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semester_4/osnove_racunalniskega_vida/Naloga_5/train.py

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+import cv2
+import numpy as np
+import matplotlib.pyplot as plt
+from skimage.feature import hog
+from sklearn.neighbors import KNeighborsClassifier
+from sklearn.metrics import accuracy_score
+from sklearn.model_selection import train_test_split
+from sklearn.metrics import classification_report
+from sklearn import svm
+from sklearn import tree
+import pickle
+
+from implement import train_and_save_model, save_data, get_data, load_data
+
+print("Train")
+
+img_data_path = "Data\\train_img_data.npy"
+marks_data_path = "Data\\train_marks.npy"
+train_baza_path = "Baza\\Pet1000"
+
+print("loading data")
+if False:
+    img_data, marks = get_data(train_baza_path)
+    save_data(img_data, marks, img_data_path, marks_data_path)
+else:
+    img_data, marks = load_data(img_data_path, marks_data_path)
+
+
+print("Training")
+train_and_save_model(img_data, marks)
+print("End")