diff --git a/static/data/dataset_history.json b/static/data/dataset_history.json index 6e799d7..e6740b7 100644 --- a/static/data/dataset_history.json +++ b/static/data/dataset_history.json @@ -1,6 +1,6 @@ { "_readme": "Hand-maintained going forward — do not regenerate. To add a snapshot, run `python3 scripts/append_dataset_snapshot.py` (counts the live static/data/{datasets,hf_datasets}.json the same way src/lib/datasets.ts computeDatasetStats does: top-level datasets only, iNatAg-mini's images excluded) or append to `points` by hand: { period: \"\", date: \"\", datasetCount: , imageCount: }.", - "generatedAt": "2026-09-15", + "generatedAt": "2026-09-16", "annotations": [ { "atPeriod": "May 30", @@ -159,6 +159,12 @@ "date": "2026-09-15", "datasetCount": 306, "imageCount": 6766197 + }, + { + "period": "Sep 17", + "date": "2026-09-16", + "datasetCount": 313, + "imageCount": 6772953 } ] } diff --git a/static/data/hf_datasets.json b/static/data/hf_datasets.json index fd1df15..d863a8b 100644 --- a/static/data/hf_datasets.json +++ b/static/data/hf_datasets.json @@ -12891,5 +12891,263 @@ "hf_link": "https://huggingface.co/datasets/Project-AgML/horseradish_weed_detection", "examples_image_url": "/img/agml/sample_images/horseradish_weed_detection_sample.webp", "bibtex": "@article{pagadala2026evaluation,\n title={Evaluation of YOLO-based weed detection models on commercial horseradish fields in Southern Illinois},\n author={Pagadala, Abhinav and Poudel, Sandesh and Rathi, Janmejay Umakanth and Sunoj, S and Reid, John F},\n journal={Frontiers in Agronomy},\n volume={8},\n pages={1777087},\n year={2026},\n publisher={Frontiers Media SA}\n}" + }, + { + "name": "SDAU_wheat_head_detection", + "machine_learning_task": "object_detection", + "agricultural_task": "crop_detection", + "location": [ + "Science and Technology Innovation Park, Shandong, China" + ], + "lat_lon": [], + "country": "China", + "environment": "lab", + "real_or_synthetic": "synthetic", + "crop_types": [ + "wheat" + ], + "sensor_modality": "rgb", + "imaging_equipment": [ + "EOS 70D, Canon, handheld" + ], + "collection_period": "", + "platform": "handheld", + "input_data_format": "parquet", + "annotation_format": "boundingBox", + "num_images": 3030, + "classes": [ + "0" + ], + "license": "cc-by-4.0", + "documentation": "https://doi.org/10.1016/j.compag.2024.109633", + "citation": "", + "zip_size_bytes": 1787191795, + "source": "huggingface", + "hf_link": "https://huggingface.co/datasets/Project-AgML/SDAU_wheat_head_detection", + "examples_image_url": "/img/agml/sample_images/SDAU_wheat_head_detection_sample.webp" + }, + { + "name": "strawberry_avocado_ripeness_detection", + "machine_learning_task": "object_detection", + "agricultural_task": "", + "location": [ + "Mahabaleshwar, Maharashtra, India", + "Pune, Maharashtra, India" + ], + "lat_lon": [], + "country": "India", + "environment": "mixed", + "real_or_synthetic": "real", + "crop_types": [ + "strawberry", + "avocado" + ], + "sensor_modality": "rgb", + "imaging_equipment": [ + "dual 12 MP camera, f/1.6, 26 mm (wide), 1.4 µm pixel size" + ], + "collection_period": "25 days", + "platform": "handheld", + "input_data_format": "parquet", + "annotation_format": "boundingBox", + "num_images": 758, + "classes": [ + "0", + "1", + "2", + "3", + "4", + "5", + "6", + "7" + ], + "license": "cc-by-4.0", + "documentation": "https://doi.org/10.1016/j.dib.2025.111663", + "citation": "", + "zip_size_bytes": 897725384, + "source": "huggingface", + "hf_link": "https://huggingface.co/datasets/Project-AgML/strawberry_avocado_ripeness_detection", + "examples_image_url": "/img/agml/sample_images/strawberry_avocado_ripeness_detection_sample.webp" + }, + { + "name": "tomato_leaf_disease_detection", + "machine_learning_task": "object_detection", + "agricultural_task": "disease_classification", + "location": [ + "Dinajpur, Bangladesh", + "Thakurgaon, Bangladesh", + "Kushtia, Bangladesh" + ], + "lat_lon": [], + "country": "Bangladesh", + "environment": "field", + "real_or_synthetic": "real", + "crop_types": [ + "tomato" + ], + "sensor_modality": "rgb", + "imaging_equipment": [ + "Canon EOS M50" + ], + "collection_period": "", + "platform": "", + "input_data_format": "parquet", + "annotation_format": "boundingBox", + "num_images": 689, + "classes": [ + "0", + "1", + "2", + "3", + "4", + "5", + "6" + ], + "license": "cc-by-4.0", + "documentation": "https://doi.org/10.1016/j.dib.2025.111520", + "citation": "", + "zip_size_bytes": 23983248, + "source": "huggingface", + "hf_link": "https://huggingface.co/datasets/Project-AgML/tomato_leaf_disease_detection", + "examples_image_url": "/img/agml/sample_images/tomato_leaf_disease_detection_sample.webp" + }, + { + "name": "spittlebug_segmentation", + "machine_learning_task": "semantic_segmentation", + "agricultural_task": "", + "location": [ + "Valenzano, Bari, Italy" + ], + "lat_lon": [ + "41.028, 16.905" + ], + "country": "Italy", + "environment": "field", + "real_or_synthetic": "real", + "crop_types": [], + "sensor_modality": "rgb", + "imaging_equipment": [ + "Intel RealSense D435 (1280x720, handheld)", + "iPhone 11 (3024x4032, handheld)", + "Canon EOS1100D (4272x2848, handheld)" + ], + "collection_period": "April 2024, April 2025", + "platform": "handheld", + "input_data_format": "parquet", + "annotation_format": "segmentationMask", + "num_images": 347, + "classes": [], + "license": "cc-by-4.0", + "documentation": "https://doi.org/10.1016/j.dib.2026.112477", + "citation": "", + "zip_size_bytes": 787417583, + "source": "huggingface", + "hf_link": "https://huggingface.co/datasets/Project-AgML/spittlebug_segmentation", + "examples_image_url": "/img/agml/sample_images/spittlebug_segmentation_sample.webp" + }, + { + "name": "Luffa_disease_classification", + "machine_learning_task": "image_classification", + "agricultural_task": "disease_classification", + "location": [ + "Binokdia, Faridpur, Bangladesh" + ], + "lat_lon": [], + "country": "Bangladesh", + "environment": "field", + "real_or_synthetic": "real", + "crop_types": [ + "luffa" + ], + "sensor_modality": "rgb", + "imaging_equipment": [ + "VIVO V25 5G smartphone (64 MP, 8 MP, 2 MP triple camera, handheld)" + ], + "collection_period": "2nd to 23rd October 2023", + "platform": "handheld", + "input_data_format": "parquet", + "annotation_format": "classLabel", + "num_images": 1227, + "classes": [ + "Alternaria", + "Angular Spot", + "Fresh", + "Holed", + "Mosaic Virus" + ], + "license": "cc-by-4.0", + "documentation": "https://doi.org/10.1016/j.dib.2024.110149", + "citation": "", + "zip_size_bytes": 990933241, + "source": "huggingface", + "hf_link": "https://huggingface.co/datasets/Project-AgML/Luffa_disease_classification", + "examples_image_url": "/img/agml/sample_images/Luffa_disease_classification_sample.webp" + }, + { + "name": "Luffa_quality_classification", + "machine_learning_task": "image_classification", + "agricultural_task": "disease_classification", + "location": [ + "Binokdia, Faridpur, Bangladesh" + ], + "lat_lon": [], + "country": "Bangladesh", + "environment": "field", + "real_or_synthetic": "real", + "crop_types": [ + "luffa" + ], + "sensor_modality": "rgb", + "imaging_equipment": [ + "VIVO V25 5G smartphone (64 MP, 8 MP, 2 MP triple camera, handheld)" + ], + "collection_period": "2nd to 23rd October 2023", + "platform": "handheld", + "input_data_format": "parquet", + "annotation_format": "classLabel", + "num_images": 343, + "classes": [ + "Faulty", + "Fresh" + ], + "license": "cc-by-4.0", + "documentation": "https://doi.org/10.1016/j.dib.2024.110149", + "citation": "", + "zip_size_bytes": 359698062, + "source": "huggingface", + "hf_link": "https://huggingface.co/datasets/Project-AgML/Luffa_quality_classification", + "examples_image_url": "/img/agml/sample_images/Luffa_quality_classification_sample.webp" + }, + { + "name": "Luffa_flowers", + "machine_learning_task": "unlabeled", + "agricultural_task": "disease_classification", + "location": [ + "Binokdia, Faridpur, Bangladesh" + ], + "lat_lon": [], + "country": "Bangladesh", + "environment": "field", + "real_or_synthetic": "real", + "crop_types": [ + "luffa" + ], + "sensor_modality": "rgb", + "imaging_equipment": [ + "VIVO V25 5G smartphone (64 MP, 8 MP, 2 MP triple camera, handheld)" + ], + "collection_period": "2nd to 23rd October 2023", + "platform": "handheld", + "input_data_format": "parquet", + "annotation_format": "none", + "num_images": 362, + "classes": [], + "license": "cc-by-4.0", + "documentation": "https://doi.org/10.1016/j.dib.2024.110149", + "citation": "", + "zip_size_bytes": 213203225, + "source": "huggingface", + "hf_link": "https://huggingface.co/datasets/Project-AgML/Luffa_flowers", + "examples_image_url": "/img/agml/sample_images/Luffa_flowers_sample.webp" } -] \ No newline at end of file +] diff --git a/static/img/agml/sample_images/Luffa_disease_classification_sample.webp b/static/img/agml/sample_images/Luffa_disease_classification_sample.webp new file mode 100644 index 0000000..ce276f6 Binary files /dev/null and b/static/img/agml/sample_images/Luffa_disease_classification_sample.webp differ diff --git 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