paramiko error

README.md

@@ -1,56 +1,114 @@
-
 # Bureau of Ocean Energy Management Geospatial Data Viewer
 
-Offshore biodiversity surveys for BOEM
+A web application for visualizing and analyzing biodiversity data collected during aerial surveys of offshore wind energy areas.
+
+## 🔧 Installation
+
+### Prerequisites
+- Python 3.8 or higher
+- Git
 
-## Install the required dependencies:
+### Setup
+
+1. Clone the repository:
+```bash
+git clone https://github.com/yourusername/BOEM-webapp.git
+cd BOEM-webapp
+```
 
+2. Create and activate a virtual environment:
+```bash
+# On Windows
+python -m venv venv
+venv\Scripts\activate
+
+# On macOS/Linux
+python3 -m venv venv
+source venv/bin/activate
+```
+
+3. Install required dependencies:
 ```bash
 pip install -r requirements.txt
 ```
 
-## Running the Application
+### Environment Configuration
+
+Create a `.env` file in the project root with the following configuration:
+```bash
+REPORT_SERVER_HOST=your_server_host
+REPORT_SERVER_USER=your_username
+REPORT_DIR=/path/to/reports/directory
+```
+
+Replace the values with your specific configuration:
+- `REPORT_SERVER_HOST`: The host server for reports (e.g., hpg.rc.ufl.edu)
+- `REPORT_SERVER_USER`: Your server username
+- `REPORT_DIR`: Full path to the reports directory on the server
 
-1. Ensure you're in the project directory and your virtual environment is activated
+## 🚀 Running the Application
+
+1. Ensure you're in the project directory with your virtual environment activated
 
 2. Start the Streamlit app:
 ```bash
-streamlit run app.py
+streamlit run app/main.py
 ```
 
 3. The application will open in your default web browser at `http://localhost:8501`
 
-## Project Structure
+## 📁 Project Structure
 
-## Dependencies
+```
+BOEM-webapp/
+├── app/
+│   ├── main.py              # Main application entry point
+│   ├── pages/              
+│   │   ├── Model_Development.py
+│   │   ├── Observations.py
+│   │   ├── Video.py
+│   │   └── ...
+│   └── utils/
+│       └── vector_utils.py
+├── .env                    # Environment configuration
+├── .vscode/
+│   └── launch.json        # VS Code debug configuration
+├── prepare.py             # Data preparation script
+├── requirements.txt       # Python dependencies
+└── README.md
+```
 
-The main project dependencies include:
-- streamlit
-- openai (or your preferred AI model library)
-- python-dotenv
-- (other relevant dependencies)
+## 🛠️ Features
 
-## Contributing
+- Interactive visualization of biodiversity survey data
+- Marine wildlife species detection and classification
+- Distribution maps and abundance estimates
+- Temporal and spatial pattern analysis
+- Video playback of flight line footage
+- Image galleries of detected species
+
+## 🤝 Contributing
 
 1. Fork the repository
 2. Create a new branch for your feature
 3. Commit your changes
 4. Push to the branch
 5. Create a Pull Request
 
-## License
+## 💬 Support
 
-This project is licensed under the MIT License - see the LICENSE file for details.
+For support:
+- Open an issue in the repository
+- Contact the project maintainers
 
-## Support
+## 📜 License
 
-For support, please:
-- Open an issue in the repository
-- Contact the maintainers at [email]
+This project is licensed under the MIT License - see the LICENSE file for details.
 
-## Acknowledgments
+## 🙏 Acknowledgments
 
-- Streamlit team for the amazing framework
-- Contributors and maintainers
-- (Other relevant acknowledgments)
+- Bureau of Ocean Energy Management
+- University of Florida Research Computing
+- Streamlit team
+- All contributors and maintainers
 

app/pages/Model_Development.py

@@ -1,17 +1,37 @@
 import streamlit as st
+import pandas as pd
+
+report = pd.read_csv("app/data/report.csv")
+detection_url = report.loc[0, "Detection URL"]
+classification_url = report.loc[0, "Classification URL"]
 
 st.title("Model Development")
 
 st.header("Detection")
 
-st.subheader("True Positive Rate:")
+# Filter for detection metrics
+detection_metrics = report.filter(regex='^detection_').reset_index(drop=True)
+
+# Clean up column names by removing 'detection_' prefix
+detection_metrics.columns = detection_metrics.columns.str.replace('detection_', '')
 
-st.subheader("False Positive Rate:")
+# Create two column layout
+col1, col2 = st.columns(2)
 
-st.subheader("Confusion Matrix:")
+with col1:
+    st.subheader("Detection Metrics:")
+    # Format metrics as table
+    st.dataframe(
+        detection_metrics.T.rename(columns={0: 'Value'})
+        .style.format("{:.3f}")
+    )
+
+st.markdown(f"For more details, see the [Detection Report Confusion Matrix]({detection_url + '?experiment-tab=confusionMatrix'})")
 
 st.header("Species Classification") 
 
+st.markdown(f"For more details, see the [Classification Report Confusion Matrix]({classification_url + '?experiment-tab=confusionMatrix'})")
+
 st.subheader("Species Classification Accuracy:")
 
 st.subheader("Species Classification Confusion Matrix:")