2 篇博文 含有标签「Computer Vision」

1. Project Overview​

Botanical Extract AI Pro is a project designed to address the challenges of background interference and high manual segmentation costs in traditional plant phenotyping analysis. By leveraging the visual understanding and generation capabilities of multimodal AI models, the system achieves zero-shot high-precision plant image background removal and segmentation. The system supports both single-image interactive processing (Web end) and large-scale batch processing (script end), providing efficient data preprocessing tools for botanical research.

Key Features:​

• Zero-Shot Segmentation: No training required, works directly with multimodal AI models
• Dual-Mode Processing: Web interface for interactive processing + Node.js script for batch processing
• Intelligent Aspect Ratio Adaptation: Automatically matches optimal image ratios for model input
• Robust Binary Stream Processing: Handles multiple input formats and sources
• Batch Pipeline: Automated processing for hundreds/thousands of images

Project Overview​

This tutorial introduces a powerful standalone Python tool for agricultural image quantification analysis. The tool provides automated detection and measurement of plant samples from images, including morphological and color metrics.