The open-source agricultural disease detection model Dhenu-vision-lora-0.1 accurately identifies diseases in rice, corn, and wheat and provides prevention and control suggestions.

Dhenu Vision Lora 0.1

Developed by KissanAI

An agricultural disease detection model fine-tuned based on Qwen-VL-chat, specializing in disease identification and treatment recommendations for three major crops: rice, corn, and wheat.

Text-to-Image

Transformers

EnglishOpen Source License:Apache-2.0 #Agricultural disease detection #Multi-crop recognition #Conversational diagnosis

Downloads 96

Release Time : 3/14/2024

Model Overview

Dhenu Vision LoRA v0.1 is an open-source agricultural disease detection model that assists in identifying crop diseases and providing treatment solutions through conversational interaction. Developed by KissanAI, it embodies the symbolism of the Indian divine cow Kamadhenu, aiming to offer precise guidance to agricultural communities.

Model Features

Agricultural specialization

Optimized specifically for diseases affecting three major crops (corn, rice, wheat)

Cost-effective LoRA technology

Utilizes Low-Rank Adaptation for efficient fine-tuning with 2x performance improvement

Multi-disease recognition

Supports detection and diagnosis of 9 common crop diseases

Conversational interaction

Provides disease identification and treatment advice through natural dialogue

Model Capabilities

Crop disease identification

Symptom analysis

Treatment recommendations

Prevention methods

Disease severity assessment

Use Cases

Agricultural technical support

Field disease diagnosis

Farmers obtain instant disease diagnosis by photographing crop leaves

Accurately identifies 9 common diseases

Treatment plan recommendation

Provides customized treatment and prevention suggestions based on disease type

Helps reduce crop losses

Agricultural education

Agricultural knowledge dissemination

Serves as an educational tool to help farmers learn about crop diseases

🚀 Dhenu Vision LoRA 0.1

Inspired by the mythical Kaamdhenu, the wish - fulfilling cow of Hindu mythology, KissanAI is introducing the "Dhenu" series of finetuned Language Learning Models (LLM) for the agricultural sector. These models blend agricultural practices with modern AI, providing actionable insights to farmers. They represent the fusion of tradition and technology, offering precise guidance for navigating the complexities of agriculture.

🚀 Quick Start

Dhenu-vision-lora-v0.1 is an open - source agricultural disease detection model. It's fine - tuned on the Qwen - VL - chat model and designed to help detect diseases in rice, maize, and wheat through conversations. Low Rank adaptation techniques are used for low - cost fine - tuning on agricultural datasets.

✨ Features

Specifically designed for conversational disease detection in three major crops: rice, maize, and wheat.
Utilizes Low Rank adaptation for cost - effective fine - tuning.
Performs 2X better than the base model for specific disease - related objectives.

📦 Installation

No installation steps are provided in the original README, so this section is skipped.

💻 Usage Examples

No code examples are provided in the original README, so this section is skipped.

📚 Documentation

Model details

Property	Details
Model Type	Base LLM: "Qwen/Qwen - VL - Chat", Method: LoRA
Model Date	Trained in 03 - 2024
Resources for more information	[https://huggingface.co/Qwen/Qwen - VL - Chat](https://huggingface.co/Qwen/Qwen - VL - Chat), [https://github.com/QwenLM/Qwen - VL](https://github.com/QwenLM/Qwen - VL)

Dataset

A synthetic dataset of ~9000 images for three major crops (Maize, Rice, and Wheat) is used. It includes images for the following common diseases identifiable from leaves:

Leaf blight
Leaf spot
Streak virus
Bacterial blight
Blast
Tungro
Crown and Root Rot
Leaf rust
Wheat loose smut

The dataset is used for the following objectives:

Disease identification
Symptoms
Cure
Prevention methods
Severity

Evaluation

For a collection of 500 images evaluated using multiple prompt - based approaches, the following results were achieved:

Qwen - VL - chat: 17.95%
Dhenu - vision - lora - 0.1: 36.13%
GPT4 - V: 51.59%

🔧 Technical Details

No specific technical details (more than 50 - word description) are provided in the original README, so this section is skipped.

📄 License

This model uses the [Qwen - VL - chat](https://huggingface.co/Qwen/Qwen - VL - Chat/blob/main/LICENSE) license.

ToDo

[ ] SFT model
[ ] 15+ crops and 80 diseases

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