mnist | MNIST data set parser https : //crates.io/crates/mnist | Dataset library

by davidMcneil Rust Version: Current License: No License

X-Ray Key Features Code Snippets(3)Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | mnist Summary

mnist is a Rust library typically used in Artificial Intelligence, Dataset applications. mnist has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

A crate for parsing the MNIST and Fashion MNIST data set into vectors to be used by Rust programs.

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Quality

Security

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Support

mnist has a low active ecosystem.

It has 13 star(s) with 5 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 3 have been closed. On average issues are closed in 48 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of mnist is current.

Quality

mnist has no bugs reported.

Security

mnist has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

mnist does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

mnist releases are not available. You will need to build from source code and install.

Installation instructions are not available. Examples and code snippets are available.

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mnist Key Features

No Key Features are available at this moment for mnist.

mnist Examples and Code Snippets

Train mnist model .

python

Lines of Code : 51

License : Non-SPDX (Apache License 2.0)

Copy

def main(strategy):
  """Trains an MNIST model using the given tf.distribute.Strategy."""
  # TODO(fengliuai): put this in some automatically generated code.
  os.environ[
      'TF_MLIR_TFR_LIB_DIR'] = 'tensorflow/compiler/mlir/tfr/examples/mnist'

Download a file from Google MNIST .

python

Lines of Code : 17

License : Non-SPDX (Apache License 2.0)

Copy

def download(directory, filename):
  """Download (and unzip) a file from the MNIST dataset if not already done."""
  filepath = os.path.join(directory, filename)
  if tf.gfile.Exists(filepath):
    return filepath
  if not tf.gfile.Exists(directory):

Download the MNIST dataset .

python

Lines of Code : 17

License : Permissive (MIT License)

Copy

def download_mnist(path):
    """ 
    Download and unzip the dataset mnist if it's not already downloaded 
    Download from http://yann.lecun.com/exdb/mnist
    """
    safe_mkdir(path)
    url = 'http://yann.lecun.com/exdb/mnist'
    filenames = [

Community Discussions

Trending Discussions on mnist

mnist CNN ValueError expected min_ndim=4, found ndim=3. Full shape received: [32, 28, 28]

How to fix the following error in Classification dataset MNIST :-

Difficulty with stacking MNIST and Fashion_MNIST

No gradients provided for any variable - LSTM autoencoder

How do I build my own handwritten digits dataset

How to extract the hidden vector (the output of the ReLU after the third encoder layer) as the image representation

AttributeError: Layer mnist_model_35 has no inbound nodes. Tensorflow keras subclassing API

After applying torchvision.transforms on mnsit dataset, how to view it using cv2_imshow?

Manual Calculation of tanh in Tensorflow Keras Model is resulting in Nan

Autoencoder give wrong results (Not as shown in basic examples)

QUESTION

mnist CNN ValueError expected min_ndim=4, found ndim=3. Full shape received: [32, 28, 28]

Asked 2021-Jun-13 at 16:35

I define the model definition as follows.

...

ANSWER

Answered 2021-Feb-16 at 05:27

By seeing your error, I think you probably didn't add the batch axis in the training set i.e [batch, w, h, channel]. Here is the working code

DataSet

Source https://stackoverflow.com/questions/66218328

QUESTION

How to fix the following error in Classification dataset MNIST :-

Asked 2021-Jun-13 at 08:51

I assigned mnist as:

...

ANSWER

Answered 2021-Jun-13 at 08:51

It seems your X is pandas.DataFrame and in DataFrame code X[0] searchs column with name 0 but X doesn't have it.

If you want to get row with number 0 then you may need X.iloc[0]

BTW:

When I run

Source https://stackoverflow.com/questions/67955435

QUESTION

Difficulty with stacking MNIST and Fashion_MNIST

Asked 2021-Jun-10 at 03:15

I know it's basic and too easy for you people, but I'm a beginner who needs your help. I'm struggling to make binary classifier with CNN. My final goal is to check accuracy over 0.99

I import both MNIST and FASHION_MNIST to identify if it's number or clothing. So there are 2 category. I want to categorize 0-60000 as 0, and 60001-120000 as 1. I will use binary_crossentropy.

but I dont know how to start from the beginning. How can I use vstack hstack at first to combine MNIST and FASHION_MNIST?

This is how I tried so far

...

ANSWER

Answered 2021-Jun-10 at 03:15

First of all

They're images so better treat them as images and don't reshape them to vectors.

Now the answer of the question. Suppose you have mnist_train_image and fashion_train_image, both have (60000, 28, 28) input shape.

What you want to do is consist of 2 parts, combining inputs and making the targets.

First the inputs

As you've already wrote in the question, you can use np.vstack like this

Source https://stackoverflow.com/questions/67913601

QUESTION

No gradients provided for any variable - LSTM autoencoder

Asked 2021-Jun-09 at 19:28

I'm trying to build an LSTM encoder. I'm testing it on the MNIST dataset to check any errors before using it on my actual dataset. My code:

...

ANSWER

Answered 2021-Jun-09 at 19:28

You need to pass x_train and y_train into the fit statement.

Source https://stackoverflow.com/questions/67909447

QUESTION

How do I build my own handwritten digits dataset

Asked 2021-Jun-09 at 09:37

I have a set of images of numbers that go from 0 to 20 with intermediate classes(0,25 / 0,5 / 0,75). Each number will be defined as a class of its own. I have 22 images per class.

These images will be used for training and testing on a convolutional neural network for classification. I'm not worried about accuracy, it's only a proof of concept so I realise that the dataset is too small for any real reliable outcome. Like I said, it's only meant as a proof of concept.

EDIT: As suggested by @Kaveh, I checked out ImageDataGenerator.flow_from_directory

As far as I could tell, this is used to increase your dataset size using data augmentation. However, what I'm asking is, now that I have these images set in different folders (22 images per folder, each folder making a class) how do I use them. I've always been loading one file that makes up the dataset (example: mnist; through keras). I've never used my own data and therefore, have no idea what the next step is.

...

ANSWER

Answered 2021-Jun-09 at 04:13

organize your directories as shown below

Source https://stackoverflow.com/questions/67893409

QUESTION

How to extract the hidden vector (the output of the ReLU after the third encoder layer) as the image representation

Asked 2021-Jun-02 at 17:17

I am implementing an autoencoder using the Fashion Mnsit dataset. The code for the encoder-

...

ANSWER

Answered 2021-Jun-02 at 17:17

I recommend to use Functional API in order to define multiple outputs of your model because of a more clear code. However, you can do this with Sequential model by getting the output of any layer you want and add to your model's output.

Print your model.summary() and check your layers to find which layer you want to branch. You can access each layer's output by it's index with model.layers[index].output .

Then you can create a multi-output model of the layers you want, like this:

Source https://stackoverflow.com/questions/67770595

QUESTION

AttributeError: Layer mnist_model_35 has no inbound nodes. Tensorflow keras subclassing API

Asked 2021-Jun-01 at 11:02

I'm doing keras subclassing with the mnist dataset. I was able to make it with Sequantial and Functional api's. But now when i call model.fit() on my subclass i get this error:

...

ANSWER

Answered 2021-Jun-01 at 10:56

You are lacking the input_shape on your first layer:

Source https://stackoverflow.com/questions/67787156

QUESTION

After applying torchvision.transforms on mnsit dataset, how to view it using cv2_imshow?

Asked 2021-Jun-01 at 10:39

I am trying to implement a simple GAN in google collaboratory, After using transforms to normalize the images, I want to view it at the output end to display fake image generated by the generator and real image side by in the dataset once every batch iteration like a video.

...

ANSWER

Answered 2021-Jun-01 at 10:39

Problem 1

Assuming torch_image is a torch.FloatTensor of shape (C x H x W) in the range [0.0, 1.0]:

Source https://stackoverflow.com/questions/67782927

QUESTION

Manual Calculation of tanh in Tensorflow Keras Model is resulting in Nan

Asked 2021-May-31 at 09:48

Please find the below TF Keras Model in which I am using tanh activation function in the Hidden Layers.

While the value of Logits are proper, the values that are calculated by implementing the tanh function manually is resulting in Nan.

It may be because of the Runtime Warnings shown below:

/home/abc/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:76: RuntimeWarning: overflow encountered in exp

/home/abc/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:76: RuntimeWarning: invalid value encountered in true_divide

Complete reproducible code is mentioned below:

...

ANSWER

Answered 2021-May-31 at 09:48

Normalizing resolves the issue of overflowing:

Source https://stackoverflow.com/questions/67767519

QUESTION

Autoencoder give wrong results (Not as shown in basic examples)

Asked 2021-May-31 at 06:56

I'm have studied about Autoencoder and tried to implement a simple one.
I have built a model with one hidden layer.
I Run it with mnist digits dataset and plot the digits before the Autoencoder and after it.
I saw some examples which used hidden layer of size 32 or 64, I tried it and it didn't gave the same (or something close to) the source images.
I tried to change the hidden layer to size of 784 (same as the input size, just to test the model) but got same results.

What am I missing ? Why the examples on the web shows good results and when I test it, I'm getting different results ?

...

ANSWER

Answered 2021-May-31 at 06:56

Try to change the optimizer. I changed it to adam and got:

Source https://stackoverflow.com/questions/67767703

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install mnist

You can download it from GitHub.
Rust is installed and managed by the rustup tool. Rust has a 6-week rapid release process and supports a great number of platforms, so there are many builds of Rust available at any time. Please refer rust-lang.org for more information.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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