DataAugmentation | Image data augmentation tool for training of image | Machine Learning library

by takmin C++ Version: Current License: No License

X-Ray Key Features Code Snippets(4)Community Discussions(4)Vulnerabilities Install Support

kandi X-RAY | DataAugmentation Summary

DataAugmentation is a C++ library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow applications. DataAugmentation has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Image data augmentation tool for training of image recognition algorithm

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DataAugmentation has a low active ecosystem.

It has 69 star(s) with 23 fork(s). There are 8 watchers for this library.

It had no major release in the last 6 months.

DataAugmentation has no issues reported. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of DataAugmentation is current.

Quality

DataAugmentation has no bugs reported.

Security

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

License

DataAugmentation 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

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

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DataAugmentation Key Features

No Key Features are available at this moment for DataAugmentation.

DataAugmentation Examples and Code Snippets

Regular expressions

pypi

Lines of Code : 11

License : No License

Copy

r'(?:id|ID)=(?P\d+)'


r'(id|ID)=(?P\d+)'


some fancy title


title = self._search_regex(
    r']+class="title"[^>]*>([^<]+)', webpage, 'title')


title = self._search_regex(
    r']+class=(["\'])title\1[^>]*>(?P[^<]+)

Create a task from a given dataset id .

python

Lines of Code : 157

License : Non-SPDX (Apache License 2.0)

Copy

def _from_dataset_id(processing_mode,
                     service,
                     dataset_id,
                     element_spec,
                     job_name=None,
                     consumer_index=None,
                     num_consumers=N

Return the sign of x .

python

Lines of Code : 42

License : Non-SPDX (Apache License 2.0)

Copy

def sign(x, name=None):
  r"""Returns an element-wise indication of the sign of a number.

  `y = sign(x) = -1 if x < 0; 0 if x == 0; 1 if x > 0`.

  For complex numbers, `y = sign(x) = x / |x| if x != 0, otherwise y = 0`.

  Example usage:

Returns True if arg is a list .

python

Lines of Code : 19

License : Non-SPDX (Apache License 2.0)

Copy

def _should_pack(arg):
  """Determines whether the caller needs to pack the argument in a tuple.

  If user-defined function returns a list of tensors, `nest.flatten()` and
  `ops.convert_to_tensor()` and would conspire to attempt to stack those tens

Community Discussions

Trending Discussions on DataAugmentation

CNN to output percentage of 2 class

Keras Image Preprocessing

how to fix 'TypeError: 'numpy.ndarray' object is not callable'

Unable to get the output image

QUESTION

CNN to output percentage of 2 class

Asked 2020-Aug-03 at 11:14

i'm a beginner in the argument. I have this problem: I have to classify the percentage of 2 class in each frame of a video. I created a small dataset with about 500 images (250 of each class), and a CNN with these layers:

...

ANSWER

Answered 2020-Jul-16 at 16:53

Since, yours is a binary classification, go with sigmoid. Softmax is for multi-class (>2).
It is always better to use transfer learning. Go with VGG16, ResNet, Inception and others.
Yes, in case of small datasets, data augmentation helps a lot.
You need to use one neuron in the last layer rather than 2. Since, in one neuron, if value is greater than 0.5, it will be considered as class 1 otherwise 0. If you want to stick with two neurons, then, for getting your answer, you should take np.argmax of the prediction, in the example you have given, pred = [9.999e-1 4.444e-5], the predicted class is 0, as pred[0] > pred[1].

Source https://stackoverflow.com/questions/62938017

QUESTION

Keras Image Preprocessing

Asked 2019-May-22 at 11:12

My training images are downscaled versions of their associated HR image. Thus, the input and the output images aren't the same dimension. For now, I'm using a hand-crafted sample of 13 images, but eventually I would like to be able to use my 500-ish HR (high-resolution) images dataset. This dataset, however, does not have images of the same dimension, so I'm guessing I'll have to crop them in order to obtain a uniform dimension.

I currently have this code set up: it takes a bunch of 512x512x3 images and applies a few transformations to augment the data (flips). I thus obtain a basic set of 39 images in their HR form, and then I downscale them by a factor of 4, thus obtaining my trainset which consits of 39 images of dimension 128x128x3.

...

ANSWER

Answered 2018-Sep-25 at 03:51

Yes you can use keras preprocessing function. Below some snippets to help you...

Source https://stackoverflow.com/questions/52462058

QUESTION

how to fix 'TypeError: 'numpy.ndarray' object is not callable'

Asked 2019-Apr-07 at 06:45

I'm trying to resize a 1920X1080 and copy the grayscale onto a white background of size 128X32. But I'm getting this error:

...

ANSWER

Answered 2019-Apr-07 at 06:45

Typically, this problem occurs when you're trying to call something from numpy as a function() instead of it's type[]. For reference, see the accepted comment here why numpy.ndarray is object is not callable in my simple for python loop

To solve this issue, try changing some of the parenthesis to brackets on line 32, since parenthesis are for functions, and brackets are for data types. I think one of these combinations will work, but I could still be wrong.

cv2.imshow('Greyscale_Stretched', target['float32'])
cv2.imshow['Greyscale_Stretched', target('float32')]
cv2.imshow['Greyscale_Stretched', target['float32']]

Hope that helps.

Source https://stackoverflow.com/questions/55556155

QUESTION

Unable to get the output image

Asked 2019-Apr-03 at 16:02

i'm fairly new to python and openCV and i have been experimenting with some code that i found online. so thank you in advance for helping although im using the imshow() function defined in opencv im unable to display the image

...

ANSWER

Answered 2019-Apr-03 at 16:02

Just tested your code. You need to call the main() function somewhere. Since you haven't done that, the function is not executed.

simply add main() at the end of the code, and everything works.

Source https://stackoverflow.com/questions/55497715

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

Vulnerabilities

No vulnerabilities reported

Install DataAugmentation

You can download it from GitHub.

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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