README.md

metadata

title: Cell Detection Tool
emoji: 🔬
colorFrom: blue
colorTo: purple
sdk: docker
startup_duration_timeout: 5m
suggested_hardware: cpu-basic
pinned: false
license: mit

Visual Cortex - Cell Detection Tool

A Streamlit web application for automated detection and counting of circular cells in microscopy images.

Features

• Multi-channel TIFF support: Load and preview 4-channel microscopy images (up to 1GB)
• Interactive parameter tuning: Real-time adjustment of detection parameters
• Slice preview: Test settings on small image regions for fast iteration
• Advanced detection pipeline: Uses thresholding, morphological operations, and watershed segmentation
• Export results: Download annotated images and detection data as CSV

Usage

1. Upload a .tif/.tiff microscopy image
2. Preview different channels to select the best one for analysis
3. Adjust detection parameters using the settings panel
4. Test on a small slice first for quick feedback
5. Run full detection when satisfied with parameters
6. Download results (overlay image + CSV data)

Detection Parameters

• Threshold method: How to separate cells from background (percentile/otsu/sauvola)
• Cell separation: Split touching cells using watershed segmentation
• Filtering: Remove false positives based on shape and contrast
• Size constraints: Set minimum cell diameter in microns

🚀 Easy Local Setup (Recommended)

For non-technical users: See EASY_SETUP.md for one-click installation!

Quick start:

• Windows: Double-click setup_and_run.bat
• Mac/Linux: Run ./setup_and_run.sh in terminal

🔧 Manual Development Setup

pip install -r requirements.txt
streamlit run streamlit_app.py

⚡ Why Run Locally?

• No file size limits (upload 1GB+ files)
• Faster processing (uses your computer's resources)
• More reliable (no network timeouts)
• Works offline after initial setup