datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
tomato_disease_detection
Tomato Disease Detection/Classification
A dataset containing 1026 images of diseased tomato plants. There are 417 images of Tomato Viral, 82 images of Gray Mold, and 527 images of Bacterial Wilt.Bounding boxes for the images represent the location of disease in the image.There are 10 classes:Gray Mold contains GrayMold_Fruit (0) and GrayMold_Leaf (1)Viral contains Viral_Leaf (2), Viral_Top (3), and Virus_Middle (4)Wilt contains Wilt_Base (5), Wilt_Leaf (6), Wilt_Middle (7)… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/tomato_disease_detection.tomato_leaf_disease_detection
Tomato Leaf Disease Detection
This dataset provides real-world RGB images of tomato leaves affected by various diseases, captured in agricultural field environments across multiple districts in Bangladesh. Images were collected using Canon EOS M50 cameras under natural outdoor conditions to support object detection tasks for disease identification in real farming scenarios. The dataset contains 689 images with 2,278 bounding box annotations across 7 categories.
This dataset is… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/tomato_leaf_disease_detection.leaf_disease_detection
Leaf Disease Detection Dataset
Dataset Description
This dataset is designed for few-shot learning in the context of plant disease detection, specifically targeting tea anthracnose, tea brown blight, cotton fusarium wilt, and cotton powdery mildew. The dataset is a combination of self-collected data from tea gardens in Ya'an City, Sichuan Province, China, and publicly available disease image resources from the internet. It aims to support the development and evaluation of… See the full description on the dataset page: https://huggingface.co/datasets/ttkqwe123/leaf_disease_detection.Durian-Plantation-Disease-Leaf-Rot-Detection-Image-Dataset
Durian Plantation Disease Leaf Rot Detection Image Dataset
Ensures high-quality data through multiple rounds of annotation and automated consistency checks, combined with reviews by agricultural pathology experts. The annotation team consists of 10 professionals in agriculture and computer vision. Pre-processing steps include noise reduction, size adjustments, and color normalization to enhance the model's recognition capabilities. Data is stored in JPG format, organized… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Durian-Plantation-Disease-Leaf-Rot-Detection-Image-Dataset.Agricultural-Pest-Disease-Image-Annotation-Bounding-Box-Polygon-Detection
Agricultural Pest & Disease Image Annotation (Bounding Box/Polygon Detection)
For intelligent pest and disease recognition in the agriculture and livestock industry, this dataset provides target region annotations on raw plant/disease images. Annotation results support both bounding boxes and polygon shapes, enabling models to learn object locations and fine-grained contours. It covers common pest/disease targets and supplies strong supervision for detection and segmentation… See the full description on the dataset page: https://huggingface.co/datasets/shangzx/Agricultural-Pest-Disease-Image-Annotation-Bounding-Box-Polygon-Detection.plant-disease-detectionDurian-Plantation-Disease-Leaf-Rot-Detection-Image-Dataset
Durian Plantation Disease Leaf Rot Detection Image Dataset
Ensures high-quality data through multiple rounds of annotation and automated consistency checks, combined with reviews by agricultural pathology experts. The annotation team consists of 10 professionals in agriculture and computer vision. Pre-processing steps include noise reduction, size adjustments, and color normalization to enhance the model's recognition capabilities. Data is stored in JPG format, organized… See the full description on the dataset page: https://huggingface.co/datasets/shangzx/Durian-Plantation-Disease-Leaf-Rot-Detection-Image-Dataset.cocoa-disease-detection