diff --git a/static/data/hf_datasets.json b/static/data/hf_datasets.json index 80d4eb7..eb44809 100644 --- a/static/data/hf_datasets.json +++ b/static/data/hf_datasets.json @@ -26358,6 +26358,329 @@ "hf_link": "https://huggingface.co/datasets/Project-AgML/uci_rice_leaf_diseases_classification", "examples_image_url": "/img/agml/sample_images/uci_rice_leaf_diseases_classification_sample.webp" }, + { + "name": "PlantTom_tomato_disease_detection", + "machine_learning_task": "object_detection", + "agricultural_task": "disease_detection", + "location": [], + "lat_lon": [], + "country": "", + "environment": "mixed", + "real_or_synthetic": "real", + "crop_types": [ + "tomato" + ], + "sensor_modality": "rgb", + "imaging_equipment": [], + "collection_period": "", + "platform": "", + "input_data_format": "external", + "annotation_format": "boundingBox", + "classes": [ + "Bacterial Spot", + "Early Blight", + "Late Blight", + "Leaf Mold", + "Mosaic Virus", + "Septoria", + "Spider Mites", + "Yellow Leaf Curl Virus" + ], + "license": "cc-by-4.0", + "documentation": "https://doi.org/10.1371/journal.pone.0349501", + "citation": "", + "bibtex": "@article{mostafa2026leafdet,\n title={LeafDet: A lightweight and interpretable deep learning framework for tomato leaf disease detection},\n author={Mostafa, Vaskor and Sozol, Md. Shafak Shahriar and Mondal, M. Rubaiyat Hossain},\n journal={PLOS ONE},\n volume={21},\n number={5},\n pages={e0349501},\n year={2026},\n publisher={Public Library of Science}\n}", + "data_size_bytes": 523202869, + "num_files": 3, + "num_images": 7836, + "source": "doi", + "data_link": "https://huggingface.co/datasets/vaskormostafa/PlantTom", + "examples_image_url": "", + "hosted_in_original_form": true + }, + { + "name": "zijinshan_vegetation_segmentation", + "machine_learning_task": "semantic_segmentation", + "agricultural_task": "land_use_segmentation", + "location": [ + "Zijinshan Scenic Area and surrounding urban-rural interface, Nanjing, Jiangsu Province, China" + ], + "lat_lon": [], + "country": "China", + "environment": "field", + "real_or_synthetic": "real", + "crop_types": [], + "sensor_modality": "rgb", + "imaging_equipment": [], + "collection_period": "2022-10-10, 2023-11-17, 2024-05-17", + "platform": "satellite", + "input_data_format": "external", + "annotation_format": "segmentationMask", + "classes": [ + "background", + "vegetation" + ], + "license": "cc-by-nc-4.0", + "documentation": "https://doi.org/10.3390/rs18152487", + "citation": "", + "bibtex": "@article{hu2026comparative,\n title={Comparative Performance Analysis of Mainstream Deep Learning and Vision Foundation Models for Small-Sample Vegetation Segmentation in High-Resolution Remote Sensing Imagery},\n author={Hu, Le and Zhang, Fuquan},\n journal={Remote Sensing},\n volume={18},\n number={15},\n pages={2487},\n year={2026},\n publisher={MDPI}\n}", + "data_size_bytes": 300731017, + "num_files": 1085, + "num_images": 201, + "source": "doi", + "data_link": "https://huggingface.co/datasets/ledemo/zijinshan-vegetation-segmentation", + "examples_image_url": "", + "hosted_in_original_form": true + }, + { + "name": "malabar_spinach_leaf_disease_classification", + "machine_learning_task": "image_classification", + "agricultural_task": "disease_classification", + "location": [ + "Habiganj Agricultural University, Habiganj, Bangladesh", + "Daffodil International University, Dhaka, Bangladesh" + ], + "lat_lon": [], + "country": "Bangladesh", + "environment": "", + "real_or_synthetic": "real", + "crop_types": [ + "malabar spinach" + ], + "sensor_modality": "rgb", + "imaging_equipment": [], + "collection_period": "", + "platform": "", + "input_data_format": "external", + "annotation_format": "classLabel", + "classes": [ + "Alternaria", + "Healthy Leaf", + "straw_mite" + ], + "license": "apache-2.0", + "documentation": "https://doi.org/10.1371/journal.pone.0340989", + "citation": "", + "bibtex": "@article{kabya2026towards,\n title={Towards practical AI for agriculture: A self-supervised attention framework for Spinach leaf disease detection},\n author={Kabya, Nilavro Das and Sharafat, MD Shaifullah and Emu, Rahimul Islam and Opee, Mehrab Karim and Khan, Riasat},\n journal={PLOS ONE},\n volume={21},\n number={1},\n pages={e0340989},\n year={2026},\n publisher={Public Library of Science}\n}", + "data_size_bytes": 6049522883, + "num_files": 4, + "num_images": 3435, + "source": "doi", + "data_link": "https://huggingface.co/datasets/saifullah03/malabar_spinach_leaf_disease_dataset", + "examples_image_url": "", + "hosted_in_original_form": true + }, + { + "name": "DigitalGreen_crop_disease_classification", + "machine_learning_task": "image_classification", + "agricultural_task": "disease_classification", + "location": [ + "Bihar, India", + "Andhra Pradesh, India", + "Telangana, India", + "Jharkhand, India", + "Odisha, India", + "Uttar Pradesh, India", + "Karnataka, India", + "Addis Ababa, Ethiopia", + "Gujarat, India", + "Haryana, India", + "Kerala, India", + "Madhya Pradesh, India", + "Maharashtra, India", + "Rajasthan, India", + "West Bengal, India" + ], + "lat_lon": [], + "country": "India", + "environment": "field", + "real_or_synthetic": "real", + "crop_types": [ + "aparajita", + "arhar", + "banana", + "barley", + "bean", + "bhindi", + "bitter gourd", + "bottle gourd", + "brinjal", + "broad bean", + "cabbage", + "canola", + "capsicum", + "carrot", + "cauliflower", + "chickpea", + "chikoo", + "chili", + "chilli", + "citrus", + "coriander", + "cotton", + "cowpea", + "crossandra", + "cucumber", + "curry leaf", + "custard apple", + "fruit trees", + "garlic", + "gram", + "green gram", + "groundnut", + "guava", + "gum", + "jamun", + "kidney bean", + "lemon", + "lemongrass", + "maize", + "mango", + "marigold", + "medicinal plants", + "moong", + "moringa", + "mustard", + "okra", + "onion", + "paddy", + "papaya", + "pea", + "pearl millet", + "peas", + "pepper", + "pigeon pea", + "pomegranate", + "potato", + "pumpkin", + "radish", + "rahi", + "red gram", + "rice", + "ridge gourd", + "rose", + "sorghum", + "soybean", + "spinach", + "sponge gourd", + "squash", + "strawberry", + "tobacco", + "tomato", + "turmeric", + "watermelon", + "wheat" + ], + "sensor_modality": "rgb", + "imaging_equipment": [ + "farmer smartphones" + ], + "collection_period": "2024-12-02 to 2025-03-30", + "platform": "handheld", + "input_data_format": "external", + "annotation_format": "classLabel", + "classes": [ + "Alternaria Blight", + "Anthracnose", + "Aphids", + "Armyworm", + "Ascochyta Blight", + "Bacterial Blight", + "Bacterial Canker", + "Bacterial Wilt", + "Banana Aphid", + "Banana Weevil", + "Banded Leaf and Sheath Blight", + "Bark Eating Caterpillar", + "Bean Beetle", + "Black Rot", + "Blast", + "Bollworm", + "Boron Deficiency", + "Botrytis Gray Mold", + "Brown Spot", + "Cabbage Looper", + "Calcium Deficiency", + "Cercospora Leaf Spot", + "Citrus Canker", + "Citrus Psyllid", + "Collar Rot", + "Common Scab", + "Cucumber Beetle", + "Cutworms", + "Diamondback Moth", + "Downy Mildew", + "Dry Root Rot", + "Early Blight", + "Fall Armyworm", + "Fruit Borer", + "Fruit Fly", + "Fusarium Wilt", + "Grain Mold", + "Healthy", + "Jassids", + "Late Blight", + "Leaf Curl Virus", + "Leaf Hopper", + "Leaf Miner", + "Leaf Spot", + "Loose Smut", + "Magnesium Deficiency", + "Mango Hopper", + "Mealybugs", + "Melanose", + "Mites", + "Mosaic Virus", + "Nitrogen Deficiency", + "Onion Maggot", + "Panama Wilt", + "Papaya Mealybug", + "Papaya Ring Spot Virus", + "Phomopsis Blight", + "Phosphorus Deficiency", + "Phytophthora Blight", + "Pod Borer", + "Potassium Deficiency", + "Potato Tuber Moth", + "Powdery Mildew", + "Purple Blotch", + "Red Pumpkin Beetle", + "Rice Bug", + "Root Rot", + "Rust", + "Scab", + "Scale Insects", + "Sheath Blight", + "Shoot and Fruit Borer", + "Sigatoka Leaf Spot", + "Smut", + "Sooty Mold", + "Spider Mites", + "Squash Bug", + "Stem Borer", + "Stemphylium Blight", + "Sterility Mosaic", + "Stripe Rust", + "Thrips", + "Tobacco Caterpillar", + "Tobacco Mosaic Virus", + "Turcicum Leaf Blight", + "White Rust", + "Whiteflies", + "Wilt" + ], + "license": "cc-by-4.0", + "documentation": "https://huggingface.co/datasets/DigiGreen/Crop_Disease_Images", + "citation": "Digital Green. (2026). Crop Disease Expert Annotations [Dataset]. Hugging Face. https://huggingface.co/datasets/DigiGreen/Crop_Disease_Images", + "bibtex": "@dataset{digigreen_crop_disease_2026,\n title={Crop Disease Expert Annotations},\n author={Digital Green},\n year={2026},\n url={https://huggingface.co/datasets/DigiGreen/Crop_Disease_Images},\n license={CC-BY-4.0}\n}", + "data_size_bytes": 183107473, + "num_files": 993, + "num_images": 989, + "source": "doi", + "data_link": "https://huggingface.co/datasets/DigiGreen/Crop_Disease_Images", + "examples_image_url": "", + "hosted_in_original_form": true + }, { "name": "image_safari_minor_sites", "machine_learning_task": "unlabeled",