Questions tagged [data-augmentation]
The data-augmentation tag has no usage guidance.
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How many images are generated when ImageDataGenerator is used, and when data augmentation is included as a part of the model?
Is there any way to know the number of images generated by the ImageDataGenerator class and loading data using flow_from_directory method? I searched everywhere for the same but couldn't find anything ...
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12 views
Is it possible to increase the number of images of one class using data augmentation, which is not applied on the other class, in the same dataset?
I have 2 classes for my image classification problem, say class A and class B, and I am using tensorflow and keras for the same. One of them have around 5K images while the other have just around 2K ...
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5 views
How do you compare outputs from different augmentations for consistency training?
I'm trying to figure out how papers using consistency train on unsupervised data, and I'm stuck on how outputs from different augmentations are compared. Since the augmentations are transformations, I ...
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22 views
Constraining a Deep Neural Network based on a priori knowledge of a real world system
I am new to this field and to StackExchage, so I guess I'll start by saying hello!
I am building a deep neural network to model a physical system which takes a set of inputs based on real-world ...
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2answers
49 views
What is the use of using width/height shift in data augmentation?
I'm not sure to understand the use of augmentation data using width shift and height shift.
Say I have limited image data, and I want to create new data using Keras' ImageDataGenerator. To classify ...
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16 views
Should I resize my object localization dataset in order to train a fully convolutional network?
I want to create a fully-convolutional neural net that trains on wider face datasets in order to draw bounding box around faces. The dataset is highly diverse in the image sizes. So my question is, ...
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1answer
19 views
Is it better to augment both training and validation sets or just training set?
Is it better to augment data both training and validation sets or just the training set in order to achieve the best accuracy possible on a convolutional neural network? why?
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18 views
Textbook definition of Data augmentation
I'm trying to find a textbook definition of Data augmentation. We all know what it is, but I'm having a hard time finding a reliable source which I can cite for my paper:
The Wikipedia article on ...
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1answer
31 views
First perform data augmentation or normalization?
Should I first perform data augmentation or normalization in deep learning? I am mainly interested in 2D and 3D input data. In tutorials that I have seen so far the data augmentation always comes ...
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2answers
44 views
Why should I use data augmentation as Keras layer
I've seen in several Tensorflow/Keras tutorials that data augmentation functions are added as keras layers. When I converted my Keras Python model (for production purpose) to TensorflowJS I faced the ...
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11 views
ImageDataGenerator augmenting only one image in training set
My datset consists of images in 10 classes. I am using 'ImageDataGenerator' to augment my training data using 'flow_from_directory' with training directory containing subdirectories of classes, each ...
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216 views
What exactly are the data augmentation experimental Keras' layers doing?
From what I gathered, data augmentation consists in increasing your number of instances in your dataset by applying some transfromations. Let's say I want to classify images. If I apply a random ...
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Modify keras_unet.utils.get_augmented to read images from disk
I want to train a cnn model on a large dataset (10K images and masks).
Currently, I am reading data in batches of BATCH_SIZE = 500 images, augment with
...
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1answer
15 views
Are GPTs close to real intelligence or just another Data In -Data Out -Data Permutation and Combinations?
Use cases and Solutions surrounding GPT's have taken NLP world with storm and started the GPT-Best vs GPT- Not So Best war on the internet. There are solutions been derived from API's provided by HF. ...
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1answer
28 views
Is there any possibility to apply deep dreaming in data augmentation?
I looked into the deep dreaming concepts and feel like this has the potential for data generation. But i'm not sure how possible this concept is. Any thoughts regarding this?
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114 views
How to change voice features in python without affecting speech/language features?
I am trying to build a CNN model which should be able to identify the language being spoken in an audio file. I have extracted the MFCC matrix (for 13 coefficients) for each audio file and trained it....
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7 views
How to use ImageDataGenerator for uint16 images
Keras does not support png uint16 images and convert them into uint8. I found some changes made here, but not adopted yet in the installed version in Google Colab. I wonder if there is any way to ...
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2answers
52 views
Problem of continuous training - Supervised learning
I am sure this is a most common problem, but would like to know by experts on how to tackle it. Note that, I mostly deal with textual data (NLP problems).
When a supervised learning model is created, ...
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43 views
How to measure augmented data quality
I work on NLP binary classification task (but actually the question can be applied to any ML task using augmentation) and use Augmentation technique for creating additional data.
I already have ...
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2answers
362 views
Why are results without Transfer Learning better than with Transfer Learning?
I developed a neural network for license plate recognition and used the EfficientNet architecture (https://keras.io/api/applications/efficientnet/#efficientnetb0-function) with and without pretrained ...
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86 views
Data augmentation for recommendation systems
I have a user-item matrix that I use to train a denoising autoencoder to predict the top-k items to recommend to the different users.
The idea is to corrupt the matrix by erasing a percentage ...
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1answer
42 views
Training with less data
Most problem with machine learning projects I have faced is the lack of data. The samples available are enough to disqualify rule based approach but not enough for a neural network to train.
For ...
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2answers
108 views
How to train a keras model on both original and augmented data from ImageDataGenerator?
I have a dataset that contains about 87000 images in a directory, with each class in a separate subfolder. I've tried the class ImageDataGenerator() and the ...
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2answers
131 views
Should augmentation also be performed on the validation set when the dataset is imbalanced?
I am training a CNN on images (2 classes) and I have an imbalanced dataset (1:7 ratio). I am trying to tackle this by performing offline image augmentation. Should I perform augmentation also on the ...
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1answer
31 views
What's the difference between keras api augmentation and data augmentation definition?
The augmentation definition is increasing the number of images by using rotation, crop and flip to avoid overfitting. The keras API apply augmentation but no increasing the number of image. What keras ...
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1answer
47 views
How to do data augmentation for Machine Learning on statistical data?
I am training machine learning classification model. I have data in csv format with lets say 5 features(or columns) and 100 such observations(or rows).
I want to add more similar data to improve my ...
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74 views
What is the difference between domain randomization and data augmentation?
Domain randomization (https://arxiv.org/abs/1703.06907) is used to create a synthetic dataset with enough variance that it will encompass unseen real data, as just one variation.
I am trying to ...
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62 views
Problem with data augmentation only on train set!
So I want to augment my data but unfortunately, I don't have an individual folder for train and validation set, and of course, I want to only augment the train set but if I use this:
...
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1answer
511 views
Data augmentation for multiple output heads in Keras
I have a transfer learning based two output classification problem. So, accordingly, I have formatted my data to have X_train as a ...
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0answers
34 views
Time Series Model (n-beats paper) how is sampling / training done?
does any one know what this means?
It is taken from the paper https://openreview.net/pdf?id=r1ecqn4YwB (n-beats time series model).
To update network parameters for one horizon, we sample train ...
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1answer
64 views
How can I improve my model on a very very small dataset?
I am starting as a PhD student and we want to find appropriate materials (with certain qualities) from basic chemical properties like charge, etc. There are a lot of models and datasets in similar ...
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1answer
28 views
After performing data Augmentation on tf.data.Dataset, should i MERGE it with original tf.data.Dataset?
Kind of a silly question, but I read that data Augmentation can be used in order to solve problem of small datasets. In my case, I've got a dataset with 5 different classes and around 2k examples per ...
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0answers
81 views
Flow_from_directory() won't load any image
i'm trying to load images for training a CNN using keras flow_from_directorY(), but seems that is having hard times finding the images. i'm running the code on google colab
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835 views
ValueError: could not convert string to float: 'Nor967.jpg'
Whenever I try to use the data augmentation ImageDataGenerator I'm getting an error like could not convert string to float. Here is my code.
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1answer
66 views
Why do we use different image processing at train and test time for an image classification tasl
I would like to ask why we use different image processing at train and test for an image classification task. For example, this pytorch tutorial uses RandomResizedCrop at train time and then Resize + ...
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1answer
131 views
Using MultiLabelBinarizer for SMOTE
This is my first NLP project. I'm trying to use SMOTE for a classifier with 14 classes. I need to convert the classes into an array before using SMOTE. I tried using MultiLinearBinarizer but it does ...
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1answer
186 views
ImageDataGenerator - trained with model.fit instead of model.fit_generator [closed]
I am a beginner in using the ImageDataGenerator from Keras and I accidentally used model.fit instead of model.fit_generator.
...
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42 views
How to build wake-word detection dataset from keyword pronunciations
I have quite a few audio files which are just pronunciation of one particular word, of course there are different tones, accents etc.
I want to build model for wake-word detection, so I need to ...
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2answers
138 views
Same validation accuracy, different train accuracy for two neural networks models
I'm performing emotion classification over FER2013 dataset. I'm trying to measure different models performance, and when I checked ImageDataGenerator with a model I had already used I came up with the ...
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1answer
25 views
Data augmentation in deep training
I'm trying to understand the role of data augmentation and how it can affect the performance/accuracy of a deep model. My target application is a fire classification (fire or not, on video frames), ...
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How many augmentated data points for each training image?
What are some useful rules of thumb for picking the number of augmenters per training image?
I realize this is a hyperparameter I can vary and test: I'm just trying to get a sense for reasonable ...
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1answer
1k views
Is GridSearchCV in combination with ImageDataGenerator possible and recommendable?
I want to optimize some hyperparameters for a CNN architecture by using GridSearchCV (Scikit-Learn) in combination with Data Augmentation (ImageDataGenerator from Keras).
However, GridSearchCV only ...
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1answer
86 views
How important is the channel order in deep-learning computer vision tasks?
I stumbled across this question while working with OpenCV, which stores color images in BGR order in memory, while most other libraries I know of use RGB order.
How important is this difference? ...
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1answer
438 views
Fastest batch perspective transform for image augmentation
I need to do some augmentation for my training images for a neural networks.
The problem is that even when loading batches in parallel, the augmentation is taking longer to perform than the network ...
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0answers
506 views
Data Augmentation techniques for classification of imbalanced time series datasets
Now I have a task to classify the imbalanced time series datasets using ML classifiers, such as Logistic Regression, Decision Tree, SVM, and KNN. I am not allowed to use the Deep Learning tools, such ...
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1answer
28 views
What is the reason behind having low results using the data augmentation technique in NLP?
I used Data augmentation technique on my dataset, to have more data to train. My data is text so the data augmentation technique is based on random insertion of words, random swaps and synonyms ...
1
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1answer
438 views
Data Augmentation Multi Outputs
This question is asked several times here on SE, but I havent been able to find the right answer.
I'm trying to build a network with 1 input and 2 outputs. I don't have a lot of data so I would like ...
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1answer
31 views
Using data agumentation for a frozen pre-trained model
I was following the following article with regards to doing transfer learning:
https://blog.keras.io/building-powerful-image-classification-models-using-very-little-data.html
In the section, Using ...
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1answer
73 views
Non-Real Time Data Augmentation for CNN Classification. What are the drawbacks?
When people talk about and use data augmentation, are they mostly referring to real-time data augmentation? In the case of image classification, that would involve augmenting the data right before ...
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2answers
415 views
after augmentation validation accuracy going down?
My main question is about augmentation.
if I process the augmentation I believe it always better than less data
but in my case the validation accuracy going down
train : 7000 images , validation: ...
