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CITATION.cff

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+cff-version: 1.2.0
+message: "If you use AgroVG, please cite the accompanying paper and dataset release."
+title: "AgroVG: A Large-Scale Multi-Domain Benchmark for Agricultural Visual Grounding"
+type: dataset
+authors:
+  - name: "Anonymous Authors"
+year: 2026
+version: "0.1.0-review"
+abstract: "AgroVG is a benchmark for agricultural visual grounding, including box-set grounding (T1) and query-level mask grounding (T2)."
+license: "CC-BY-4.0"
+url: "https://huggingface.co/datasets/sauryrs/AgroVG"
+keywords:
+  - visual grounding
+  - referring expression comprehension
+  - referring expression segmentation
+  - agriculture
+  - benchmark

LICENSE

@@ -0,0 +1,396 @@
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+

NOTICE

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+AgroVG Dataset Notice
+=====================
+
+This repository packages AgroVG, a benchmark for agricultural visual grounding.
+
+AgroVG-specific annotations, referring-expression queries, audit metadata, split metadata, and derived benchmark metadata are released under Creative Commons Attribution 4.0 International (CC BY 4.0), as provided in LICENSE.
+
+Images and source-derived annotations retain the licenses, terms, and redistribution permissions of their original source datasets. The file source_licenses.json lists each normalized source key, the task(s) in which it is used, source URLs, citations, license summaries, and release notes.
+
+This review release is hosted at:
+
+https://huggingface.co/datasets/sauryrs/AgroVG
+
+The release is prepared for anonymous NeurIPS 2026 review. Non-public permission correspondence is retained by the authors and is not included in this anonymized package.
+
+After review, CITATION.cff should be updated with final author names, venue information, DOI, and any permanent archival identifier.
+
+This anonymized review package intentionally omits author names, emails, institutions, local file-system paths, and internal review-sheet files.

README.md

@@ -1,3 +1,184 @@
----
-license: cc-by-4.0
----
+---
+pretty_name: AgroVG
+license: other
+task_categories:
+- object-detection
+- image-segmentation
+tags:
+- visual-grounding
+- referring-expression-comprehension
+- referring-expression-segmentation
+- agriculture
+- benchmark
+- mlcroissant
+size_categories:
+- 10K<n<100K
+language:
+- en
+configs:
+- config_name: t1_annotations
+  data_files:
+  - split: dev
+    path: t1/annotations/dev.jsonl
+  - split: test
+    path: t1/annotations/test.jsonl
+- config_name: t1_queries
+  data_files:
+  - split: dev
+    path: t1/queries/queries_dev.jsonl
+  - split: test
+    path: t1/queries/queries_test.jsonl
+- config_name: t2_annotations
+  data_files:
+  - split: dev
+    path: t2/annotations/dev.jsonl
+  - split: test
+    path: t2/annotations/test.jsonl
+- config_name: t2_queries
+  data_files:
+  - split: dev
+    path: t2/queries/queries_dev.jsonl
+  - split: test
+    path: t2/queries/queries_test.jsonl
+---
+
+# AgroVG
+
+AgroVG is a large-scale benchmark for agricultural visual grounding. It contains two evaluation tasks:
+
+- **T1: box-set visual grounding**, where a model receives an agricultural referring expression and returns a set of bounding boxes.
+- **T2: query-level mask grounding**, where a model receives an agricultural referring expression and returns a binary segmentation mask.
+
+This repository is the anonymized public-release package prepared for peer review and archival hosting. It contains only release data and metadata; construction scripts, model predictions, and evaluation code should be hosted in a separate code repository.
+
+Dataset URL for review: https://huggingface.co/datasets/sauryrs/AgroVG
+
+## Dataset Composition
+
+| Task | Images | Queries | Output target | Main files |
+|---|---:|---:|---|---|
+| T1 | 6,526 | 6,526 | Bounding-box set | `t1/annotations`, `t1/images`, `t1/queries` |
+| T2 | 3,545 | 3,545 | Query-level binary mask | `t2/annotations`, `t2/images`, `t2/instance_maps`, `t2/queries` |
+| Total | 10,071 | 10,071 | Boxes or masks | `t1`, `t2` |
+
+## Repository Structure
+
+```text
+AgroVG/
+  README.md
+  LICENSE
+  CITATION.cff
+  croissant.json
+  NOTICE
+  source_licenses.json
+  t1/
+    annotations/
+      annotations.jsonl
+      dev.jsonl
+      test.jsonl
+      final_audit_table.csv
+      policy.json
+      final_stats.json
+      split_stats.json
+      kept_ids.txt
+      dropped_ids.txt
+    images/
+      <source>/
+    queries/
+      queries_dev.jsonl
+      queries_test.jsonl
+      query_policy.json
+      query_stats.json
+  t2/
+    annotations/
+      annotations.jsonl
+      dev.jsonl
+      test.jsonl
+      final_audit_table.csv
+      policy.json
+      final_stats.json
+      split_stats.json
+      kept_ids.txt
+      dropped_ids.txt
+    images/
+      <source>/
+    instance_maps/
+      <source>/
+    queries/
+      queries_dev.jsonl
+      queries_test.jsonl
+      query_policy.json
+      query_stats.json
+```
+
+All `rgb_relpath` and `mask_relpath` fields are relative to the corresponding task root (`t1/` or `t2/`).
+
+## Annotation Records
+
+Each image annotation record contains:
+
+- `image_id`: stable image identifier.
+- `source`: normalized source-dataset key.
+- `scene_family`: benchmark-level scene family.
+- `sensor_type`: imaging context when available.
+- `task_candidates`: task list, e.g. `["T1"]` or `["T2"]`.
+- `annotation_type`: `bbox` for T1 and `instance_mask` for T2.
+- `rgb_relpath`: relative RGB image path.
+- `mask_relpath`: relative uint16 instance-map path for T2.
+- `width`, `height`: image dimensions.
+- `group_id`: group identifier used to avoid split leakage.
+- `split_source`: source-side split label when available.
+- `benchmark_split`: `dev` or `test`.
+- `instances`: normalized instance annotations.
+- `meta`: source-specific metadata retained for auditability.
+
+T1 instances include `object_id`, `class_family_global`, source-derived class labels, and `bbox_xyxy`. T2 instances additionally include `instance_local_id`, mask-derived geometry, mask area statistics, and mask-generation provenance when applicable.
+
+## Query Records
+
+Each query record contains the common fields:
+
+- `query_id`
+- `image_id`
+- `benchmark_split`
+- `source`
+- `scene_family`
+- `sensor_type`
+- `rgb_relpath`
+- `width`
+- `height`
+- `group_id`
+- `query`
+- `query_type`
+- `program_type`
+- `template_id`
+- `target_object_ids`
+- `target_count`
+- `is_empty`
+- `meta`
+
+T1 query records additionally include `target_boxes`. T2 query records additionally include `mask_relpath` and `target_instance_local_ids`.
+
+## Splits
+
+AgroVG uses `dev` and `test` splits. Split construction is group-aware: records sharing a `group_id` are assigned to the same benchmark split to reduce leakage across visually related images.
+
+## Evaluation
+
+T1 evaluates set-level box grounding with IoU-thresholded matching. T2 evaluates query-level mask grounding with overlap-based mask metrics and separate target-absent accuracy. Evaluation scripts are not included in this data-only package and should be released in the accompanying code repository.
+
+## Licensing
+
+AgroVG-specific annotations, query templates, audit metadata, and derived benchmark metadata are released under Creative Commons Attribution 4.0 International (CC BY 4.0), included in `LICENSE`.
+
+Images and source-derived annotations retain the licenses, terms, and redistribution permissions of their original source datasets. Source-level license and attribution information is summarized in `source_licenses.json` and `NOTICE`. Non-public permission correspondence is intentionally not included in this anonymized review package.
+
+## Responsible Use and Limitations
+
+AgroVG is intended for research on agricultural visual grounding, referring-expression comprehension, referring segmentation, and robustness analysis across agricultural domains. It is not intended for direct deployment in farm-management, pesticide, disease-treatment, yield-estimation, or safety-critical agricultural decision systems without additional domain validation.
+
+Known limitations include source-dataset heterogeneity, uneven geographic and crop coverage, possible source-specific annotation biases, and the fact that AgroVG normalizes existing source labels rather than re-certifying all taxonomic labels from scratch.
+
+## Citation
+
+This anonymized release is associated with a NeurIPS 2026 submission. Please cite the accompanying anonymous submission during review. The citation metadata in `CITATION.cff` should be updated with final author names, venue information, and DOI after the review process.

croissant.json

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+{
+  "@context": {
+    "@vocab": "https://schema.org/",
+    "sc": "https://schema.org/",
+    "cr": "http://mlcommons.org/croissant/",
+    "rai": "http://mlcommons.org/croissant/RAI/",
+    "prov": "http://www.w3.org/ns/prov#"
+  },
+  "@type": "sc:Dataset",
+  "conformsTo": "http://mlcommons.org/croissant/1.1",
+  "name": "AgroVG",
+  "description": "AgroVG is a large-scale multi-domain benchmark for agricultural visual grounding. It includes T1 box-set grounding and T2 query-level mask grounding.",
+  "url": "https://huggingface.co/datasets/sauryrs/AgroVG",
+  "license": "https://huggingface.co/datasets/sauryrs/AgroVG/blob/main/source_licenses.json",
+  "version": "0.1.0-review",
+  "datePublished": "2026-01-01",
+  "citeAs": "Anonymous Authors. AgroVG: A Large-Scale Multi-Domain Benchmark for Agricultural Visual Grounding. NeurIPS 2026 submission, dataset version 0.1.0-review, 2026.",
+  "creator": [
+    {
+      "@type": "Organization",
+      "name": "Anonymous Authors"
+    }
+  ],
+  "keywords": [
+    "visual grounding",
+    "referring expression comprehension",
+    "referring expression segmentation",
+    "agriculture",
+    "benchmark"
+  ],
+  "distribution": [
+    {
+      "@type": "cr:FileSet",
+      "name": "t1_images",
+      "description": "RGB images for AgroVG-T1.",
+      "encodingFormat": "image/png, image/jpeg",
+      "includes": "t1/images/**/*"
+    },
+    {
+      "@type": "cr:FileSet",
+      "name": "t2_images",
+      "description": "RGB images for AgroVG-T2.",
+      "encodingFormat": "image/png, image/jpeg",
+      "includes": "t2/images/**/*"
+    },
+    {
+      "@type": "cr:FileSet",
+      "name": "t2_instance_maps",
+      "description": "Uint16 instance maps for AgroVG-T2.",
+      "encodingFormat": "image/png",
+      "includes": "t2/instance_maps/**/*"
+    },
+    {
+      "@type": "cr:FileObject",
+      "name": "t1_annotations",
+      "description": "AgroVG-T1 image-level annotation records.",
+      "encodingFormat": "application/jsonl",
+      "contentUrl": "t1/annotations/annotations.jsonl"
+    },
+    {
+      "@type": "cr:FileObject",
+      "name": "t2_annotations",
+      "description": "AgroVG-T2 image-level annotation records.",
+      "encodingFormat": "application/jsonl",
+      "contentUrl": "t2/annotations/annotations.jsonl"
+    },
+    {
+      "@type": "cr:FileObject",
+      "name": "t1_queries_dev",
+      "description": "AgroVG-T1 development queries.",
+      "encodingFormat": "application/jsonl",
+      "contentUrl": "t1/queries/queries_dev.jsonl"
+    },
+    {
+      "@type": "cr:FileObject",
+      "name": "t1_queries_test",
+      "description": "AgroVG-T1 test queries.",
+      "encodingFormat": "application/jsonl",
+      "contentUrl": "t1/queries/queries_test.jsonl"
+    },
+    {
+      "@type": "cr:FileObject",
+      "name": "t2_queries_dev",
+      "description": "AgroVG-T2 development queries.",
+      "encodingFormat": "application/jsonl",
+      "contentUrl": "t2/queries/queries_dev.jsonl"
+    },
+    {
+      "@type": "cr:FileObject",
+      "name": "t2_queries_test",
+      "description": "AgroVG-T2 test queries.",
+      "encodingFormat": "application/jsonl",
+      "contentUrl": "t2/queries/queries_test.jsonl"
+    },
+    {
+      "@type": "cr:FileObject",
+      "name": "source_licenses",
+      "description": "Source-dataset license and attribution template.",
+      "encodingFormat": "application/json",
+      "contentUrl": "source_licenses.json"
+    }
+  ],
+  "recordSet": [
+    {
+      "@type": "cr:RecordSet",
+      "name": "t1_image_records",
+      "description": "Image-level records for box-set grounding.",
+      "data": [
+        {
+          "@type": "cr:Field",
+          "name": "image_id",
+          "dataType": "sc:Text",
+          "description": "Stable image identifier."
+        },
+        {
+          "@type": "cr:Field",
+          "name": "rgb_relpath",
+          "dataType": "sc:Text",
+          "description": "RGB image path relative to t1/."
+        },
+        {
+          "@type": "cr:Field",
+          "name": "instances",
+          "dataType": "sc:Text",
+          "description": "Nested list of localized object instances with bounding boxes."
+        }
+      ]
+    },
+    {
+      "@type": "cr:RecordSet",
+      "name": "t2_image_records",
+      "description": "Image-level records for query-level mask grounding.",
+      "data": [
+        {
+          "@type": "cr:Field",
+          "name": "image_id",
+          "dataType": "sc:Text",
+          "description": "Stable image identifier."
+        },
+        {
+          "@type": "cr:Field",
+          "name": "rgb_relpath",
+          "dataType": "sc:Text",
+          "description": "RGB image path relative to t2/."
+        },
+        {
+          "@type": "cr:Field",
+          "name": "mask_relpath",
+          "dataType": "sc:Text",
+          "description": "Uint16 instance-map path relative to t2/."
+        },
+        {
+          "@type": "cr:Field",
+          "name": "instances",
+          "dataType": "sc:Text",
+          "description": "Nested list of localized object instances with mask identifiers."
+        }
+      ]
+    },
+    {
+      "@type": "cr:RecordSet",
+      "name": "query_records",
+      "description": "Referring-expression query records for both T1 and T2.",
+      "data": [
+        {
+          "@type": "cr:Field",
+          "name": "query_id",
+          "dataType": "sc:Text",
+          "description": "Stable query identifier."
+        },
+        {
+          "@type": "cr:Field",
+          "name": "query",
+          "dataType": "sc:Text",
+          "description": "Natural-language referring expression."
+        },
+        {
+          "@type": "cr:Field",
+          "name": "query_type",
+          "dataType": "sc:Text",
+          "description": "Single-target, multi-target, or target-absent query type."
+        },
+        {
+          "@type": "cr:Field",
+          "name": "target_object_ids",
+          "dataType": "sc:Text",
+          "description": "Target object identifiers referenced by the query."
+        }
+      ]
+    }
+  ],
+  "rai:dataLimitations": "AgroVG combines heterogeneous source datasets and inherits source-specific coverage, imaging, and annotation biases. It should not be used as the sole validation source for safety-critical agricultural decisions.",
+  "rai:dataBiases": "Coverage is shaped by the source datasets and may be uneven across crops, pests, diseases, geographic regions, sensors, growth stages, and imaging conditions.",
+  "rai:personalSensitiveInformation": "The dataset is agricultural imagery and is not intended to contain personal or sensitive human information. The release package has been scrubbed of local file-system paths and internal review notes.",
+  "rai:dataUseCases": "Research on agricultural visual grounding, referring-expression comprehension, referring segmentation, robustness analysis, and benchmark evaluation.",
+  "rai:dataSocialImpact": "The benchmark may support more robust agricultural perception research, but model outputs should not be directly used for farm-management, pesticide, treatment, or yield decisions without independent domain validation.",
+  "rai:hasSyntheticData": "False. The release contains normalized annotations, generated referring expressions, and derived masks, but does not synthesize RGB imagery.",
+  "prov:wasDerivedFrom": [
+    "https://www.phenobench.org",
+    "https://github.com/cropandweed/cropandweed-dataset",
+    "https://conservancy.umn.edu/handle/11299/206575",
+    "http://data.acfr.usyd.edu.au/ag/treecrops/2016-multifruit/",
+    "https://www.kaggle.com/datasets/mmwang0/megafruits",
+    "https://zenodo.org/records/5092309",
+    "https://github.com/xpwu95/IP102",
+    "https://zenodo.org/records/13762907",
+    "https://zenodo.org/records/11617167",
+    "https://zenodo.org/records/15155081"
+  ],
+  "prov:wasGeneratedBy": "AgroVG normalization, audit, query-generation, and split-construction pipelines. Release package is anonymized for review."
+}

source_licenses.json

@@ -0,0 +1,213 @@
+{
+  "schema_version": "0.2.0",
+  "generated_for": "AgroVG public-release packaging",
+  "last_checked": "2026-05-05",
+  "note": "This file records source-dataset license information used by AgroVG. It is a metadata summary, not legal advice. AgroVG-specific annotations, query templates, audit metadata, split metadata, and derived benchmark metadata are released under CC BY 4.0, but source images and source-derived annotations remain governed by their original source terms.",
+  "agrovg_contributions": {
+    "license_name": "Creative Commons Attribution 4.0 International",
+    "license_spdx": "CC-BY-4.0",
+    "license_url": "https://creativecommons.org/licenses/by/4.0/",
+    "redistribution_status": "allowed_with_attribution",
+    "applies_to": [
+      "normalized annotation schema",
+      "query records",
+      "audit metadata",
+      "split metadata",
+      "derived benchmark metadata"
+    ]
+  },
+  "sources": [
+    {
+      "source_key": "phenobench",
+      "display_name": "PhenoBench",
+      "used_in": ["T1", "T2"],
+      "num_images": 1260,
+      "license_name": "Creative Commons Attribution ShareAlike 4.0 International",
+      "license_spdx": "CC-BY-SA-4.0",
+      "license_url": "https://creativecommons.org/licenses/by-sa/4.0/",
+      "source_url": "https://www.phenobench.org",
+      "metadata_url": "https://github.com/PRBonn/phenobench",
+      "citation": "Weyler et al., PhenoBench: A Large Dataset and Benchmarks for Semantic Image Interpretation in the Agricultural Domain, 2024.",
+      "redistribution_status": "allowed_with_attribution_and_sharealike",
+      "license_notes": "The PhenoBench development kit FAQ states that the dataset is distributed under CC-BY-SA 4.0 and permits research and commercial usage with attribution and share-alike terms."
+    },
+    {
+      "source_key": "cropandweed",
+      "display_name": "CropAndWeed",
+      "used_in": ["T1", "T2"],
+      "num_images": 1075,
+      "license_name": "Custom non-commercial license; no redistribution of dataset or modified versions",
+      "license_spdx": "LicenseRef-CropAndWeed-NonCommercial-NoRedistribution",
+      "license_url": "https://github.com/cropandweed/cropandweed-dataset/blob/main/LICENCE",
+      "source_url": "https://github.com/cropandweed/cropandweed-dataset",
+      "citation": "Steininger et al., The CropAndWeed Dataset: A Multi-Modal Learning Approach for Efficient Crop and Weed Manipulation, WACV 2023.",
+      "redistribution_status": "not_redistributable_without_explicit_permission",
+      "license_notes": "The source license permits non-commercial use but explicitly says users must not distribute the dataset or modified versions. Do not include CropAndWeed RGB images or directly recoverable modified versions in a public Hugging Face release unless explicit permission is obtained."
+    },
+    {
+      "source_key": "minneapple",
+      "display_name": "MinneApple",
+      "used_in": ["T1"],
+      "num_images": 598,
+      "license_name": "Creative Commons Attribution-NonCommercial-ShareAlike 3.0 United States",
+      "license_spdx": "CC-BY-NC-SA-3.0-US",
+      "license_url": "http://creativecommons.org/licenses/by-nc-sa/3.0/us/",
+      "source_url": "https://conservancy.umn.edu/handle/11299/206575",
+      "doi": "10.13020/8ecp-3r13",
+      "citation": "Haeni, Roy, and Isler, MinneApple: A Benchmark Dataset for Apple Detection and Segmentation, DRUM, 2019.",
+      "redistribution_status": "allowed_for_noncommercial_use_with_attribution_and_sharealike",
+      "license_notes": "The DRUM record lists CC BY-NC-SA 3.0 US. Public redistribution should preserve non-commercial and share-alike terms."
+    },
+    {
+      "source_key": "acfr",
+      "display_name": "ACFR Orchard Fruit Dataset",
+      "used_in": ["T1"],
+      "num_images": 636,
+      "license_name": "Unknown / not clearly stated on located public dataset pages",
+      "license_spdx": "LicenseRef-ACFR-Unknown",
+      "license_url": null,
+      "source_url": "http://data.acfr.usyd.edu.au/ag/treecrops/2016-multifruit/",
+      "citation": "Bargoti and Underwood, Deep Fruit Detection in Orchards, ICRA 2017.",
+      "redistribution_status": "unknown_needs_permission_before_public_redistribution",
+      "license_notes": "Located public index/aggregator pages report the ACFR license as unknown. Obtain explicit redistribution permission or remove ACFR RGB images before public release."
+    },
+    {
+      "source_key": "acfr_apples",
+      "display_name": "ACFR Apples",
+      "used_in": ["T2"],
+      "num_images": 84,
+      "license_name": "Unknown / not clearly stated on located public dataset pages",
+      "license_spdx": "LicenseRef-ACFR-Unknown",
+      "license_url": null,
+      "source_url": "http://data.acfr.usyd.edu.au/ag/treecrops/2016-multifruit/",
+      "citation": "Bargoti and Underwood, Deep Fruit Detection in Orchards, ICRA 2017; Bargoti and Underwood, Image Segmentation for Fruit Detection and Yield Estimation in Apple Orchards.",
+      "redistribution_status": "unknown_needs_permission_before_public_redistribution",
+      "license_notes": "This AgroVG subset uses ACFR apple imagery and derived instance maps. Since the source license is not clearly stated, public redistribution should wait for permission or be replaced by reconstruction instructions."
+    },
+    {
+      "source_key": "magefruits_blueberry",
+      "display_name": "MegaFruits Blueberry",
+      "used_in": ["T2"],
+      "num_images": 554,
+      "license_name": "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International",
+      "license_spdx": "CC-BY-NC-SA-4.0",
+      "license_url": "https://creativecommons.org/licenses/by-nc-sa/4.0/",
+      "source_url": "https://www.kaggle.com/datasets/mmwang0/megafruits",
+      "citation": "Wang et al., MegaFruits dataset, Kaggle, version 2.",
+      "redistribution_status": "allowed_for_noncommercial_use_with_attribution_and_sharealike",
+      "license_notes": "Kaggle metadata for MegaFruits lists CC BY-NC-SA 4.0."
+    },
+    {
+      "source_key": "magefruits_peach",
+      "display_name": "MegaFruits Peach",
+      "used_in": ["T2"],
+      "num_images": 585,
+      "license_name": "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International",
+      "license_spdx": "CC-BY-NC-SA-4.0",
+      "license_url": "https://creativecommons.org/licenses/by-nc-sa/4.0/",
+      "source_url": "https://www.kaggle.com/datasets/mmwang0/megafruits",
+      "citation": "Wang et al., MegaFruits dataset, Kaggle, version 2.",
+      "redistribution_status": "allowed_for_noncommercial_use_with_attribution_and_sharealike",
+      "license_notes": "Kaggle metadata for MegaFruits lists CC BY-NC-SA 4.0."
+    },
+    {
+      "source_key": "gwhd2021",
+      "display_name": "Global Wheat Head Dataset 2021",
+      "used_in": ["T1"],
+      "num_images": 1091,
+      "license_name": "Creative Commons Attribution 4.0 International",
+      "license_spdx": "CC-BY-4.0",
+      "license_url": "https://creativecommons.org/licenses/by/4.0/",
+      "source_url": "https://zenodo.org/records/5092309",
+      "doi": "10.5281/zenodo.5092309",
+      "citation": "David et al., Global Wheat Head Dataset 2021: more diversity to improve the benchmarking of wheat head localization methods, 2021.",
+      "redistribution_status": "allowed_with_attribution",
+      "license_notes": "Zenodo metadata lists license id cc-by-4.0. The Global Wheat site also describes the dataset as free to use for any purpose."
+    },
+    {
+      "source_key": "ip102_detection",
+      "display_name": "IP102 Detection",
+      "used_in": ["T1"],
+      "num_images": 1255,
+      "license_name": "Custom academic-use license",
+      "license_spdx": "LicenseRef-IP102-Academic-Only",
+      "license_url": "https://github.com/xpwu95/IP102",
+      "source_url": "https://github.com/xpwu95/IP102",
+      "citation": "Wu et al., IP102: A Large-Scale Benchmark Dataset for Insect Pest Recognition, CVPR 2019.",
+      "redistribution_status": "academic_use_only_permission_recommended_for_public_redistribution",
+      "license_notes": "The source README states that the dataset is free for academic usage and asks users to contact the maintainer for other purposes. It does not clearly grant third-party redistribution rights."
+    },
+    {
+      "source_key": "plantseg",
+      "display_name": "PlantSeg",
+      "used_in": ["T1", "T2"],
+      "num_images": 2358,
+      "license_name": "Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International",
+      "license_spdx": "CC-BY-NC-ND-4.0",
+      "license_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
+      "source_url": "https://zenodo.org/records/13762907",
+      "doi": "10.5281/zenodo.13762907",
+      "citation": "Wei, PlantSeg: A Large-Scale In-the-wild Dataset for Plant Disease Segmentation, Zenodo, 2024.",
+      "redistribution_status": "noncommercial_original_redistribution_only_no_derivatives",
+      "license_notes": "Zenodo metadata lists CC BY-NC-ND 4.0. Because the license includes NoDerivatives, redistribution of transformed/derived annotations or modified source materials needs careful review or explicit permission."
+    },
+    {
+      "source_key": "oam_tcd",
+      "display_name": "OAM-TCD",
+      "used_in": ["T1"],
+      "num_images": 104,
+      "license_name": "Mixed Creative Commons licenses: CC BY 4.0, CC BY-NC 4.0, and CC BY-SA 4.0",
+      "license_spdx": "LicenseRef-OAM-TCD-Mixed-CC",
+      "license_url": "https://zenodo.org/records/11617167",
+      "source_url": "https://zenodo.org/records/11617167",
+      "doi": "10.5281/zenodo.11617167",
+      "citation": "Veitch-Michaelis et al., OAM-TCD: A globally diverse dataset of high-resolution tree cover maps, 2024.",
+      "redistribution_status": "allowed_subject_to_per_image_license",
+      "license_breakdown_in_source": {
+        "CC-BY-4.0": 4608,
+        "CC-BY-NC-4.0": 272,
+        "CC-BY-SA-4.0": 192
+      },
+      "license_breakdown_in_agrovg_metadata": {
+        "license_id_1": 14,
+        "license_id_2": 85,
+        "license_id_3": 5
+      },
+      "license_notes": "OAM-TCD documentation states that images are split by license class. AgroVG currently preserves numeric license_id values from source metadata; verify the id-to-license mapping before public release or keep OAM-TCD records separated by license."
+    },
+    {
+      "source_key": "dumortier",
+      "display_name": "Annotated tree crown bounding boxes in urban/rural environment",
+      "used_in": ["T1"],
+      "num_images": 471,
+      "license_name": "Creative Commons Zero v1.0 Universal",
+      "license_spdx": "CC0-1.0",
+      "license_url": "https://creativecommons.org/publicdomain/zero/1.0/",
+      "source_url": "https://zenodo.org/records/15155081",
+      "doi": "10.5281/zenodo.15155081",
+      "citation": "Dumortier, Annotated tree crown bounding boxes in urban/rural environment, Zenodo, 2025.",
+      "redistribution_status": "public_domain_dedication",
+      "license_notes": "Zenodo API metadata lists license id cc-zero."
+    }
+  ],
+  "release_risk_summary": {
+    "low_risk_open_licenses": [
+      "phenobench",
+      "gwhd2021",
+      "dumortier"
+    ],
+    "redistributable_with_noncommercial_or_sharealike_constraints": [
+      "minneapple",
+      "magefruits_blueberry",
+      "magefruits_peach",
+      "oam_tcd"
+    ],
+    "requires_permission_or_release_adjustment_before_public_huggingface_upload": [
+      "cropandweed",
+      "acfr",
+      "acfr_apples",
+      "ip102_detection",
+      "plantseg"
+    ]
+  }
+}

t1/annotations/final_stats.json

@@ -0,0 +1,53 @@
+{
+  "num_images": 6526,
+  "by_source": {
+    "acfr": 636,
+    "cropandweed": 632,
+    "dumortier": 471,
+    "gwhd2021": 1091,
+    "ip102_detection": 1255,
+    "minneapple": 598,
+    "oam_tcd": 104,
+    "phenobench": 528,
+    "plantseg": 1211
+  },
+  "by_scene_family": {
+    "crop_weed": 1160,
+    "forest_tree_cover": 575,
+    "fruit": 1234,
+    "pest": 1255,
+    "plant_disease": 1211,
+    "wheat_head": 1091
+  },
+  "by_split_source": {
+    "finetuning_df": 471,
+    "test": 603,
+    "test_segmentation": 242,
+    "train": 2049,
+    "unspecified": 2485,
+    "val": 676
+  },
+  "by_benchmark_split": {
+    "dev": 5238,
+    "test": 1288
+  },
+  "source_targets_realized": {
+    "acfr": 636,
+    "cropandweed": 632,
+    "dumortier": 471,
+    "gwhd2021": 1091,
+    "ip102_detection": 1255,
+    "minneapple": 598,
+    "oam_tcd": 104,
+    "phenobench": 528,
+    "plantseg": 1211
+  },
+  "family_targets_realized": {
+    "crop_weed": 1160,
+    "forest_tree_cover": 575,
+    "fruit": 1234,
+    "pest": 1255,
+    "plant_disease": 1211,
+    "wheat_head": 1091
+  }
+}

t1/annotations/policy.json

@@ -0,0 +1,8 @@
+{
+  "mode": "query_aligned_release_pool",
+  "num_images": 6526,
+  "num_queries": 6526,
+  "dev_images": 5238,
+  "test_images": 1288,
+  "note": "Records without a released RGB file or official query were removed during the public release packaging step."
+}

t1/annotations/split_stats.json

@@ -0,0 +1,73 @@
+{
+  "dev": {
+    "num_images": 5238,
+    "by_source": {
+      "acfr": 509,
+      "cropandweed": 505,
+      "dumortier": 377,
+      "gwhd2021": 889,
+      "ip102_detection": 1004,
+      "minneapple": 480,
+      "oam_tcd": 83,
+      "phenobench": 422,
+      "plantseg": 969
+    },
+    "by_scene_family": {
+      "crop_weed": 927,
+      "forest_tree_cover": 460,
+      "fruit": 989,
+      "pest": 1004,
+      "plant_disease": 969,
+      "wheat_head": 889
+    },
+    "by_split_source": {
+      "finetuning_df": 377,
+      "test": 468,
+      "test_segmentation": 126,
+      "train": 1758,
+      "unspecified": 1980,
+      "val": 529
+    }
+  },
+  "test": {
+    "num_images": 1288,
+    "by_source": {
+      "acfr": 127,
+      "cropandweed": 127,
+      "dumortier": 94,
+      "gwhd2021": 202,
+      "ip102_detection": 251,
+      "minneapple": 118,
+      "oam_tcd": 21,
+      "phenobench": 106,
+      "plantseg": 242
+    },
+    "by_scene_family": {
+      "crop_weed": 233,
+      "forest_tree_cover": 115,
+      "fruit": 245,
+      "pest": 251,
+      "plant_disease": 242,
+      "wheat_head": 202
+    },
+    "by_split_source": {
+      "finetuning_df": 94,
+      "test": 135,
+      "test_segmentation": 116,
+      "train": 291,
+      "unspecified": 505,
+      "val": 147
+    }
+  },
+  "source_dev_actual": {
+    "acfr": 509,
+    "cropandweed": 505,
+    "dumortier": 377,
+    "gwhd2021": 889,
+    "ip102_detection": 1004,
+    "minneapple": 480,
+    "oam_tcd": 83,
+    "phenobench": 422,
+    "plantseg": 969
+  }
+}

t1/queries/query_policy.json

@@ -0,0 +1,142 @@
+{
+  "task": "T1 Generalized Instance Grounding (bbox)",
+  "split_files": [
+    "dev.jsonl",
+    "test.jsonl"
+  ],
+  "query_bucket_fraction": {
+    "single": 0.5,
+    "multi_core": 0.2,
+    "multi_challenge": 0.15,
+    "empty": 0.15
+  },
+  "empty_fraction": 0.15,
+  "multi_bucket_definition": {
+    "multi_core_program_types": [
+      "multi_family_all",
+      "multi_family_topk_leftmost"
+    ],
+    "multi_challenge_program_types": "all remaining multi_* program types"
+  },
+  "scene_query_quota_policy": {
+    "single": "scene_family-level quota from single_fraction, with residual fallback when other buckets lack eligible images",
+    "multi_core": "scene_family-level quota from multi_core_fraction",
+    "multi_challenge": "scene_family-level quota from multi_challenge_fraction",
+    "empty": "scene_family-level quota from empty_fraction",
+    "image_pool_overlap": "single/multi_core/multi_challenge/empty image pools are disjoint unless later code is changed"
+  },
+  "multi_density_policy": {
+    "preferred_buckets": [
+      "2-5",
+      "6-20",
+      "21-50"
+    ],
+    "fallback_buckets": [
+      "51-100",
+      "1",
+      ">100",
+      "0"
+    ],
+    "selection_rule": "multi-core and multi-challenge images are each stratified by density bucket within each scene family"
+  },
+  "multi_target_count_range": {
+    "min": 2,
+    "max": 20
+  },
+  "multi_quality_guardrails": {
+    "max_safe_multi_all_targets": 10,
+    "max_safe_multi_side_targets": 8,
+    "min_safe_multi_box_area_ratio": 0.00025,
+    "soft_multi_box_area_ratio": 0.001,
+    "max_safe_multi_pair_iou": 0.55,
+    "soft_multi_pair_iou": 0.3,
+    "min_multi_candidate_score": 0.58
+  },
+  "topk_query_policy": {
+    "max_k": 5,
+    "leftmost_margin_fraction": 0.04,
+    "largest_ratio_margin": 1.15
+  },
+  "side_query_policy": {
+    "side_region_margin_fraction": 0.05
+  },
+  "scene_negative_preference": {
+    "crop_weed": [
+      "fruit",
+      "pest",
+      "disease",
+      "wheat_head",
+      "tree"
+    ],
+    "fruit": [
+      "pest",
+      "disease",
+      "crop",
+      "weed",
+      "wheat_head",
+      "tree"
+    ],
+    "pest": [
+      "fruit",
+      "disease",
+      "crop",
+      "weed",
+      "wheat_head",
+      "tree"
+    ],
+    "plant_disease": [
+      "fruit",
+      "pest",
+      "crop",
+      "weed",
+      "wheat_head",
+      "tree"
+    ],
+    "wheat_head": [
+      "fruit",
+      "pest",
+      "disease",
+      "crop",
+      "weed",
+      "tree"
+    ],
+    "forest_tree_cover": [
+      "fruit",
+      "pest",
+      "disease",
+      "crop",
+      "weed",
+      "wheat_head"
+    ],
+    "oil_palm_plantation": [
+      "fruit",
+      "pest",
+      "disease",
+      "crop",
+      "weed",
+      "wheat_head"
+    ]
+  },
+  "global_families": [
+    "crop",
+    "disease",
+    "fruit",
+    "pest",
+    "tree",
+    "weed",
+    "wheat_head"
+  ],
+  "seed": 42,
+  "notes": [
+    "Query quotas are computed per split at the scene_family x query_bucket level.",
+    "Single, multi-core, multi-challenge, and empty queries are assigned to disjoint image pools whenever possible.",
+    "Single queries are generated on the residual single-only pool after multi-core, multi-challenge, and empty image selection.",
+    "Multi queries are only kept when the target set size is between 2 and 20.",
+    "Multi queries with tiny targets, excessive overlap, or overly large exact target sets are filtered out.",
+    "When multiple multi templates are available, higher-quality candidates are preferred over brittle ones.",
+    "Multi-core and multi-challenge image selection are each stratified by density bucket to avoid over-concentrating on very dense scenes.",
+    "Additional VG-style multi templates include top-k leftmost, top-k largest, and left/right-side subsets.",
+    "The smallest-object single query template is disabled to avoid unstable tiny-target references.",
+    "Empty queries are generated using family-negative programs; natural-empty images are not required."
+  ]
+}

t1/queries/query_stats.json

@@ -0,0 +1,469 @@
+{
+  "dev": {
+    "num_queries": 5238,
+    "by_query_type": {
+      "empty": 798,
+      "multi": 1866,
+      "single": 2574
+    },
+    "by_query_bucket": {
+      "empty": 798,
+      "multi_challenge": 800,
+      "multi_core": 1066,
+      "single": 2574
+    },
+    "by_program_type": {
+      "empty_family_negative": 798,
+      "multi_family_all": 402,
+      "multi_family_side_left": 63,
+      "multi_family_side_right": 75,
+      "multi_family_topk_largest": 536,
+      "multi_family_topk_leftmost": 664,
+      "multi_fine_all": 58,
+      "multi_fine_side_right": 1,
+      "multi_fine_topk_largest": 55,
+      "multi_fine_topk_leftmost": 12,
+      "single_family_unique": 212,
+      "single_fine_unique": 202,
+      "single_rank_bottommost": 360,
+      "single_rank_largest": 685,
+      "single_rank_leftmost": 382,
+      "single_rank_rightmost": 338,
+      "single_rank_topmost": 371,
+      "single_relation_family": 24
+    },
+    "by_source": {
+      "acfr": 509,
+      "cropandweed": 505,
+      "dumortier": 377,
+      "gwhd2021": 889,
+      "ip102_detection": 1004,
+      "minneapple": 480,
+      "oam_tcd": 83,
+      "phenobench": 422,
+      "plantseg": 969
+    },
+    "by_scene_family": {
+      "crop_weed": 927,
+      "forest_tree_cover": 460,
+      "fruit": 989,
+      "pest": 1004,
+      "plant_disease": 969,
+      "wheat_head": 889
+    },
+    "by_scene_family_and_query_type": {
+      "crop_weed": {
+        "empty": 139,
+        "multi": 324,
+        "single": 464
+      },
+      "forest_tree_cover": {
+        "empty": 69,
+        "multi": 161,
+        "single": 230
+      },
+      "fruit": {
+        "empty": 149,
+        "multi": 348,
+        "single": 492
+      },
+      "pest": {
+        "empty": 150,
+        "multi": 352,
+        "single": 502
+      },
+      "plant_disease": {
+        "empty": 145,
+        "multi": 339,
+        "single": 485
+      },
+      "wheat_head": {
+        "empty": 146,
+        "multi": 342,
+        "single": 401
+      }
+    },
+    "by_scene_family_and_query_bucket": {
+      "crop_weed": {
+        "empty": 139,
+        "multi_challenge": 139,
+        "multi_core": 185,
+        "single": 464
+      },
+      "forest_tree_cover": {
+        "empty": 69,
+        "multi_challenge": 69,
+        "multi_core": 92,
+        "single": 230
+      },
+      "fruit": {
+        "empty": 149,
+        "multi_challenge": 149,
+        "multi_core": 199,
+        "single": 492
+      },
+      "pest": {
+        "empty": 150,
+        "multi_challenge": 151,
+        "multi_core": 201,
+        "single": 502
+      },
+      "plant_disease": {
+        "empty": 145,
+        "multi_challenge": 145,
+        "multi_core": 194,
+        "single": 485
+      },
+      "wheat_head": {
+        "empty": 146,
+        "multi_challenge": 147,
+        "multi_core": 195,
+        "single": 401
+      }
+    },
+    "query_plan": {
+      "scene_query_targets": {
+        "crop_weed": {
+          "single": 464,
+          "multi_core": 185,
+          "multi_challenge": 139,
+          "multi": 324,
+          "empty": 139
+        },
+        "forest_tree_cover": {
+          "single": 230,
+          "multi_core": 92,
+          "multi_challenge": 69,
+          "multi": 161,
+          "empty": 69
+        },
+        "fruit": {
+          "single": 492,
+          "multi_core": 199,
+          "multi_challenge": 149,
+          "multi": 348,
+          "empty": 149
+        },
+        "pest": {
+          "single": 502,
+          "multi_core": 201,
+          "multi_challenge": 151,
+          "multi": 352,
+          "empty": 150
+        },
+        "plant_disease": {
+          "single": 485,
+          "multi_core": 194,
+          "multi_challenge": 145,
+          "multi": 339,
+          "empty": 145
+        },
+        "wheat_head": {
+          "single": 401,
+          "multi_core": 195,
+          "multi_challenge": 147,
+          "multi": 342,
+          "empty": 146
+        }
+      },
+      "scene_query_realized": {
+        "crop_weed": {
+          "single": 464,
+          "multi_core": 185,
+          "multi_challenge": 139,
+          "multi": 324,
+          "empty": 139
+        },
+        "forest_tree_cover": {
+          "single": 230,
+          "multi_core": 92,
+          "multi_challenge": 69,
+          "multi": 161,
+          "empty": 69
+        },
+        "fruit": {
+          "single": 492,
+          "multi_core": 199,
+          "multi_challenge": 149,
+          "multi": 348,
+          "empty": 149
+        },
+        "pest": {
+          "single": 502,
+          "multi_core": 201,
+          "multi_challenge": 151,
+          "multi": 352,
+          "empty": 150
+        },
+        "plant_disease": {
+          "single": 485,
+          "multi_core": 194,
+          "multi_challenge": 145,
+          "multi": 339,
+          "empty": 145
+        },
+        "wheat_head": {
+          "single": 401,
+          "multi_core": 195,
+          "multi_challenge": 147,
+          "multi": 342,
+          "empty": 146
+        }
+      },
+      "multi_core_density_realized": {
+        "2-5": 384,
+        "21-50": 279,
+        "6-20": 403
+      },
+      "multi_challenge_density_realized": {
+        "2-5": 322,
+        "21-50": 216,
+        "6-20": 262
+      },
+      "multi_density_realized": {
+        "2-5": 706,
+        "21-50": 495,
+        "6-20": 665
+      },
+      "image_pool_overlap": {
+        "single_multi": 0,
+        "single_empty": 0,
+        "multi_empty": 0,
+        "multi_core_challenge": 0
+      }
+    }
+  },
+  "test": {
+    "num_queries": 1288,
+    "by_query_type": {
+      "empty": 199,
+      "multi": 468,
+      "single": 621
+    },
+    "by_query_bucket": {
+      "empty": 199,
+      "multi_challenge": 200,
+      "multi_core": 268,
+      "single": 621
+    },
+    "by_program_type": {
+      "empty_family_negative": 199,
+      "multi_family_all": 96,
+      "multi_family_side_left": 15,
+      "multi_family_side_right": 15,
+      "multi_family_topk_largest": 132,
+      "multi_family_topk_leftmost": 172,
+      "multi_fine_all": 18,
+      "multi_fine_topk_largest": 16,
+      "multi_fine_topk_leftmost": 4,
+      "single_family_unique": 43,
+      "single_fine_unique": 53,
+      "single_rank_bottommost": 90,
+      "single_rank_largest": 196,
+      "single_rank_leftmost": 73,
+      "single_rank_rightmost": 75,
+      "single_rank_topmost": 86,
+      "single_relation_family": 5
+    },
+    "by_source": {
+      "acfr": 127,
+      "cropandweed": 127,
+      "dumortier": 94,
+      "gwhd2021": 202,
+      "ip102_detection": 251,
+      "minneapple": 118,
+      "oam_tcd": 21,
+      "phenobench": 106,
+      "plantseg": 242
+    },
+    "by_scene_family": {
+      "crop_weed": 233,
+      "forest_tree_cover": 115,
+      "fruit": 245,
+      "pest": 251,
+      "plant_disease": 242,
+      "wheat_head": 202
+    },
+    "by_scene_family_and_query_type": {
+      "crop_weed": {
+        "empty": 35,
+        "multi": 82,
+        "single": 116
+      },
+      "forest_tree_cover": {
+        "empty": 17,
+        "multi": 40,
+        "single": 58
+      },
+      "fruit": {
+        "empty": 37,
+        "multi": 87,
+        "single": 121
+      },
+      "pest": {
+        "empty": 38,
+        "multi": 88,
+        "single": 125
+      },
+      "plant_disease": {
+        "empty": 36,
+        "multi": 85,
+        "single": 121
+      },
+      "wheat_head": {
+        "empty": 36,
+        "multi": 86,
+        "single": 80
+      }
+    },
+    "by_scene_family_and_query_bucket": {
+      "crop_weed": {
+        "empty": 35,
+        "multi_challenge": 35,
+        "multi_core": 47,
+        "single": 116
+      },
+      "forest_tree_cover": {
+        "empty": 17,
+        "multi_challenge": 17,
+        "multi_core": 23,
+        "single": 58
+      },
+      "fruit": {
+        "empty": 37,
+        "multi_challenge": 37,
+        "multi_core": 50,
+        "single": 121
+      },
+      "pest": {
+        "empty": 38,
+        "multi_challenge": 38,
+        "multi_core": 50,
+        "single": 125
+      },
+      "plant_disease": {
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+        "multi_challenge": 36,
+        "multi_core": 49,
+        "single": 121
+      },
+      "wheat_head": {
+        "empty": 36,
+        "multi_challenge": 37,
+        "multi_core": 49,
+        "single": 80
+      }
+    },
+    "query_plan": {
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+        "crop_weed": {
+          "single": 116,
+          "multi_core": 47,
+          "multi_challenge": 35,
+          "multi": 82,
+          "empty": 35
+        },
+        "forest_tree_cover": {
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+        },
+        "fruit": {
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+          "multi_core": 50,
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+          "empty": 37
+        },
+        "pest": {
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+          "multi_core": 50,
+          "multi_challenge": 38,
+          "multi": 88,
+          "empty": 38
+        },
+        "plant_disease": {
+          "single": 121,
+          "multi_core": 49,
+          "multi_challenge": 36,
+          "multi": 85,
+          "empty": 36
+        },
+        "wheat_head": {
+          "single": 80,
+          "multi_core": 49,
+          "multi_challenge": 37,
+          "multi": 86,
+          "empty": 36
+        }
+      },
+      "scene_query_realized": {
+        "crop_weed": {
+          "single": 116,
+          "multi_core": 47,
+          "multi_challenge": 35,
+          "multi": 82,
+          "empty": 35
+        },
+        "forest_tree_cover": {
+          "single": 58,
+          "multi_core": 23,
+          "multi_challenge": 17,
+          "multi": 40,
+          "empty": 17
+        },
+        "fruit": {
+          "single": 121,
+          "multi_core": 50,
+          "multi_challenge": 37,
+          "multi": 87,
+          "empty": 37
+        },
+        "pest": {
+          "single": 125,
+          "multi_core": 50,
+          "multi_challenge": 38,
+          "multi": 88,
+          "empty": 38
+        },
+        "plant_disease": {
+          "single": 121,
+          "multi_core": 49,
+          "multi_challenge": 36,
+          "multi": 85,
+          "empty": 36
+        },
+        "wheat_head": {
+          "single": 80,
+          "multi_core": 49,
+          "multi_challenge": 37,
+          "multi": 86,
+          "empty": 36
+        }
+      },
+      "multi_core_density_realized": {
+        "2-5": 98,
+        "21-50": 85,
+        "6-20": 85
+      },
+      "multi_challenge_density_realized": {
+        "2-5": 89,
+        "21-50": 58,
+        "6-20": 53
+      },
+      "multi_density_realized": {
+        "2-5": 187,
+        "21-50": 143,
+        "6-20": 138
+      },
+      "image_pool_overlap": {
+        "single_multi": 0,
+        "single_empty": 0,
+        "multi_empty": 0,
+        "multi_core_challenge": 0
+      }
+    }
+  }
+}

t2/annotations/dropped_ids.txt

@@ -0,0 +1,1455 @@
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+plantseg::ps_val_wheat_stripe_rust_Google_0019
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t2/annotations/final_stats.json

@@ -0,0 +1,71 @@
+{
+  "num_images": 3545,
+  "by_scene_family": {
+    "crop_weed": 1175,
+    "fruit_blueberry": 554,
+    "fruit_peach": 585,
+    "orchard_fruit": 84,
+    "plant_disease": 1147
+  },
+  "by_density_bucket": {
+    "0": 2,
+    "1": 253,
+    "2-5": 1666,
+    "21-50": 96,
+    "6-20": 1528
+  },
+  "by_benchmark_split": {
+    "dev": 2836,
+    "test": 709
+  },
+  "by_source": {
+    "acfr_apples": {
+      "num_images": 84,
+      "num_queryable_instances": 358,
+      "split_hist": {
+        "dev": 67,
+        "test": 17
+      }
+    },
+    "cropandweed": {
+      "num_images": 443,
+      "num_queryable_instances": 1965,
+      "split_hist": {
+        "dev": 354,
+        "test": 89
+      }
+    },
+    "magefruits_blueberry": {
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+      "num_queryable_instances": 4709,
+      "split_hist": {
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+        "test": 111
+      }
+    },
+    "magefruits_peach": {
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+      "num_queryable_instances": 2835,
+      "split_hist": {
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+        "test": 117
+      }
+    },
+    "phenobench": {
+      "num_images": 732,
+      "num_queryable_instances": 5314,
+      "split_hist": {
+        "dev": 586,
+        "test": 146
+      }
+    },
+    "plantseg": {
+      "num_images": 1147,
+      "num_queryable_instances": 7935,
+      "split_hist": {
+        "dev": 918,
+        "test": 229
+      }
+    }
+  }
+}

t2/annotations/policy.json

@@ -0,0 +1,9 @@
+{
+  "target_total": 0,
+  "dev_fraction": 0.8,
+  "seed": 42,
+  "review_mode": "keep_only",
+  "num_images": 3545,
+  "num_queries": 3545,
+  "note": "Public release policy; internal review-sheet paths and local transfer settings are omitted."
+}

t2/annotations/split_stats.json

@@ -0,0 +1,129 @@
+{
+  "dev": {
+    "num_images": 2836,
+    "by_scene_family": {
+      "crop_weed": 940,
+      "fruit_blueberry": 443,
+      "fruit_peach": 468,
+      "orchard_fruit": 67,
+      "plant_disease": 918
+    },
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+      "2-5": 1333,
+      "21-50": 75,
+      "6-20": 1231
+    },
+    "by_benchmark_split": {
+      "dev": 2836
+    },
+    "by_source": {
+      "acfr_apples": {
+        "num_images": 67,
+        "num_queryable_instances": 283,
+        "split_hist": {
+          "dev": 67
+        }
+      },
+      "cropandweed": {
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+        "num_queryable_instances": 1570,
+        "split_hist": {
+          "dev": 354
+        }
+      },
+      "magefruits_blueberry": {
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+        "num_queryable_instances": 3748,
+        "split_hist": {
+          "dev": 443
+        }
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+      "magefruits_peach": {
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+        "num_queryable_instances": 2280,
+        "split_hist": {
+          "dev": 468
+        }
+      },
+      "phenobench": {
+        "num_images": 586,
+        "num_queryable_instances": 4378,
+        "split_hist": {
+          "dev": 586
+        }
+      },
+      "plantseg": {
+        "num_images": 918,
+        "num_queryable_instances": 6414,
+        "split_hist": {
+          "dev": 918
+        }
+      }
+    }
+  },
+  "test": {
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+    "by_scene_family": {
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+      "fruit_blueberry": 111,
+      "fruit_peach": 117,
+      "orchard_fruit": 17,
+      "plant_disease": 229
+    },
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+    },
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+    },
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+        "num_queryable_instances": 75,
+        "split_hist": {
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+        }
+      },
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+        "num_queryable_instances": 395,
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+        "num_queryable_instances": 961,
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+        }
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+        }
+      },
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+        }
+      }
+    }
+  }
+}

t2/queries/query_policy.json

@@ -0,0 +1,40 @@
+{
+  "single_fraction": 0.5,
+  "multi_fraction": 0.35,
+  "empty_fraction": 0.15,
+  "max_multi_targets": 20,
+  "scene_negative_preferences": {
+    "crop_weed": [
+      "fruit",
+      "disease"
+    ],
+    "plant_disease": [
+      "fruit",
+      "crop",
+      "weed"
+    ],
+    "orchard_fruit": [
+      "crop",
+      "weed",
+      "disease"
+    ],
+    "fruit_blueberry": [
+      "crop",
+      "weed",
+      "disease"
+    ],
+    "fruit_peach": [
+      "crop",
+      "weed",
+      "disease"
+    ]
+  },
+  "target_family_space": [
+    "crop",
+    "weed",
+    "fruit",
+    "disease"
+  ],
+  "family_balance_rule": "within each query bucket, prefer an even spread across crop / weed / fruit / disease when candidates exist",
+  "output_answer_format": "target_instance_local_ids"
+}

t2/queries/query_stats.json

@@ -0,0 +1,100 @@
+{
+  "dev": {
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+    "num_queries": 2836,
+    "quota": {
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+      "multi": 993,
+      "empty": 425
+    },
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+    "realized": {
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+        "multi": 993,
+        "single": 1417
+      },
+      "by_scene_family": {
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+        "fruit_blueberry": 443,
+        "fruit_peach": 468,
+        "orchard_fruit": 67,
+        "plant_disease": 918
+      },
+      "by_program_type": {
+        "empty_family_absent": 426,
+        "multi_family_all": 358,
+        "multi_family_topk_largest": 329,
+        "multi_family_topk_leftmost": 306,
+        "single_family_unique": 85,
+        "single_fine_unique": 81,
+        "single_rank_bottommost": 231,
+        "single_rank_largest": 217,
+        "single_rank_leftmost": 204,
+        "single_rank_rightmost": 211,
+        "single_rank_smallest": 171,
+        "single_rank_topmost": 217
+      },
+      "by_target_family": {
+        "crop": 656,
+        "disease": 869,
+        "fruit": 904,
+        "weed": 407
+      }
+    },
+    "eligible": {
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+      "multi": 2624,
+      "empty": 2836
+    }
+  },
+  "test": {
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+    "quota": {
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+      "multi": 248,
+      "empty": 106
+    },
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+        "multi": 248,
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+      },
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+        "fruit_blueberry": 111,
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+        "orchard_fruit": 17,
+        "plant_disease": 229
+      },
+      "by_program_type": {
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+        "multi_family_all": 90,
+        "multi_family_topk_largest": 87,
+        "multi_family_topk_leftmost": 71,
+        "single_family_unique": 20,
+        "single_fine_unique": 32,
+        "single_rank_bottommost": 48,
+        "single_rank_largest": 45,
+        "single_rank_leftmost": 56,
+        "single_rank_rightmost": 55,
+        "single_rank_smallest": 59,
+        "single_rank_topmost": 40
+      },
+      "by_target_family": {
+        "crop": 161,
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+        "fruit": 233,
+        "weed": 108
+      }
+    },
+    "eligible": {
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+      "multi": 649,
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+    }
+  }
+}