Beispiel #1
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def load2d(test=False, cols=None):
    X, y = load(test=test)
    X = X.reshape(-1, 1, 96, 96)
    return X, y
Beispiel #2
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def vectorized_result(j):
    e = np.zeros(10)
    e[j] = 1.0
    return e


def normalize_input(X):
    return np.array([x / 255 for x in X])


images, labels = loadlocal_mnist(
    images_path='../Datasets/MNIST_digits/train-images-idx3-ubyte',
    labels_path='../Datasets/MNIST_digits/train-labels-idx1-ubyte')

#net = network.Network([784, 64, 40, 10])
net = network.load('MNIST_digits', 20)

#images = images[:10000]
#labels = labels[:10000]

for ep in range(10, 100):
    example = 0
    ep_loss = 0
    start = time.time()
    for X, y in zip(images, labels):
        ep_loss += net.train(normalize_input(X), vectorized_result(y), ep)
        #ep_loss += network.mse_loss(vectorized_result(y), net.feedforward(X))
        example += 1
        if example % 10000 == 0:
            end = time.time()
            if example > 0:
Beispiel #3
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def load2d(test=False, cols=None):
    X, y = load(test=test)
    X = X.reshape(-1, 1, 96, 96)
    return X, y
Beispiel #4
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    img = cv2.imread("/home/simon/Downloads/george-clooney.jpg")
    img = cv2.imread("/home/simon/Pictures/smoss.jpg")
    grey = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    rects = detect(grey)
    print rects, len(rects)
    face = rects[0]
    grey = grey[face[1]:face[3],face[0]:face[2]]/255.0
    grey = cv2.resize(grey, (96,96))
    draw_rects(img, rects, (0,255,0))
    cv2.imshow("X", grey)

    net1 = pickle.load(file('net1.pickle'))
    net2 = pickle.load(file('net2.pickle'))

    sample1 = load(test=True)[0][6:7]
    print sample1


    sample2 = load2d(test=True)[0][6:7]
    print grey.shape
    sample2 = grey.reshape(-1,1,96,96)
    sample2 = np.array(sample2, np.float32)
    print sample2

    y_pred1 = net1.predict(sample1)[0]
    import time

    for i in range(100):
        y_pred2 = net2.predict(sample2)[0]
        print i
Beispiel #5
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    img = cv2.imread("/home/simon/Downloads/george-clooney.jpg")
    img = cv2.imread("/home/simon/Pictures/smoss.jpg")
    grey = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    rects = detect(grey)
    print rects, len(rects)
    face = rects[0]
    grey = grey[face[1]:face[3], face[0]:face[2]] / 255.0
    grey = cv2.resize(grey, (96, 96))
    draw_rects(img, rects, (0, 255, 0))
    cv2.imshow("X", grey)

    net1 = pickle.load(file('net1.pickle'))
    net2 = pickle.load(file('net2.pickle'))

    sample1 = load(test=True)[0][6:7]
    print sample1

    sample2 = load2d(test=True)[0][6:7]
    print grey.shape
    sample2 = grey.reshape(-1, 1, 96, 96)
    sample2 = np.array(sample2, np.float32)
    print sample2

    y_pred1 = net1.predict(sample1)[0]
    import time

    for i in range(100):
        y_pred2 = net2.predict(sample2)[0]
        print i