updates
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train.py
2
train.py
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@ -379,7 +379,7 @@ if __name__ == '__main__':
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if opt.bucket:
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os.system('gsutil cp gs://%s/evolve.txt .' % opt.bucket) # download evolve.txt if exists
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for _ in range(2): # generations to evolve
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for _ in range(1): # generations to evolve
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if os.path.exists('evolve.txt'): # if evolve.txt exists: select best hyps and mutate
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# Get best hyperparameters
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x = np.loadtxt('evolve.txt', ndmin=2)
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@ -29,7 +29,7 @@ python3 detect.py
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python3 test.py --save-json
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# Evolve
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for i in {0..100}
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for i in {0..500}
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do
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python3 train.py --data data/coco.data --img-size 320 --epochs 1 --batch-size 64 --accumulate 1 --evolve --bucket yolov4
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done
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