zero-padding | 易学教程

Moving Filter/Mask Across Given Image (No Function)

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问题 I am struggling attempting to create a program that pads an image and filter/mask. Where I am having trouble is actually attempting to move this filter over each bit of the image without using a function to do so. Here is what I have so far. L=256; %Gray Levels %Saving Dimensions of both Filter and Image Sizes [FilterX , FilterY] = size(Filter); [ImageX , ImageY]= size(Image); % Padding Image pad1 = FilterY; PAD = (pad1-1); %New Padded Image With Zeros MaskX = ImageX + PAD; MaskY = ImageY +

Rotating image with trigonometric functions and image padding

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来源： https://stackoverflow.com/questions/64692126/rotating-image-with-trigonometric-functions-and-image-padding

Rotating image with trigonometric functions and image padding

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来源： https://stackoverflow.com/questions/64692126/rotating-image-with-trigonometric-functions-and-image-padding

Zero pad array based on other array's shape

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问题 I've got K feature vectors that all share dimension n but have a variable dimension m (n x m). They all live in a list together. to_be_padded = [] to_be_padded.append(np.reshape(np.arange(9),(3,3))) array([[0, 1, 2], [3, 4, 5], [6, 7, 8]]) to_be_padded.append(np.reshape(np.arange(18),(3,6))) array([[ 0, 1, 2, 3, 4, 5], [ 6, 7, 8, 9, 10, 11], [12, 13, 14, 15, 16, 17]]) to_be_padded.append(np.reshape(np.arange(15),(3,5))) array([[ 0, 1, 2, 3, 4], [ 5, 6, 7, 8, 9], [10, 11, 12, 13, 14]]) What I

Tensorflow/Keras Conv2D layers with padding='SAME' behave strangely

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问题 My question: A straightforward experiment that I conducted showed that using padding='SAME' in a conv2d layer in Keras/TF is different from using padding='VALID' with a preceding zero-padding layer. How is that possible? Does Keras/TF pads zeros symmetrically around the tensor? Explanation of the experiment - just if you're interested in reading further: I used the onnx2keras package to convert my Pytorch model into keras/TF. When onnx2keras encounters a convolutional layer with padding > 0

Padding zeros to the left in postgreSQL

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问题 I am relatively new to PostgreSQL and I know how to pad a number with zeros to the left in SQL Server but I'm struggling to figure this out in PostgreSQL. I have a number column where the maximum number of digits is 3 and the min is 1: if it's one digit it has two zeros to the left, and if it's 2 digits it has 1, e.g. 001, 058, 123. In SQL Server I can use the following: RIGHT('000' + cast([Column1] as varchar(3)), 3) as [Column2] This does not exist in PostgreSQL. Any help would be

Tensor-flow how to use padding and masking layer in case of MLPs?

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问题 I want to use MLPs to solve regression problem. I have inputs with variable length to fix this I want to use Zero-padding with masking layer . I read the inputs from csv file using pandas library. Here is how my data look like. I know only how to fill NaN values with 0 using this command x_train.fillna(0.0).values Like the first row : [4, 0, 0, 512, 1.0, 0.0, 1.0, 0.0, 128.0 , NaN] After padding : [4, 0, 0, 512, 1.0, 0.0, 1.0, 0.0, 128.0 , 0.0] The mask should be like this : [1, 1, 1, 1, 1, 1

Reflection padding Conv2D

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问题 I'm using keras to build a convolutional neural network for image segmentation and I want to use "reflection padding" instead of padding "same" but I cannot find a way to to do it in keras. inputs = Input((num_channels, img_rows, img_cols)) conv1=Conv2D(32,3,padding='same',kernel_initializer='he_uniform',data_format='channels_first')(inputs) Is there a way to implement a reflection layer and insert it in a keras model ? 回答1: The accepted answer above is not working in the current Keras

Padding zeros to the left in postgreSQL

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I am relatively new to PostgreSQL and I know how to pad a number with zeros to the left in SQL Server but I'm struggling to figure this out in PostgreSQL. I have a number column where the maximum number of digits is 3 and the min is 1: if it's one digit it has two zeros to the left, and if it's 2 digits it has 1, e.g. 001, 058, 123. In SQL Server I can use the following: RIGHT('000' + cast([Column1] as varchar(3)), 3) as [Column2] This does not exist in PostgreSQL. Any help would be appreciated. You can use the rpad and lpad functions to pad numbers to the right or to the left, respectively.

why do we “pack” the sequences in pytorch?

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I was trying to replicate How to use packing for variable-length sequence inputs for rnn but I guess I first need to understand why we need to "pack" the sequence. I understand why we need to "pad" them but why is "packing" ( through pack_padded_sequence ) necessary? Any high-level explanation would be appreciated! Umang Gupta I have stumbled upon this problem too and below is what I figured out. When training RNN (LSTM or GRU or vanilla-RNN), it is difficult to batch the variable length sequences. For ex: if length of sequences in a size 8 batch is [4,6,8,5,4,3,7,8], you will pad all the