Adityam Ghosh lucifermorningstar1305
👨💻
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| gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) | |
| Hx = np.array([[1,0,-1], [2,0,-2],[1,0,-1]], dtype=np.float32) | |
| Hy = np.array([[-1,-2,-1],[0,0,0],[1,2,1]], dtype=np.float32) | |
| Gx = scipy.signal.convolve2d(Gm, Hx, mode ='same') | |
| Gy = scipy.signal.convolve2d(Gm,Hy,mode = 'same') | |
| G = (Gx*Gx + Gy*Gy) ** 0.5 |
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| Hg = np.zeros((20,20)) | |
| gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) | |
| for i in range(20): | |
| for j in range(20): | |
| Hg[i,j] = np.exp(-((i-10) ** 2 + (j-10)**2)/10) | |
| gaussian_blur = scipy.signal.convolve2d(gray, Hg, mode='same') | |
| gray_high = gray - gaussian_blur | |
| gray_enhanced = gray + 0.025 * gray_high |
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| gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) | |
| Gm = cv2.medianBlur(gray,3) | |
| imgs = np.array([gray, Gm]) | |
| labels = ['Original','Filtered'] | |
| for i in range(1, column*row+1): | |
| ax = fig.add_subplot(row,column,i) | |
| ax.set_title(labels[i-1]) | |
| plt.imshow(imgs[i-1], cmap='gray') | |
| plt.show() |
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| Mean_filter = np.array([[1,1,1], [1,1,1], [1,1,1]])/float(9) | |
| Gm = scipy.signal.convolve2d(gray,Mean_filter,mode='same') | |
| plt.imshow(Gm,cmap='gray') | |
| plt.show() |
lucifermorningstar1305
/ nn.py
Created
January 13, 2019 16:02
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| activation_function = lambda x: 1.0/(1.0 + np.exp(-x)) | |
| input = np.random.randn(3,1) | |
| W1 = np.random.randn(None, 1) | |
| W2 = np.random.randn(None,1) | |
| W3 = np.random.randn(None,1) | |
| b1 = np.zeros(1) | |
| b2 = np.zeros(1) | |
| b3 = np.zeros(1) | |
| hidden_1 = activation(np.dot(W1, input) + b1) | |
| hidden_2 = activation(np.dot(W2, W1) + b2) |
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| def convolutional_neural_network(x): | |
| weights = {'W_conv1' : tf.Variable(tf.random_normal([3,3,3,64])), | |
| 'W_conv2' : tf.Variable(tf.random_normal([3,3,64,64])), | |
| 'W_conv3' : tf.Variable(tf.random_normal([3,3,64,128])), | |
| 'W_conv4' : tf.Variable(tf.random_normal([3,3,128,128])), | |
| 'W_conv5': tf.Variable(tf.random_normal([3,3,128,256])), | |
| 'W_conv6' : tf.Variable(tf.random_normal([3,3,256,256])), | |
| 'W_conv7' : tf.Variable(tf.random_normal([3,3,256,256])), | |
| 'W_conv8' : tf.Variable(tf.random_normal([3,3,256,512])), | |
| 'W_conv9' : tf.Variable(tf.random_normal([3,3,512,512])), |
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