testCase neural-network2
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@ -130,7 +130,7 @@ def testing(n, testingSamples, testingLabels):
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print('Performance', scorecardArray.sum() / scorecardArray.size)
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testing(digitNetwork,dig_test_images,dig_test_labels)
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testing(letterNetwork,let_test_images,let_test_labels)
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li = []
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ourOwnDataset = []
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@ -145,8 +145,14 @@ def testCase(inputWord):
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imgData = (imgData/255 * 0.99) + 0.01
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#inputWord[i]
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word = word + recognizeLet(letterNetwork ,imgData)
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word = word + recognizeNum(digitNetwork, inputWord[-2])
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word = word + recognizeNum(digitNetwork ,inputWord[-1])
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i=len-2
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for i in range(i,len):
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imgArray = imageio.imread(imageFileName, as_gray=True)
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imgData = 255 - imgArray.reshape(784)
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imgData = (imgData/255 * 0.99) + 0.01
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#inputWord[i]
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word = word + recognizeNum(digitNetwork, imgData)
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#assert record_cache.shape == ourOwnDataset[0].shape
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@ -234,5 +240,5 @@ print('slowo: ', word)
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##################################### URUCHOMIENIE TRENINGU
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trainNetwork(letterNetwork, "Lweights_test.npy", "Lhidden_test.npy", let_train_images, let_train_labels)
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#trainNetwork(letterNetwork, "Lweights_test.npy", "Lhidden_test.npy", let_train_images, let_train_labels)
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# trainNetwork(digitNetwork, "Dweights_test.npy", "Dhidden_test.npy", let_train_images, let_train_labels)
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