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# For the best DCGAN generator | |
# 1. covid small | |
# 2. rsna_10 | |
# 3. rsna_50 | |
noise = np.random.normal(0, 1, (100, 128)) | |
gen_sample = generator.predict([noise, label]) # e.g. label is 0 or 1 in RSNA | |
# gen_sample in keras outputs (100, 64, 64, 3) | |
# e.g. for rsna_10 i need two vectors (100, 64, 64, 3), one for each lass |
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