I’m training a tensorflow model on image dataset for a classification task, we usually provide the training set and validation set to the model.fit method, we can later output model convergence graph of training and validation. I want to do the same with the testing set, in other words, I want to get the accuracy and loss of my model
Tag: image-classification
MSINT – Image classification – value error incompatible shape
I am beginning with image classification using keras. Tried a simple minst dataset for detecting numbers in images. Ran the model. However I wanted to test the model on my own dataset and facing some problem. Error: WARNING:tensorflow:Model was constructed with shape (None, 28, 28) for input KerasTensor(type_spec=TensorSpec(shape=(None, 28, 28), dtype=tf.float32, name=’flatten_input’), name=’flatten_input’, description=”created by layer ‘flatten_input'”), but it was
PIL.UnidentifiedImageError: cannot identify image file <_io.BytesIO object
I am trying to train my model (Image classification) using Tensorflow. I keep getting an error when I try to run the following cell: Error is: I tried changing from loss=’categorical_crossentropy’ to loss=’binary_crossentropy’ but still the issue persists. I wish to train the model but the Epoch keeps getting stuck. Edit: The train generator function and where it is used