| import pickle
|
| import numpy as np
|
|
|
|
|
| with open("random_forest_pkl.pkl", "rb") as f:
|
| model = pickle.load(f)
|
|
|
|
|
| label_map = {
|
| 0: "غير خصبة",
|
| 1: "خصبة",
|
| 2: "عالية الخصوبة"
|
| }
|
|
|
| def predict(inputs):
|
| """
|
| تنبؤ خصوبة التربة بناءً على مدخلات عددية
|
| """
|
| try:
|
| if isinstance(inputs, dict):
|
| features = inputs.get("inputs")
|
| elif isinstance(inputs, list):
|
| features = inputs
|
| else:
|
| return {"error": "تنسيق البيانات غير صحيح"}
|
|
|
| if not isinstance(features, list) or len(features) != 12:
|
| return {"error": "مطلوب 12 خاصية في قائمة"}
|
|
|
| data = np.array(features).reshape(1, -1)
|
| code = model.predict(data)[0]
|
| label = label_map.get(code, "غير معروف")
|
|
|
| return [{"label": label}]
|
| except Exception as e:
|
| return {"error": str(e)} |
