jacobbarkow commited on
Commit
4921103
·
1 Parent(s): c08fbe3

minor fixes to diagnostic message and probability sorting\

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Files changed (1) hide show
  1. app.py +1 -2
app.py CHANGED
@@ -77,7 +77,7 @@ def plant_treatment_message(predicted_string):
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  elif predicted_string == "Squash___Powdery_mildew":
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  return "This is a fungal disease that can cause white powdery spots on leaves and fruit. Consider removing infected plant parts and treating with a fungicide."
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  elif predicted_string == "Strawberry___Leaf_scorch":
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- return "This can be caused by drought, sunburn, or fungal diseases. Make sure Consider removing infected plant parts and treating with a fungicide."
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  elif predicted_string == "Tomato___Bacterial_spot":
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  return "This is a bacterial disease that can cause spots on leaves and fruit. Consider removing infected plant parts and treating with a copper-based fungicide."
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  elif predicted_string == "Tomato___Early_blight":
@@ -105,7 +105,6 @@ def clean_prediction(prediction):
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  treatment = plant_treatment_message(p['predicted']) if diagnosis is not 'healthy' else None
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  clean_predictions.append([plant, diagnosis, "{0:.1f}%".format(float(p['probability']) * 100), treatment])
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- clean_predictions.sort(key=lambda x: x[2], reverse=True)
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  return clean_predictions
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  def diagnose_health(file):
 
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  elif predicted_string == "Squash___Powdery_mildew":
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  return "This is a fungal disease that can cause white powdery spots on leaves and fruit. Consider removing infected plant parts and treating with a fungicide."
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  elif predicted_string == "Strawberry___Leaf_scorch":
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+ return "This can be caused by drought, sunburn, or fungal diseases. Make sure your plant is getting enough water and sunlight. Consider removing infected plant parts and treating with a fungicide."
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  elif predicted_string == "Tomato___Bacterial_spot":
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  return "This is a bacterial disease that can cause spots on leaves and fruit. Consider removing infected plant parts and treating with a copper-based fungicide."
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  elif predicted_string == "Tomato___Early_blight":
 
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  treatment = plant_treatment_message(p['predicted']) if diagnosis is not 'healthy' else None
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  clean_predictions.append([plant, diagnosis, "{0:.1f}%".format(float(p['probability']) * 100), treatment])
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  return clean_predictions
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  def diagnose_health(file):