Crop Recommendation Serve.ipynb

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      "source": [
        "import numpy\n",
        "import joblib\n",
        "import pandas as pd\n",
        "\n",
        "class RandomForestClassifier:\n",
        "    def __init__(self):\n",
        "        self.model = joblib.load('/content/drive/MyDrive/AgriWise/ML/crop-recommendation/random_forest.joblib')\n",
        "\n",
        "    def preprocessing(self, input_data):\n",
        "        # JSON to pandas DataFrame\n",
        "        input_data = pd.DataFrame(input_data, index=[0])\n",
        "\n",
        "        return input_data\n",
        "\n",
        "    def predict(self, input_data):\n",
        "        return self.model.predict_proba(input_data)\n",
        "        \n",
        "    def postprocessing(self, prediction):\n",
        "        categories = ['apple', 'banana', 'blackgram', 'chickpea', 'coconut', 'coffee',\n",
        "                      'cotton', 'grapes', 'jute', 'kidneybeans', 'lentil', 'maize', 'mango', 'mothbeans', 'mungbean', 'muskmelon', 'orange', 'papaya', 'pigeonpeas', 'pomegranate', 'rice', 'watermelon']\n",
        "        index_max_predict = numpy.argmax(prediction)\n",
        "        return categories[index_max_predict]\n",
        "        \n",
        "\n",
        "    def compute_prediction(self, input_data):\n",
        "        try:\n",
        "            input_data = self.preprocessing(input_data)\n",
        "            prediction = self.predict(input_data)[0]  # only one sample\n",
        "            prediction = self.postprocessing(prediction)\n",
        "        except Exception as e:\n",
        "            return {\"status\": \"Error\", \"message\": str(e)}\n",
        "\n",
        "      \n",
        "        return prediction"
      ]
    }
  ]
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