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32 lines
781 B
Python
32 lines
781 B
Python
import os
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from PIL import Image
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import torch
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from predict import predict_img
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from utils import rle_encode
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from unet import UNet
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def submit(net, gpu=False):
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"""Used for Kaggle submission: predicts and encode all test images"""
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dir = 'data/test/'
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N = len(list(os.listdir(dir)))
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with open('SUBMISSION.csv', 'a') as f:
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f.write('img,rle_mask\n')
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for index, i in enumerate(os.listdir(dir)):
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print('{}/{}'.format(index, N))
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img = Image.open(dir + i)
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mask = predict_img(net, img, gpu)
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enc = rle_encode(mask)
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f.write('{},{}\n'.format(i, ' '.join(map(str, enc))))
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if __name__ == '__main__':
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net = UNet(3, 1).cuda()
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net.load_state_dict(torch.load('MODEL.pth'))
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submit(net, True)
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