Saving Custom TableNet Model (VGG19 based) for table extraction – Azure Databricks Question: I have a model based on TableNet and VGG19, the data (Marmoot) for training and the saving path is mapped to a datalake storage (using Azure). I’m trying to save it in the following ways and get the following errors on Databricks: …
cannot fit the model using data loaded from tfds ImageFolder Question: I am trying to use VGG16 in a model but I got an error when calling fit. ValueError: Input 0 of layer "sequential_1" is incompatible with the layer: expected shape=(None, 363, 360, 3), found shape=(363, 360, 3) I am using tfds to load images …
Resizing a numpy array to 224×224 for VGG16 Model Question: I am solving a Multiview Classification problem using VGG16 pretrained model. In my case, I have 4 views that are my inputs and they are of size (64,64,3). But VGG16 uses input size of (224,224,3). Now for solving the problem, I am supposed to create …
How can I add new layers on pre-trained model with PyTorch? (Keras example given) Question: I am working with Keras and trying to analyze the effects on accuracy that models which are built with some layers with meaningful weights, and some layers with random initializations. Keras: I load VGG19 pre-trained model with include_top = False …
How predict more than one image in keras Question: I Am trying to run a project from github , I am trying to cluster images, but when I run the project I get an error ValueError: Error when checking input: expected input_1 to have 4 dimensions, but got array with shape (500, 150528) I tried …
VGG, perceptual loss in keras Question: I’m wondering if it’s possible to add a custom model to a loss function in keras. For example: def model_loss(y_true, y_pred): inp = Input(shape=(128, 128, 1)) x = Dense(2)(inp) x = Flatten()(x) model = Model(inputs=[inp], outputs=[x]) a = model(y_pred) b = model(y_true) # calculate MSE mse = K.mean(K.square(a – …
