An AI-powered agricultural CV research framework automating the full pipeline from literature discovery to paper drafting, optimized for Codex, Claude Code and Cursor workflows.
This repository also configures its own agents. See what Agri-CV-Research tells them →
Skill Claude CodeCodex
Automated research framework for agricultural computer vision. Input a research direction and the system automatically completes literature search, hypothesis generation, experiment execution, result analysis, and paper writing.
Skill Claude CodeCodex
Comprehensive evaluation framework for agricultural computer vision covering standard metrics, robustness testing, edge device benchmarking, and ablation experiment automation.
Skill Claude CodeCodex
Automatic generation of publication-quality figures commonly used in agricultural CV papers: Grad-CAM heatmaps, confusion matrices, detection result displays, training curves, and radar comparison charts.
Skill Claude CodeCodex needs its repo
Unified loading, preprocessing, and augmentation for agricultural computer vision datasets. Supports automatic download from Kaggle, HuggingFace Hub, and GitHub releases; deterministic train/val/test splitting; domain-specific augmentation presets; and cross-dataset label alignment for domain-adaptation experiments.
Skill Claude CodeCodex
LaTeX template management and automatic filling for agricultural CV papers, supporting CVPR, ECCV, Plant Phenomics, Computers and Electronics in Agriculture, and other venues.
Skill Claude CodeCodex
End-to-end crop disease detection skill supporting classification (which disease), detection (where is the disease), and segmentation (disease region) at three granularity levels, with multiple SOTA models and training strategies built in.
Skill Claude CodeCodex
Fruit detection, instance segmentation, and yield estimation skill for orchard management, supporting apple, citrus, and other fruit counting using YOLO and SAM combined approaches.
Skill Claude CodeCodex
Weed identification and site-specific weed management skill for precision agriculture, supporting detection, classification, and localization of weed species in field conditions.
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: