np_utils.to_categorical Keras method give me an error when i gived it a a vector of [962] element which contain 3 classes [1,1,1,...,2,2,2,...3,3,3]. The used
I tried a sample code for CNN application on MNIST data classification from the book : from keras import layers from keras import models model = models.Sequent
I'm trying to make a classification on an image with the CNN algorithm. When I tried to run it on jupyter notebook(anaconda) it didn't work, but when I run it o
Given an output prediction of shape [1,21,388,88] from my Unet. How can I plot it as a masked image? I am using PASCAL dataset. Thanks!
I've created a multi-class image classifier using CNN. I am using the keras module specifically and I am using generators to fit and then predict 4 different cl
Tensorflow/Keras I have developed a CNN model to classify images as circle, triangle or square. However, my accuracy values have wide fluctuations. Is it someth
I am dealing with a CNN and I get the following error on the line loss = criterion(outputs, data_y): Here is the relevant code snippet: def run(model, X_train,
I used a convolutional neural network (CNN) for training a dataset and I want to plotting accuracy for this. Before, I tried to use matplotlib but I couldn't su
I've loaded in my train and validation sets from CIFAR10 like so: train = tfds.load('cifar10', split='train[:90%]', shuffle_files=True) validation = tfds.load('
ValueError Traceback (most recent call last) <ipython-input-30-33821ccddf5f> in <module> 23 output = mod
I evaluated the IoU score for the test dataset using the saved model. (model.evaluate(test_gen, steps) Also, I have calculated the IoU score for each image in
I have created a CNN to do binary classification in keras with the following code: def neural_network(): classifier = Sequential() # Adding a first convolu
I have a CNN model that has already been trained. Its training and validation accuracy are around 99%. I saved this model and then loaded it to make predictions
I have a CNN model that has already been trained. Its training and validation accuracy are around 99%. I saved this model and then loaded it to make predictions
I am currently trying to feed an image sequence as a single input entity to my CNN. I found the numpy utility numpy.lib.stride_tricks.sliding_window_view My ima
I am using dice loss for my implementation of a Fully Convolutional Network(FCN) which involves hypernetworks. The model has two inputs and one output which is
I am using dice loss for my implementation of a Fully Convolutional Network(FCN) which involves hypernetworks. The model has two inputs and one output which is
I have successfully trained and tested my model on local jupyter notebook, but I want to try the same code in Google Colab as I want to try other expensive mode
I am working on a CNN model running through a dataset of images, where I have one set of convolution layers, then two sets of dense layers for outputting age an
I know that the input_shape for Inception V3 is (299,299,3). But in Keras it is possible to construct versions of Inception V3 that have custom input_shape if