import cv2
import numpy as np
import pickle as pickle
import os


def resize(max_side, img):
    if img.shape[1] > img.shape[0]:
        r = max_side / img.shape[1]
        dim = (max_side, int(img.shape[0] * r))
    else:
        r = max_side / img.shape[0]
        dim = (int(img.shape[1] * r), max_side)

    # perform the actual resizing of the image and show it
    resized = cv2.resize(img, dim, interpolation=cv2.INTER_AREA)
    return resized


def pickle_img_lf(dest, id, keypoints, descriptors):
    dest_folder_name = id[0:3]
    filename = id + '.dat'
    dest_folder_path = os.path.join(dest, dest_folder_name)
    if (not os.path.exists(dest_folder_path)):
        os.mkdir(dest_folder_path)
    dest_path = os.path.join(dest_folder_path, filename)
    kps = np.float32([keypoints[i].pt for i in range(0, len(keypoints))])
    pickle.dump([kps, descriptors], open(dest_path, 'wb'))


def unpickle_img_lf(lf_path, id):
    dest_folder_name = id[0:3]
    filename = id + '.dat'
    dest_folder_path = os.path.join(lf_path, dest_folder_name)
    dest_path = os.path.join(dest_folder_path, filename)
    kps,  des = pickle.load((open(dest_path, "rb")))
    return kps,  des


def delete_img_lf(dest, id):
    dest_folder_name = id[0:3]
    filename = id + '.dat'
    dest_folder_path = os.path.join(dest, dest_folder_name)
    dest_path = os.path.join(dest_folder_path, filename)
    if os.path.exists(dest_path):
        os.remove(dest_path)
        if not os.listdir(dest_folder_path):
            os.rmdir(dest_folder_path)