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")