HaiPenglai/Succulent-Vision-Dataset

Succulent Vision Dataset

Introduction

This dataset contains 1,000+ high-quality segmented images of succulents. The original photos were taken in complex cluster environments, and individual succulent plants were precisely segmented using SAM (Segment Anything Model).

Processing Pipeline

To provide structured data, the images have been automatically categorized using an advanced unsupervised pipeline:

• Feature Extraction: DINOv2 (Vision Transformer) for semantic shape features.
• Color Analysis: HSV Histogram analysis to prioritize botanical color variations.
• Dimensionality Reduction: UMAP for manifold learning.
• Clustering: Agglomerative Hierarchical Clustering to ensure morphological consistency.

Dataset Structure

The dataset is organized into folders representing different species/morphological groups:

• class_000/: Echeveria-like structures (green)
• class_001/: Cabbage-like wrinkled leaves
• ... and more.

Usage

Perfect for:

• Training Conditional DDPM or GANs for plant generation.
• Fine-tuning image classification models for botany.
• Testing unsupervised clustering algorithms.

Maintained by: HaiPenglai