Greenhouse Tomato Environment Monitoring Dataset

The current agricultural industry faces challenges of global climate change and frequent crop pests and diseases. Traditional manual monitoring methods are inefficient and costly. Existing solutions often lack real-time capabilities and precision, failing to effectively meet modern agriculture's need for data-driven decision-making. This dataset aims to solve object detection issues in crop health monitoring by providing high-quality greenhouse tomato environment monitoring images, thus enhancing the intelligence level of agricultural production. Data collection is carried out using high-resolution cameras within greenhouses, covering tomatoes at different growth stages and under various environmental conditions. To ensure data quality, we implemented multiple rounds of annotation and consistency checks, with all annotations reviewed by agricultural experts. The data storage format is JPEG, organized by folder structure for easy processing and use.