29 lines
630 B
Python
29 lines
630 B
Python
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import os
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import numpy as np
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import pandas as pd
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import random
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import matplotlib.pyplot as plt
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import time
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#progess bar
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from tqdm import tqdm
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import cv2
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import warnings
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#deep learning
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from consts import SEED, JPG_IMAGES, FC_DIR, FEATURES
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from helpers import create_folder, convert_tif_to_jpg
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warnings.filterwarnings('ignore')
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def transform_photo(tif_dir):
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dp = create_folder(tif_dir, JPG_IMAGES)
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fc = create_folder(FC_DIR, dp)
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convert_tif_to_jpg(os.path.join(FEATURES, tif_dir), dp, fc)
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if __name__ == "__main__":
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for d in os.listdir(FEATURES):
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print(str(d), end='\t')
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transform_photo(d)
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