It's weird, I wrote a functioning program on a Jupyter notebook and I wanted to have it in a normal python file with VSCode aswell. However, while copying and p
I am doing classification of citrus leaves dataset. I came up with a very basic model and ran it in Jupyter notebook on my machine, using anaconda. Exact same m
I'm having some trouble with a pretty basic model. Am unable to create a pre-processing layer that simply normalizes all features. It is likely that my concept
Image classification Problem I have two classes of images. Fake Real Dataset splitting detail is below. Total Training FAKE Images 3457 Total
I'm too new with tensorflow and keras, actually I'm trying first to install it correctly. I used Anaconda to make it easier. My question is probabily related to
I am having trouble loading large model after saving. have tried all below saveing methods: tf.saved_model.save(model, model_save_path) model.save(model_save_pa
I am trying out Keras (2.8.0) autotuner for a regression problem. Here is my code: import pandas as pd from tensorflow import keras from keras import layers, lo
I'm using Anaconda Python 2.7 on windows 10 I was planning on doing Keras visualization so (whilst spyder was open) I opened the Anaconda command prompt and pi
I am trying to do several imports from the keras library. I am doing this on a Jupyter notebook using an Anaconda installed Python. I have used keras before fin
I'm trying to get a basic segmentation model going before making major tweaks and no matter how simple I make it I receive this error. I'm working on Collaborat
I am trying to create a dense neural network where my input is a sparse 3d matrix. When converted to a dense matrix the shape is (2, None, n) (where n is a numb
The input shape in the first Conv2D layer is supposed to be (100, 100, 1) however the output is (None, 98, 98, 200). I understand what 200 and None determine bu
I'm following some lectures from lynda.com about deep learning using Keras-TensorFlow in a PyCharmCE enviroment and they didn't have this problem. I get this er
I want to predict the center of the pupil from an image. so I used a CNN with 3 Dence layer. so the input is an image and the output is a coordinate (X,Y). my m
How do I use keras function fit_generator() to train and simultaneously save the model weights with lowest validation loss?
Recently I tried to convert mask rcnn in this repository from tensorflow 1 to tensorflow 2. After re-writing the codes and when I run sample "shape" and execute
I am using the headsegmentation dataset. A single mask looks like this All mask images are a single channel. This is my code: image_size = 512 batch = 4 labels
I have a Mac with an M1 Pro chip. I was able to install keras/tensorflow with tensorflow-metal PluggableDevice. My image classification model runs smoothly on m
So basically, I am fairly new to programming and using python. I am trying to build an ANN model for which I have to use Tensor flow, Theano and Keras library.
I have a bunch of poor quality photos that I extracted from a pdf. Somebody I know has the good quality photo's somewhere on her computer(Mac), but it's my unde