Fix pixel-to-micron conversion for slice preview - now uses correct physical dimensions

EASY_SETUP.md

@@ -0,0 +1,78 @@
+# 🔬 Cell Detection Tool - Easy Setup Guide
+
+This guide will help you run the Cell Detection Tool on your computer in just a few clicks!
+
+## 📋 What You Need
+
+1. **A computer** (Windows, Mac, or Linux)
+2. **Internet connection** (for initial setup only)
+3. **Your TIFF microscopy files**
+
+## 🚀 Quick Start (3 Steps!)
+
+### Step 1: Download the Code
+1. Click the green "Code" button on this page
+2. Select "Download ZIP"
+3. Extract the ZIP file to your desktop or Documents folder
+
+### Step 2: Run the Setup Script
+
+#### On Windows:
+- Double-click `setup_and_run.bat`
+- If Windows asks about running the file, click "Yes" or "Run anyway"
+
+#### On Mac:
+- Open Terminal (press Cmd+Space, type "Terminal", press Enter)
+- Type: `cd ` (with a space), then drag the downloaded folder into Terminal
+- Press Enter, then type: `./setup_and_run.sh`
+- Press Enter
+
+#### On Linux:
+- Open Terminal
+- Navigate to the downloaded folder: `cd /path/to/cell-detection-tool`
+- Run: `./setup_and_run.sh`
+
+### Step 3: Use the App!
+- Your web browser will automatically open to `http://localhost:8501`
+- Upload your TIFF files and start detecting cells!
+- **No file size limits** when running locally! 🎉
+
+## 🔧 Troubleshooting
+
+### "Python not found" Error
+**Windows:**
+1. Download Python from https://python.org/downloads/
+2. **IMPORTANT:** Check "Add Python to PATH" during installation
+3. Restart your computer and try again
+
+**Mac:**
+1. Install Homebrew: `/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"`
+2. Install Python: `brew install python3`
+
+**Linux (Ubuntu/Debian):**
+```bash
+sudo apt update
+sudo apt install python3 python3-pip python3-venv
+```
+
+### Still Having Issues?
+1. Make sure you have an internet connection
+2. Try running the setup script again
+3. On Windows, try "Run as Administrator"
+
+## 💡 Features
+
+✅ **No file size limits** (upload 1GB+ files!)  
+✅ **Fast processing** (runs on your computer)  
+✅ **Interactive parameter tuning**  
+✅ **Slice preview** for quick testing  
+✅ **Export results** (images + CSV data)  
+✅ **Works offline** after initial setup  
+
+## 🛑 To Stop the App
+
+Press `Ctrl+C` in the terminal/command window where the app is running.
+
+---
+
+**Need help?** The setup script will guide you through any issues and provide helpful error messages!

README.md

@@ -38,9 +38,24 @@ A Streamlit web application for automated detection and counting of circular cel
 - **Filtering**: Remove false positives based on shape and contrast
 - **Size constraints**: Set minimum cell diameter in microns
 
-## Local Development
+## 🚀 Easy Local Setup (Recommended)
+
+**For non-technical users:** See [EASY_SETUP.md](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
 
 ```bash
 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

setup_and_run.bat

@@ -0,0 +1,69 @@
+@echo off
+echo ====================================
+echo Cell Detection Tool - Easy Setup
+echo ====================================
+echo.
+
+:: Check if Python is installed
+python --version >nul 2>&1
+if %errorlevel% neq 0 (
+    echo ERROR: Python is not installed or not in PATH
+    echo Please install Python 3.8+ from https://python.org
+    echo Make sure to check "Add Python to PATH" during installation
+    pause
+    exit /b 1
+)
+
+echo ✅ Python found
+echo.
+
+:: Check if virtual environment exists
+if not exist "venv" (
+    echo 🔧 Creating virtual environment...
+    python -m venv venv
+    if %errorlevel% neq 0 (
+        echo ERROR: Failed to create virtual environment
+        pause
+        exit /b 1
+    )
+    echo ✅ Virtual environment created
+) else (
+    echo ✅ Virtual environment already exists
+)
+
+echo.
+echo 🔧 Activating virtual environment and installing dependencies...
+
+:: Activate virtual environment and install packages
+call venv\Scripts\activate.bat
+if %errorlevel% neq 0 (
+    echo ERROR: Failed to activate virtual environment
+    pause
+    exit /b 1
+)
+
+:: Upgrade pip first
+python -m pip install --upgrade pip >nul 2>&1
+
+:: Install requirements
+echo Installing required packages... (this may take a few minutes)
+pip install -r requirements.txt
+if %errorlevel% neq 0 (
+    echo ERROR: Failed to install requirements
+    echo Make sure you have an internet connection
+    pause
+    exit /b 1
+)
+
+echo.
+echo ✅ All dependencies installed successfully!
+echo.
+echo 🚀 Starting Cell Detection Tool...
+echo The app will open in your web browser at http://localhost:8501
+echo.
+echo Press Ctrl+C to stop the application
+echo.
+
+:: Run the Streamlit app
+streamlit run streamlit_app.py --server.port=8501
+pause

setup_and_run.sh

@@ -0,0 +1,81 @@
+#!/bin/bash
+
+echo "===================================="
+echo "Cell Detection Tool - Easy Setup"
+echo "===================================="
+echo ""
+
+# Colors for better output
+RED='\033[0;31m'
+GREEN='\033[0;32m'
+BLUE='\033[0;34m'
+YELLOW='\033[1;33m'
+NC='\033[0m' # No Color
+
+# Check if Python is installed
+if ! command -v python3 &> /dev/null; then
+    if ! command -v python &> /dev/null; then
+        echo -e "${RED}ERROR: Python is not installed${NC}"
+        echo "Please install Python 3.8+ from:"
+        echo "  - macOS: brew install python3 or download from python.org"
+        echo "  - Ubuntu/Debian: sudo apt update && sudo apt install python3 python3-pip python3-venv"
+        echo "  - Other Linux: Use your package manager"
+        exit 1
+    else
+        PYTHON_CMD="python"
+    fi
+else
+    PYTHON_CMD="python3"
+fi
+
+echo -e "${GREEN}✅ Python found${NC}"
+echo ""
+
+# Check if virtual environment exists
+if [ ! -d "venv" ]; then
+    echo -e "${BLUE}🔧 Creating virtual environment...${NC}"
+    $PYTHON_CMD -m venv venv
+    if [ $? -ne 0 ]; then
+        echo -e "${RED}ERROR: Failed to create virtual environment${NC}"
+        echo "You may need to install python3-venv:"
+        echo "  Ubuntu/Debian: sudo apt install python3-venv"
+        exit 1
+    fi
+    echo -e "${GREEN}✅ Virtual environment created${NC}"
+else
+    echo -e "${GREEN}✅ Virtual environment already exists${NC}"
+fi
+
+echo ""
+echo -e "${BLUE}🔧 Activating virtual environment and installing dependencies...${NC}"
+
+# Activate virtual environment
+source venv/bin/activate
+if [ $? -ne 0 ]; then
+    echo -e "${RED}ERROR: Failed to activate virtual environment${NC}"
+    exit 1
+fi
+
+# Upgrade pip first
+pip install --upgrade pip > /dev/null 2>&1
+
+# Install requirements
+echo "Installing required packages... (this may take a few minutes)"
+pip install -r requirements.txt
+if [ $? -ne 0 ]; then
+    echo -e "${RED}ERROR: Failed to install requirements${NC}"
+    echo "Make sure you have an internet connection"
+    exit 1
+fi
+
+echo ""
+echo -e "${GREEN}✅ All dependencies installed successfully!${NC}"
+echo ""
+echo -e "${YELLOW}🚀 Starting Cell Detection Tool...${NC}"
+echo "The app will open in your web browser at http://localhost:8501"
+echo ""
+echo -e "${YELLOW}Press Ctrl+C to stop the application${NC}"
+echo ""
+
+# Run the Streamlit app
+streamlit run streamlit_app.py --server.port=8501

streamlit_app.py

@@ -352,6 +352,9 @@ if uploaded is not None:
             current_path = paths.get(sel or "", None)
             if current_path:
                 pil_img = Image.open(current_path).convert("L")
+                # Get original image dimensions for physical scaling calculation
+                orig_h, orig_w = pil_img.size[1], pil_img.size[0]  # PIL uses (W, H) format
+                
                 slice_img = st_cropper(pil_img, aspect_ratio=None, box_color="#00FF00")
                 snp = np.array(slice_img)
                 h, w = snp.shape[:2]
@@ -360,14 +363,32 @@ if uploaded is not None:
                         "Selected slice is too small. Increase selection to at least 100×100."
                     )
                 else:
+                    # Calculate slice physical dimensions based on the crop ratio
+                    # Get settings for original physical dimensions
+                    s = st.session_state.get("_settings", {})
+                    orig_width_um = s.get("width_um", 1705.6)
+                    orig_height_um = s.get("height_um", 1706.81)
+                    
+                    # Calculate slice physical dimensions proportionally
+                    slice_width_um = orig_width_um * (w / orig_w)
+                    slice_height_um = orig_height_um * (h / orig_h)
+                    
                     if max(h, w) > 1024:
                         scale = max(h, w) / 1024.0
                         new_h, new_w = int(h / scale), int(w / scale)
                         snp = resize(snp, (new_h, new_w), preserve_range=True).astype(
                             np.uint8
                         )
+                        # Also scale the physical dimensions
+                        slice_width_um = slice_width_um * (new_w / w)
+                        slice_height_um = slice_height_um * (new_h / h)
+                    
                     roi_path = os.path.join(prev_dir, "slice.png")
                     iio.imwrite(roi_path, snp)
+                    
+                    # Show slice info
+                    st.caption(f"📏 Slice: {snp.shape[1]}×{snp.shape[0]} px → {slice_width_um:.1f}×{slice_height_um:.1f} µm")
+                    
                     if st.button("Preview on slice"):
                         # Get settings from session state if available, fallback to defaults
                         s = st.session_state.get("_settings", {})
@@ -397,8 +418,8 @@ if uploaded is not None:
                                 threshold=0.03,
                                 overlap=0.5,
                                 downsample=downsample,
-                                width_um=width_um,
-                                height_um=height_um,
+                                width_um=slice_width_um,  # Use calculated slice dimensions
+                                height_um=slice_height_um,  # Use calculated slice dimensions
                                 min_diam_um=min_diam_um,
                                 threshold_mode=threshold_mode,
                                 thresh_percent=float(thresh_percent),