Example #1
0
        static void testClassMNIST()
        {
            MNIST mnist = new MNIST();

            mnist.loadTrainingSetFiles(trainingImagesFileName, trainingLabelsFileName);
            mnist.loadTestSetFiles(testImagesFileName, testLabelsFileName);

            int i, j;

            while (Console.ReadLine().Equals(""))
            {
                i = random.Next(60000);
                Console.WriteLine("trainingImages[" + i + "]:");
                Console.WriteLine(mnist.trainingImages[i]);
                Console.WriteLine("trainingLabels[" + i + "]:");
                Console.WriteLine(mnist.trainingLabels[i]);

                j = random.Next(10000);
                Console.WriteLine("testImages[" + j + "]:");
                Console.WriteLine(mnist.testImages[j]);
                Console.WriteLine("testLabels[" + j + "]:");
                Console.WriteLine(mnist.testLabels[j]);

                Console.WriteLine("Enter non-empty line to quit!");
            }

            for (int k = 0; k < 60000; k++)
            {
                if (mnist.trainingLabels[k] < 0 || mnist.trainingLabels[k] > 9)
                {
                    throw new Exception("testMNIST: Invalid training label. " +
                                        "trainingLabels[" + k + "]: " + mnist.trainingLabels[k]);
                }
            }

            Console.WriteLine("trainingLabels OK!");

            for (int k = 0; k < 10000; k++)
            {
                if (mnist.testLabels[k] < 0 || mnist.testLabels[k] > 9)
                {
                    throw new Exception("testMNIST: Invalid test label. " +
                                        "testLabels[" + k + "]: " + mnist.testLabels[k]);
                }
            }

            Console.WriteLine("testLabels OK!");
        }
Example #2
0
        static void writeImage()
        {
            MNIST mnist = new MNIST();

            mnist.loadTrainingSetFiles(trainingImagesFileName, trainingLabelsFileName);

            int i;

            while (Console.ReadLine().Equals(""))
            {
                i = random.Next(60000);
                Console.WriteLine("trainingImages[" + i + "]:");
                Console.WriteLine(mnist.trainingImages[i]);
                Console.WriteLine("trainingLabels[" + i + "]:");
                Console.WriteLine(mnist.trainingLabels[i]);

                Console.WriteLine("Enter non-empty line to quit!");
            }
        }