iamomtiwari commited on
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b660e9c
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1 Parent(s): d4c84cb

Update app.py

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Files changed (1) hide show
  1. app.py +11 -11
app.py CHANGED
@@ -18,20 +18,20 @@ class_labels = {
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  2: {"label": "Stage Corn___Gray_Leaf_Spot", "treatment": "Rotate crops to non-host plants, apply resistant varieties, and use fungicides as needed."},
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  3: {"label": "Stage safe Corn___Healthy", "treatment": "Continue good agricultural practices: ensure proper irrigation, nutrient supply, and monitor for pests."},
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  4: {"label": "Stage Corn___Northern_Leaf_Blight", "treatment": "Remove and destroy infected plant debris, apply fungicides, and rotate crops."},
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- 8: {"label": "Stage Rice___Brown_Spot", "treatment": "Use resistant varieties, improve field drainage, and apply fungicides if necessary."},
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- 9: {"label": "Stage safe Rice___Healthy", "treatment": "Maintain proper irrigation, fertilization, and pest control measures."},
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- 10: {"label": "Stage Rice___Leaf_Blast", "treatment": "Use resistant varieties, apply fungicides during high-risk periods, and practice good field management."},
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- 11: {"label": "Stage Rice___Neck_Blast", "treatment": "Plant resistant varieties, improve nutrient management, and apply fungicides if symptoms appear."},
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- 12: {"label": "Stage Sugarcane__Bacterial Blight", "treatment": "Use disease-free planting material, practice crop rotation, and destroy infected plants."},
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- 13: {"label": "Stage safe Sugarcane__Healthy", "treatment": "Maintain healthy soil conditions and proper irrigation."},
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- 14: {"label": "Stage Sugarcane__Red_Rot", "treatment": "Plant resistant varieties and ensure good drainage."},
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- 15: {"label": "Stage Wheat___Brown_Rust", "treatment": "Apply fungicides and practice crop rotation with non-host crops."},
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- 16: {"label": "Stage safe Wheat___Healthy", "treatment": "Continue with good management practices, including proper fertilization and weed control."},
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- 17: {"label": "Stage Wheat___Yellow_Rust", "treatment": "Use resistant varieties, apply fungicides, and rotate crops."}
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  }
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  # Mapping label indices to class labels
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- labels_list = [class_labels[i]["label"] for i in range(1, 18)]
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  # Inference function
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  def predict(image):
 
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  2: {"label": "Stage Corn___Gray_Leaf_Spot", "treatment": "Rotate crops to non-host plants, apply resistant varieties, and use fungicides as needed."},
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  3: {"label": "Stage safe Corn___Healthy", "treatment": "Continue good agricultural practices: ensure proper irrigation, nutrient supply, and monitor for pests."},
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  4: {"label": "Stage Corn___Northern_Leaf_Blight", "treatment": "Remove and destroy infected plant debris, apply fungicides, and rotate crops."},
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+ 5: {"label": "Stage Rice___Brown_Spot", "treatment": "Use resistant varieties, improve field drainage, and apply fungicides if necessary."},
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+ 6: {"label": "Stage safe Rice___Healthy", "treatment": "Maintain proper irrigation, fertilization, and pest control measures."},
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+ 7: {"label": "Stage Rice___Leaf_Blast", "treatment": "Use resistant varieties, apply fungicides during high-risk periods, and practice good field management."},
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+ 8: {"label": "Stage Rice___Neck_Blast", "treatment": "Plant resistant varieties, improve nutrient management, and apply fungicides if symptoms appear."},
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+ 9: {"label": "Stage Sugarcane__Bacterial Blight", "treatment": "Use disease-free planting material, practice crop rotation, and destroy infected plants."},
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+ 10: {"label": "Stage safe Sugarcane__Healthy", "treatment": "Maintain healthy soil conditions and proper irrigation."},
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+ 11: {"label": "Stage Sugarcane__Red_Rot", "treatment": "Plant resistant varieties and ensure good drainage."},
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+ 12: {"label": "Stage Wheat___Brown_Rust", "treatment": "Apply fungicides and practice crop rotation with non-host crops."},
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+ 13: {"label": "Stage safe Wheat___Healthy", "treatment": "Continue with good management practices, including proper fertilization and weed control."},
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+ 14: {"label": "Stage Wheat___Yellow_Rust", "treatment": "Use resistant varieties, apply fungicides, and rotate crops."}
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  }
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  # Mapping label indices to class labels
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+ labels_list = [class_labels[i]["label"] for i in range(1, 15)]
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  # Inference function
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  def predict(image):