49 lines
1.5 KiB
Python
49 lines
1.5 KiB
Python
import cv2
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import numpy as np
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import pickle as pickle
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import os
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def resize(max_side, img):
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if img.shape[1] > img.shape[0]:
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r = max_side / img.shape[1]
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dim = (max_side, int(img.shape[0] * r))
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else:
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r = max_side / img.shape[0]
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dim = (int(img.shape[1] * r), max_side)
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# perform the actual resizing of the image and show it
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resized = cv2.resize(img, dim, interpolation=cv2.INTER_AREA)
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return resized
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def pickle_img_lf(dest, id, keypoints, descriptors):
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dest_folder_name = id[0:3]
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filename = id + '.dat'
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dest_folder_path = os.path.join(dest, dest_folder_name)
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if (not os.path.exists(dest_folder_path)):
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os.mkdir(dest_folder_path)
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dest_path = os.path.join(dest_folder_path, filename)
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kps = np.float32([keypoints[i].pt for i in range(0, len(keypoints))])
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pickle.dump([kps, descriptors], open(dest_path, 'wb'))
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def unpickle_img_lf(lf_path, id):
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dest_folder_name = id[0:3]
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filename = id + '.dat'
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dest_folder_path = os.path.join(lf_path, dest_folder_name)
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dest_path = os.path.join(dest_folder_path, filename)
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kps, des = pickle.load((open(dest_path, "rb")))
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return kps, des
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def delete_img_lf(dest, id):
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dest_folder_name = id[0:3]
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filename = id + '.dat'
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dest_folder_path = os.path.join(dest, dest_folder_name)
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dest_path = os.path.join(dest_folder_path, filename)
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if os.path.exists(dest_path):
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os.remove(dest_path)
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if not os.listdir(dest_folder_path):
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os.rmdir(dest_folder_path)
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