CCockrum commited on
Commit
511b09d
ยท
verified ยท
1 Parent(s): 6cb72f5

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +8 -8
app.py CHANGED
@@ -210,9 +210,9 @@ with gr.Blocks(title="F1 Telemetry Data Analyzer", theme=gr.themes.Soft()) as de
210
  gr.Markdown("# ๐ŸŽ๏ธ F1 Telemetry Data Analyzer")
211
  gr.Markdown("Advanced AI-powered analysis of Formula 1 telemetry data with anomaly detection and predictive modeling.")
212
 
213
- with gr.Tab("๐Ÿ“Š Data Analysis"):
214
  gr.Markdown("### Generate and analyze telemetry data")
215
- analyze_btn = gr.Button("๐Ÿ” Analyze Telemetry Data", variant="primary")
216
 
217
  with gr.Row():
218
  with gr.Column(scale=2):
@@ -225,7 +225,7 @@ with gr.Blocks(title="F1 Telemetry Data Analyzer", theme=gr.themes.Soft()) as de
225
  outputs=[plot_output, report_output]
226
  )
227
 
228
- with gr.Tab("๐Ÿ”ฎ Performance Prediction"):
229
  gr.Markdown("### Predict tire performance and fuel consumption")
230
  gr.Markdown("*Note: Run the analysis first to train the models*")
231
 
@@ -249,29 +249,29 @@ with gr.Blocks(title="F1 Telemetry Data Analyzer", theme=gr.themes.Soft()) as de
249
  outputs=[tire_pred_output, fuel_pred_output]
250
  )
251
 
252
- with gr.Tab("โ„น๏ธ About"):
253
  gr.Markdown("""
254
  ## About This Tool
255
 
256
  This F1 Telemetry Data Analyzer demonstrates advanced AI techniques used in Formula 1 racing:
257
 
258
- **๐Ÿ” Anomaly Detection:**
259
  - Uses Isolation Forest algorithm to detect unusual patterns in telemetry data
260
  - Identifies potential mechanical issues or performance anomalies
261
  - Helps engineers spot problems before they become critical
262
 
263
- **๐Ÿ“ˆ Predictive Modeling:**
264
  - Machine learning models predict tire degradation and fuel consumption
265
  - Based on real-time telemetry inputs (speed, throttle, temperatures)
266
  - Enables strategic decision-making during races
267
 
268
- **๐ŸŽฏ Key Features:**
269
  - Real-time telemetry processing simulation
270
  - Advanced visualization of racing data
271
  - Performance prediction for race strategy
272
  - Anomaly detection for preventive maintenance
273
 
274
- **๐Ÿ—๏ธ Technical Stack:**
275
  - Python with scikit-learn for ML models
276
  - Isolation Forest for anomaly detection
277
  - Linear regression for performance prediction
 
210
  gr.Markdown("# ๐ŸŽ๏ธ F1 Telemetry Data Analyzer")
211
  gr.Markdown("Advanced AI-powered analysis of Formula 1 telemetry data with anomaly detection and predictive modeling.")
212
 
213
+ with gr.Tab("Data Analysis"):
214
  gr.Markdown("### Generate and analyze telemetry data")
215
+ analyze_btn = gr.Button("Analyze Telemetry Data", variant="primary")
216
 
217
  with gr.Row():
218
  with gr.Column(scale=2):
 
225
  outputs=[plot_output, report_output]
226
  )
227
 
228
+ with gr.Tab("Performance Prediction"):
229
  gr.Markdown("### Predict tire performance and fuel consumption")
230
  gr.Markdown("*Note: Run the analysis first to train the models*")
231
 
 
249
  outputs=[tire_pred_output, fuel_pred_output]
250
  )
251
 
252
+ with gr.Tab("About"):
253
  gr.Markdown("""
254
  ## About This Tool
255
 
256
  This F1 Telemetry Data Analyzer demonstrates advanced AI techniques used in Formula 1 racing:
257
 
258
+ **Anomaly Detection:**
259
  - Uses Isolation Forest algorithm to detect unusual patterns in telemetry data
260
  - Identifies potential mechanical issues or performance anomalies
261
  - Helps engineers spot problems before they become critical
262
 
263
+ **Predictive Modeling:**
264
  - Machine learning models predict tire degradation and fuel consumption
265
  - Based on real-time telemetry inputs (speed, throttle, temperatures)
266
  - Enables strategic decision-making during races
267
 
268
+ **Key Features:**
269
  - Real-time telemetry processing simulation
270
  - Advanced visualization of racing data
271
  - Performance prediction for race strategy
272
  - Anomaly detection for preventive maintenance
273
 
274
+ **Technical Stack:**
275
  - Python with scikit-learn for ML models
276
  - Isolation Forest for anomaly detection
277
  - Linear regression for performance prediction