SoilSight GUI: Microplastic Morphometric Analysis Tool

📖 Overview

SoilSight is a desktop application that automates detection and morphometric analysis of microplastic particles from microscopy images and live camera feeds. It reduces manual annotation effort by combining instance segmentation models (PyTorch) with a PyQt6-based GUI and optional cloud integrations (Roboflow, Directus).

This repository contains the GUI, local model artifacts, inference helpers, and service connectors used for data export and remote model hosting.

✨ Key Features

• Instance Segmentation: Detects particles and displays segmentation masks and confidence scores.
• Morphometrics: Computes area, perimeter, equivalent circular diameter, aspect ratio, circularity, skeleton length, and other shape metrics.
• Color Analysis: Extracts color composition for each detected particle.
• Live & Batch Processing: Works with live camera feeds (microscope cameras) and static image batches.
• Services Integration: Supports Directus for record storage and Roboflow for remote inference/annotations via services/ connectors.
• Extensible UI: Separate pages for Camera, Farm (project management), and Samples.

Quickstart

Prerequisites:

• Python 3.10 or newer (project uses a venv by default).
• A GPU is recommended for local inference with PyTorch, but CPU will work for smaller images or testing.

Basic setup (PowerShell example):

python -m venv .venv311
.\.venv311\Scripts\Activate.ps1
pip install -r requirements.txt
python main.py

Running the app will open the Qt GUI. The main entry point is main.py and navigation is handled by ui_nav.py.

Usage / UI Overview

• Camera page: start/stop live capture, run real-time inference, save snapshots.
• Farm page: manage projects, metadata, and batch operations.
• Samples page: review saved images, re-run inference, export results.

UI files are located in layouts/ and controllers are in mpcamera/controllers/ (e.g. camera_page.py, farm_page.py, samples_page.py).

Prediction debugging output can be found in prediction_debug.txt (root and mpcamera/).

Models

Local model weights are stored in the models/ folder. Examples:

• optimized-maskrcnn-resnet50.pth
• PH-optimized-maskrcnn-resnet101.pth

To use a local model, set the appropriate model path in the app settings or update utils/local_models_utils.py / utils/inference_utils.py as needed. The app also includes support for Roboflow-hosted models via services/roboflow.py.

Architecture (high level)

GUI (PyQt6) -> Inference layer (PyTorch models + utils/inference_utils.py) -> Morphometrics utilities (utils/morphometrics/*) -> Services (services/directus.py, services/roboflow.py) for export and remote inference.

Code Organization

• main.py — application entry point
• ui_nav.py — navigation and startup logic
• mpcamera/ — package with controllers, UI helpers, and assets
• layouts/ — Qt Designer .ui files
• models/ — model weights and artifacts
• services/ — external integrations (Directus, Roboflow)
• utils/ — image processing, inference helpers, and morphometric calculators