Plant phenotyping with image analysis
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Updated
Oct 23, 2026 - Python
Plant phenotyping with image analysis
A computer vision and deep learning pipeline for plant disease classification. Features custom image augmentation, leaf segmentation (PlantCV/OpenCV), and an optimized Mini-ResNet architecture designed for efficient CPU training.
PyTorch CNN model to detect leaves disease
Image processing and computer vision pipeline that applies automated transformations and CNN training to plant leaf photos to support disease-classification.
Plant disease image classification using a convolutional neural network - 42
This repository contains a plantcv workflow tool for performing automatic image-based phenotyping on blueberry samples.
👁️ Computer Vision model made with Convolutional Neural Network for leaf disease identification
An innovative computer vision project utilizing leaf image analysis for disease recognition.
plantcv extension for the image-dataset-converter library.
Leaf-disease classification: dataset balancing, OpenCV feature transforms and a fine-tuned ConvNeXt (PyTorch, timm), 8 classes
MCP server exposing PlantCV as a measurement instrument — plant traits plus the segmentation overlay they were measured from
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