data-augmentation

zoom in and zoom out images for training dataset augmentation

zoom in and zoom out images for training dataset augmentation Question: I want to train a deep learning model with some image data. Since my dataset is small, I want to perform a zoom-in and zoom-out augmentation to get a 3 times larger dataset. I have done the zoom-in operation as follows: img = cv2.imread(path),0) …

Total answers: 1

How to train XGBoost with probabilities instead of class?

How to train XGBoost with probabilities instead of class? Question: I am trying to train an XGBoost classifier by inputting the training dataset and the training labels. The labels are one hot encodings and instead of sending in the classes such as [0,1,0,0], I wanted to send an inputs of the probabilities like [0,0.6,0.4,0] for …

Total answers: 1

Time Series Augmentation

Time Series Augmentation Question: How to apply “Magnitude Warping” data augmentation on time series dataset? Is there any sample code in pytorch? Also can we apply the image augmentation techniques like RandomGrayscale, GaussianBlur and Normalize to time series dataset? Trying with the below code for magnitude Warping on Swelltrain dataset of size (1887, 95): sigma …

Total answers: 1

Changes to Dataset in for loop don't work

Changes to Dataset in for loop don't work Question: I’m trying to augment my dataset by randomly changing the hue of its images within a for loop but the changes do not persist outside of the loop. I imported the dataset with tf.keras.utils.image_dataset_from_directory. The rest of the code looks as follows: def augment(image, label, counter): …

Total answers: 3

How to rotate a rectangle/bounding box together with an image

How to rotate a rectangle/bounding box together with an image Question: I’m working on a data augmentation and im trying to generate synthetic version of every image in my dataset. So i need to rotate images and together with bounding boxes as well in the images. im only going to rotate images by 90, 180, …

Total answers: 3

How to fit Keras ImageDataGenerator for large data sets using batches

How to fit Keras ImageDataGenerator for large data sets using batches Question: I want to use the Keras ImageDataGenerator for data augmentation. To do so, I have to call the .fit() function on the instantiated ImageDataGenerator object using my training data as parameter as shown below. image_datagen = ImageDataGenerator(featurewise_center=True, rotation_range=90) image_datagen.fit(X_train, augment=True) train_generator = image_datagen.flow_from_directory(‘data/images’) …

Total answers: 1

Data Augmentation in PyTorch

Data Augmentation in PyTorch Question: I am a little bit confused about the data augmentation performed in PyTorch. Now, as far as I know, when we are performing data augmentation, we are KEEPING our original dataset, and then adding other versions of it (Flipping, Cropping…etc). But that doesn’t seem like happening in PyTorch. As far …

Total answers: 6