I am looking for a parametric image generator that can for a specified parameters produce different images of the same object (e.g. lobster images where each image contains the same lobster of different fatness).
I need to be able to control parameters (e.g. set lobster's fatness). The image and the object it represents could be basically anything.
Is there any existing library/software that produces such images?
Blender,
Google Sketchup,
Autocad,
3D Canvas,
MeshLab (just for the geometry part)
Related
From Apples documentation I read:
An alternative to creating bitmap images is to use template images or symbol images instead. Template images specify the shape you want to draw, but not the associated color information. Symbol images are similar to template images but are vector based, so they scale to different sizes. Both types of images simplify the process for supporting Dark Mode. They also reduce the number of image assets you must ship with your app.
Do I understand this correct that I can not use a vector based symbol image set as a replacement for bitmap but scalable?
Update
My situation:
I've an Image Set in my iOS project. There I can add three bitmaps for the three scaling options iOS devices support. Those images must be of type *.png
Now I would like to replace those three bitmaps with a single vector graphic file *.svg. This seems not possible. If I want to use vector graphic images I've to add another asset type called "symbol image set" (Xcode -> Editor -> Add Assets -> New Symbol Image Set).
So far so good but now my question. Those "symbol image set" assets only the the shape but not the color information into account. That's why I would like the "old" way where the color information is taken into account but the file being a vector graphics file (*.svg).
You don't actually need a Symbol Set for what you are trying to achieve.
All you need is a vector image in pdf format, marking it as Single Scale
Then, you can mark the asset as template (meaning you can tint it with any color) or original if you want to retain its original colors.
Finally, note that although you supply vector images, Xcode by default will produce png versions for all scales behind the scenes. If you need to preserve the vector data (which can help in some cases where you need to upscale) you can enable Preserve Vector Data as well.
I am following the Semantic Segmentation Examples tutorial by MathWorks.
I understand that I can load pixel labeled images
pxDir = fullfile(dataDir,'buildingPixelLabels');
Define the class names.
classNames = ["sky" "grass" "building" "sidewalk"];
Define the label ID for each class name.
pixelLabelID = [1 2 3 4];
and create a pixelLabelDatastore.
pxds = pixelLabelDatastore(pxDir,classNames,pixelLabelID);
But, how do I create a custom pixel labelled image where every pixel value represents the categorical label of that pixel?
I would then proceed by writing:
pxDir = fullfile(dataDir,'myCustomPixelLabels');
If I understood correctly, imageDatastore holds the actual image and not the pixel labels for that image.
EDIT:
On my system pxDir points to 'C:\Program Files\MATLAB\R2017a\toolbox\vision\visiondata\buildingPixelLabels'. Since I am on Matlab2017a so this example is not included by default, and I cannot compare or view the file to get a better understanding of what I need to do to reproduce this example.
The answer can be found here.
Matlab 2017a
Go to the APPS tab, and search for Image Labeler, or Training Image Labeler
Click on Add Images to add your training images.
Click on Add ROI Labels to add class names for the regions of interest.
Proceed to select the regions of interest manually from the uploaded images.
Once areas are selected, the data can be exported to workspace as a Ground Truth object.
When it comes to adding an icon to my app, there're two main options:
IMAGE ASSET || IMAGE VECTOR
What are the differences between the Image Asset and Vector Asset? What makes them different?
According to Android User Guide :
Image Asset Studio helps you create various types of icons at different densities and shows you exactly where they'll be placed in your project. It includes tools for adjusting your icons and adding backdrops, all while displaying the result in a preview pane, so they appear exactly as you intended.
Vector Asset Studio adds a vector graphic to the project as an XML file that describes the image. Maintaining one XML file can be easier than updating multiple raster graphics at various resolutions.
When you create an image asset it will automatically create a vector graphic that describes that image as an xml file in the drawable..thus you can maintain that one xml file of your image rather than update it in multiple graphics and resolutions.
When you create a vector asset you simply create an xml file that describes an image/graphic in the drawables.
Is there any library which allows reading PSD with vector paths? E.g. gwenview and gimp seem to rasterize fonts and paths. The same issue with libraries like
https://github.com/kmike/psd-tools
Does PSD has rasterize data for each layer itself or it's just about how libraries work?
As for text layer - PSD contains both rasterized data and text settings. Therefore, you can use already rendered text or draw your own.
There is also a merged image, which contains render result of all layers but it is optional.
It looks like libpsd has path support.
I want to use a satellite image as a background for plotting polygons, points, etc ... using ggplot.
I managed to use google earth imagery with the ggmap function but I'd rather have a false colour composite from my own image as a background. As this image is rather heavy (>2GB) I prepared the false colour composite in Arcmap and exported it as .jpeg with coordinates attached (.jgw) to reduce resolution.
The problem is how I can add this image as a (georeferenced base) layer in ggplot? When importing the jpeg (938 rows and 1743 columns) using readGDAL, a SpatialGridDataFrame is created with the three (RGB) bands.
All help appreciated
The core piece to a ggmap object is just a matrix of colors with some attributes (use the str function on one).
You should be able to read in your jpeg file and create a raster from it, then just change the attributes to match those of a ggmap object (mainly just the class and the bounding box information). You should then be able to use it with the ggmap function.