Update README.md

README.md

@@ -4,25 +4,40 @@ sdk_version: 1.49.1
 ---
 # TGA Graph Interpreter
 
-This Streamlit app analyzes Thermogravimetric Analysis (TGA) plots.
+A Streamlit app to analyze Thermogravimetric Analysis (TGA) data.
 
 ## Features
-- Upload TGA plots (PNG, JPG, PDF).
-- Detects and separates multiple thermograms from a single figure.
-- Reads legends (if present).
-- Extracts and reports:
+- Upload TGA data in **CSV** or **Excel** format:
+  - First column = Temperature (°C)
+  - Remaining columns = Weight (%) for each thermogram
+  - Column headers are used as labels (legends)
+- Supports multiple thermograms in a single file
+- Provides analysis for each thermogram:
   - Onset temperature
   - Peak degradation temperature
   - % weight loss
+- Optional image upload (PNG/JPG) for visualization only
 
-## Deployment
-This app runs on Hugging Face Spaces with the Streamlit SDK.
+## File Structure
+- `app.py`: Streamlit app
+- `requirements.txt`: Python dependencies
+- `Dockerfile`: Hugging Face Docker build setup
+- `README.md`: Project documentation
 
-### Files
-- `app.py`: Main Streamlit application.
-- `requirements.txt`: Required Python packages.
+## Usage
+1. Open the app in Hugging Face Spaces.
+2. Upload your TGA dataset:
+   - CSV or Excel file with columns as described above.
+3. View results for each thermogram separately.
+4. Optionally, upload a TGA graph image for display.
 
-### Usage
-1. Upload your TGA plot.
-2. The app extracts each curve and provides a description separately.
+## Example CSV format
+```csv
+Temperature, Sample1, Sample2
+25, 100, 100
+100, 98, 97
+200, 85, 82
+300, 60, 55
+400, 55, 50
+500, 50, 45