Detection Benchmark from French Orthophotos and Topographic Data},
+  author  = {Moubane, Abdelrrahman},
+  journal = {arXiv preprint arXiv:2601.22596},
+  year    = {2026},
+  url     = {https://arxiv.org/abs/2601.22596}
+}
+```
+

SHA256SUMS

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dataset-statistics.json

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+{
+  "base_dataset": "abdevd/FOTBCD",
+  "base_revision": "92b677c881f0d973d76460204431c711ccbac25b",
+  "splits": {
+    "train": {
+      "pairs": 221712,
+      "captions": 318162,
+      "durable_change_true": 132720,
+      "durable_change_false": 88992
+    },
+    "val": {
+      "pairs": 984,
+      "captions": 1532,
+      "durable_change_true": 704,
+      "durable_change_false": 280
+    },
+    "test": {
+      "pairs": 979,
+      "captions": 1506,
+      "durable_change_true": 692,
+      "durable_change_false": 287
+    }
+  },
+  "totals": {
+    "pairs": 223675,
+    "captions": 321200,
+    "durable_change_true": 134116,
+    "durable_change_false": 89559
+  }
+}

provenance.json

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+{
+  "annotation_type": "machine-generated",
+  "base_dataset": "abdevd/FOTBCD",
+  "base_revision": "92b677c881f0d973d76460204431c711ccbac25b",
+  "annotator_base_model": "Qwen3-VL-8B",
+  "teacher_model": "Qwen3.8-Max",
+  "teacher_pairs": 19997,
+  "teacher_captions": 29447,
+  "distillation_method": "supervised LoRA response distillation",
+  "training": {
+    "vision_tower": "frozen",
+    "visual_aligner": "frozen",
+    "language_model": "adapted with LoRA"
+  },
+  "bulk_inference_backend": "vLLM",
+  "prompt_sha256": "f27ab2cfdaa0cd237b814d7dfabb5b265f94a2ad7a5bd9afdb41c2119b8919ee"
+}