mirror of https://github.com/kritiksoman/GIMP-ML
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77 lines
3.7 KiB
Markdown
77 lines
3.7 KiB
Markdown
## In-painting
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Requires 2 inputs:<br>
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<br>
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[1] Image Layer. <br>
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[2] Mask Layer containing mask of object to be removed. Background should be black (255,255,255) and object should be white (0,0,0). <br>
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## Interpolate-frames
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Requires 3 inputs:<br>
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[1] Image Layer which will be the starting frame. <br>
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[2] Image Layer which will be the ending frame. <br>
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[3] Output Location: Folder where interpolated frames should be saved. <br>
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## De-blur
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Works on currently selected layer as input.
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## De-haze
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Works on currently selected layer as input.
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## De-noise
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Works on currently selected layer as input.
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## Enlightening
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Works on currently selected layer as input.
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## MonoDepth
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Works on currently selected layer as input.
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## Semantic Segmentation
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Works on currently selected layer as input containing any of the following: person, bird, cat, cow, dog, horse, sheep, aeroplane, bicycle, boat, bus, car, motorbike, train, bottle, chair, dining table, potted plant, sofa, and tv/monitor. <br>
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## Face Parsing
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Works on currently selected layer as input containing only portrait image of a person.<br>
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## Face Portrait Generation
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Requires 3 layers as input:
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<br>
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[1] Image Layer containing only the portrait. <br>
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[2] Original Mask Layer obtained by using faceparse on the image layer. <br>
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[3] Modified Mask Layer obtained by duplicating the original mask layer and modifying it using paintbrush tool. <br>
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## Image Super-resolution
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Requires the factor by which the image is to be enlarged as input.<br>
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<br>
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Set "Use as filter" to True if image size is medium/large in size (i.e., >~ 400pixels in height or width), otherwise you might run out of memory.<br>
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## K-means Clustering
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Requires 3 inputs:<br>
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[1] Image Layer. <br>
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[2] Number of clusters/colors in output. <br>
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[3] Use position: if (x,y) coordinates should be used as features for clustering. <br>
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## Deep Image Matting
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Requires 2 layers as input:
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[1] Image Layer <br>
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[2] Trimap Layer: Use RGB as [128,128,128] for boundaries, [255,255,255] for object and [0,0,0] for background. <br>
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Example: <br>
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<br>
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## Deep Image Coloring
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The image should be greyscale but the image mode should be RGB. This can be done from Image->Mode->RGB... <br>
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Requires 2 layers as input:
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<br>
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[1] Image Layer <br>
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[2] Color Mask Layer: A transparent RGB layer (with alpha channel) that contains (local points) dots of size 6 pixels specifying which color should be present at which location.<br>
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Example: <br>
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If the image and color mask layers are set to the same layer containing the image, the local points network will still give prediction. So the color mask layer is optional. |