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Add CNN Layers and model support #580

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Marsmaennchen221 opened this issue Mar 22, 2024 · 0 comments · Fixed by #645
Closed

Add CNN Layers and model support #580

Marsmaennchen221 opened this issue Mar 22, 2024 · 0 comments · Fixed by #645
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enhancement 💡 New feature or request

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Is your feature request related to a problem?

Add CNN Layers and model support

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The layers should be consistent to the already implemented fnn layer & models

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@Marsmaennchen221 Marsmaennchen221 added the enhancement 💡 New feature or request label Mar 22, 2024
@Marsmaennchen221 Marsmaennchen221 self-assigned this Mar 22, 2024
@github-project-automation github-project-automation bot moved this to Backlog in Library Mar 22, 2024
lars-reimann pushed a commit that referenced this issue May 6, 2024
)

Closes #579, #580, #581 

### Summary of Changes

feat: added `Convolutional2DLayer`, `ConvolutionalTranspose2DLayer`,
`FlattenLayer`, `MaxPooling2DLayer` and `AvgPooling2DLayer`
feat: added `InputConversionImage`, `OutputConversionImageToColumn`,
`OutputConversionImageToTable` and `OutputConversionImageToImage`
feat: added generic `ImageDataset`
feat: added class `ImageSize` and methods `ImageList.sizes` and
`Image.size` to get the sizes of the respective images
feat: added ability to iterate over `SingleSizeImageList`
feat: added param to return filenames in `ImageList.from_files`
feat: added option `None` for no activation function in `ForwardLayer`
feat: added `Image.__array__` to convert a `Image` to a `numpy.ndarray`
feat: added equals check to `OneHotEncoder`
fix: fixed bug #581 in removing
the Softmax function from the last layer in `NeuralNetworkClassifier`
refactor: move `image.utils` to `image._utils`
refactor: extracted test devices from `test_image` to `helpers.devices`

---------

Co-authored-by: megalinter-bot <[email protected]>
@github-project-automation github-project-automation bot moved this from Backlog to ✔️ Done in Library May 6, 2024
lars-reimann pushed a commit that referenced this issue May 9, 2024
## [0.24.0](v0.23.0...v0.24.0) (2024-05-09)

### Features

* `Column.plot_histogram()` using `Table.plot_histograms` for consistent results ([#726](#726)) ([576492c](576492c))
* `Regressor.summarize_metrics` and `Classifier.summarize_metrics` ([#729](#729)) ([1cc14b1](1cc14b1)), closes [#713](#713)
* `Table.keep_only_rows` ([#721](#721)) ([923a6c2](923a6c2))
* `Table.remove_rows` ([#720](#720)) ([a1cdaef](a1cdaef)), closes [#698](#698)
* Add `ImageDataset` and Layer for ConvolutionalNeuralNetworks ([#645](#645)) ([5b6d219](5b6d219)), closes [#579](#579) [#580](#580) [#581](#581)
* added load_percentage parameter to ImageList.from_files to load a subset of the given files ([#739](#739)) ([0564b52](0564b52)), closes [#736](#736)
* added rnn layer and TimeSeries conversion ([#615](#615)) ([6cad203](6cad203)), closes [#614](#614) [#648](#648) [#656](#656) [#601](#601)
* Basic implementation of cell with polars ([#734](#734)) ([004630b](004630b)), closes [#712](#712)
* deprecate `Table.add_column` and `Table.add_row` ([#723](#723)) ([5dd9d02](5dd9d02)), closes [#722](#722)
* deprecated `Table.from_excel_file` and `Table.to_excel_file` ([#728](#728)) ([c89e0bf](c89e0bf)), closes [#727](#727)
* Larger histogram plot if table only has one column ([#716](#716)) ([31ffd12](31ffd12))
* polars implementation of a column ([#738](#738)) ([732aa48](732aa48)), closes [#712](#712)
* polars implementation of a row ([#733](#733)) ([ff627f6](ff627f6)), closes [#712](#712)
* polars implementation of table ([#744](#744)) ([fc49895](fc49895)), closes [#638](#638) [#641](#641) [#649](#649) [#712](#712)
* regularization for decision trees and random forests ([#730](#730)) ([102de2d](102de2d)), closes [#700](#700)
* Remove device information in image class ([#735](#735)) ([d783caa](d783caa)), closes [#524](#524)
* return fitted transformer and transformed table from `fit_and_transform` ([#724](#724)) ([2960d35](2960d35)), closes [#613](#613)

### Bug Fixes

* make `Image.clone` internal ([#725](#725)) ([215a472](215a472)), closes [#626](#626)

### Performance Improvements

* improved performance of `TabularDataset.__eq__` by a factor of up to 2 ([#697](#697)) ([cd7f55b](cd7f55b))
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