toolambr/crops_weeds

--- license: mit task_categories: - object-detection --- This dataset was derived from the "CropWeeds-YOLO Dataset" distributed on Kaggle by Swayam Patil: https://www.kaggle.com/datasets/swish9/weeds-detection. To reduce the dataset size, we randomly filtered out 50% of the data in the train/val/test splits. This is the information provided on the dataset on Kaggle: Dataset Description: This dataset is curated for fine-tuning YOLO models specifically for weeds and crop detection. It includes over 2,000 annotated images organized into train, test, and validation directories, formatted for seamless integration with YOLO training pipelines. The dataset covers various agricultural scenarios to enhance model robustness and accuracy in detecting both weeds and specific crop types. Key Features: 2,000+ annotated images Organized into train, test, and validation sets Annotated for weeds and crop types Suitable for YOLO fine-tuning Usage: Ideal for researchers and developers working on precision agriculture and AI-driven crop monitoring applications. Format: Images and annotations are provided in YOLO-compatible format, facilitating easy integration into training workflows.