Environment

Agriculture

Plant leaf disease identification

Image classification on high-performance MCU. MobileNet 0.25 model from STM32 model zoo.

Plant leaf disease identification
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Environment

Agriculture

STM32Cube.AI

Image classification

Vision

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Plant leaf disease identification is crucial for agriculture helping to prevent the spread of diseases, which can have a significant impact on crop yields and food security. Identifying the specific disease allows farmers to take appropriate measures to control or eradicate the disease, such as applying the correct pesticides only on targeted plants or implementing quarantine measures.

Approach

The STM32 model zoo provides everything you need to train and retrain models with your own data
The solution proposes a model trained on a public dataset providing very good accuracy while running on a STM32
The model can be easily deployed on the STM32H747 discovery kit with the STM32 model zoo Python scripts
The use case presented is based on a plant leaf dataset to identify diseases

Sensor

Vision: Camera module bundle (reference: B-CAMS-OMV)

Data

Dataset Plant Village dataset of plant leaf (License CC0 1.0 Public Domain)
Data format
39 different classes of plant leaf and background images
RGB color images 

Results

Model Fast-downsampling MobileNet 0.25 
Input size: 224x224x3
Memory footprint:
137 KB Flash for weights
152 KBRAM for activations
Accuracy:
Float model: 99.82%
Quantized model: 99.62% 
Performance on STM32H747 (High-perf) @ 400 MHz 
Inference time: 63.2 ms
Frame rate: 16 fps
Confusion matrix 

Model repository

STM32 model zoo

Model repository

Optimized with

STM32Cube.AI

Optimized with

Compatible with

STM32H7 series

Compatible with

Resources

Model repository STM32 model zoo

A collection of reference AI models optimized to run on ST devices with associated deployment scripts. The model zoo is a valuable resource to add edge AI capabilities to embedded applications.

Model repository STM32 model zoo

Optimized with STM32Cube.AI

A free STM32Cube expansion package, X-CUBE-AI allows developers to convert pretrained AI algorithms automatically, such as neural network and machine learning models, into optimized C code for STM32.

Optimized with STM32Cube.AI

Compatible with STM32H7 series

The STM32 family of 32-bit microcontrollers based on the Arm Cortex®-M processor is designed to offer new degrees of freedom to MCU users. It offers products combining very high performance, real-time capabilities, digital signal processing, low-power / low-voltage operation, and connectivity, while maintaining full integration and ease of development.

Compatible with STM32H7 series

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