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Running
Running
CatherineProtas
commited on
Commit
•
1713d64
1
Parent(s):
f2f15d3
Update app.py
Browse files
app.py
CHANGED
@@ -68,7 +68,7 @@ def get_weather_data(location):
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'wind_speed': data['wind'].get('speed', 0),
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'pressure': data['main'].get('pressure', 0),
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'humidity': data['main'].get('humidity', 0),
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-
'visibility': data.get('visibility', 10000) / 1000,
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'timestamp': datetime.fromtimestamp(data['dt'])
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}
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except requests.exceptions.RequestException as e:
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@@ -90,7 +90,7 @@ def get_forecast_data(location):
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'description': item['weather'][0].get('description', ''),
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'wind_speed': item['wind'].get('speed', 0),
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'pressure': item['main'].get('pressure', 0),
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-
'visibility': item.get('visibility', 10000) / 1000,
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'timestamp': datetime.fromtimestamp(item['dt'])
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})
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return forecasts
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@@ -122,7 +122,6 @@ def determine_transmission_power(image_prediction, weather_data, forecast_data=N
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current_fog_risk = calculate_fog_risk_score(weather_data)
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# Combine image and weather predictions with weighted average
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# Give slightly more weight to image prediction as it's more reliable
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combined_fog_risk = (image_fog_confidence * 0.6) + (current_fog_risk * 0.4)
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# Initialize explanation
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@@ -150,7 +149,6 @@ def determine_transmission_power(image_prediction, weather_data, forecast_data=N
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# Find periods of high risk
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high_risk_periods = [risk > 0.6 for risk in future_risks]
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if any(high_risk_periods):
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-
# Find the last high-risk timestamp
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last_high_risk_idx = len(high_risk_periods) - 1 - high_risk_periods[::-1].index(True)
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duration = forecast_data[last_high_risk_idx]['timestamp'] - weather_data['timestamp']
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@@ -187,7 +185,6 @@ def integrated_prediction(image, location):
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f"Current Conditions ({current_weather['timestamp'].strftime('%Y-%m-%d %H:%M')})",
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f"Temperature: {current_weather['temperature']:.1f}°C",
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f"Humidity: {current_weather['humidity']}%",
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f"Visibility: {current_weather['visibility']:.1f} km",
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f"Wind Speed: {current_weather['wind_speed']} m/s",
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"",
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"Analysis Results:",
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'wind_speed': data['wind'].get('speed', 0),
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'pressure': data['main'].get('pressure', 0),
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'humidity': data['main'].get('humidity', 0),
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+
'visibility': data.get('visibility', 10000) / 1000, # Still needed for calculations
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'timestamp': datetime.fromtimestamp(data['dt'])
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}
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except requests.exceptions.RequestException as e:
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'description': item['weather'][0].get('description', ''),
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'wind_speed': item['wind'].get('speed', 0),
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'pressure': item['main'].get('pressure', 0),
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+
'visibility': item.get('visibility', 10000) / 1000, # Still needed for calculations
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'timestamp': datetime.fromtimestamp(item['dt'])
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})
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return forecasts
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current_fog_risk = calculate_fog_risk_score(weather_data)
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# Combine image and weather predictions with weighted average
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combined_fog_risk = (image_fog_confidence * 0.6) + (current_fog_risk * 0.4)
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# Initialize explanation
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# Find periods of high risk
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high_risk_periods = [risk > 0.6 for risk in future_risks]
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if any(high_risk_periods):
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last_high_risk_idx = len(high_risk_periods) - 1 - high_risk_periods[::-1].index(True)
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duration = forecast_data[last_high_risk_idx]['timestamp'] - weather_data['timestamp']
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f"Current Conditions ({current_weather['timestamp'].strftime('%Y-%m-%d %H:%M')})",
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f"Temperature: {current_weather['temperature']:.1f}°C",
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f"Humidity: {current_weather['humidity']}%",
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f"Wind Speed: {current_weather['wind_speed']} m/s",
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"",
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"Analysis Results:",
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