Has anyone used https://github.com/deepinsight/insightface/tree/master/reconstruction/PBIDR for producing face geometry and albedo maps reconstruction. I want to use it to produce the shade, albedo, depth maps on custiom images. Reading the instructions i'm able to produce the ".mtl", ".obl" and ".png"(albedo). And also i've successfully ran the preprocessing steps. But there isn't a clear way mentioned in the repository to produce all the necessary outputs mentioned in the paper.
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So I hope I can clearly communicate my issue. Since I'm fairly new to R and ArcGIS I may miss some obvious things.
Basically, I'm using R to process spatial data to make a canopy height model and detect tree tops. That parts fine. I then make a watershed segment plot using forestTools package, and visually it looks great, but how do I export that as a file I can add into ArcGIS?
I'll copy some of the code that goes into what I'm discussing.
Basically, I just followed this guide's supplemental material to get the tree detection https://www.degruyter.com/document/doi/10.1515/geo-2020-0290/html?lang=en.
With that done, I then used the forestTools package to creat an interesting segmentation polygon grid on the map. https://www.rdocumentation.org/packages/ForestTools/versions/0.2.5/topics/mcws
This is quickly the plotting code to get visualized what I want.
[1]: https://i.stack.imgur.com/7Y0EF.png
This is what the map looks like with those plotted.
[2]: https://i.stack.imgur.com/Kdfl6.png
The layer that I want to bring solo to ArcGIS is that last plot the mcws one. I'll show a pic of that as well here.
[3]: https://i.stack.imgur.com/3PKfk.png
Is there a way that I can export that as a .shp or .tif?
Any help would be wonderful and much appreciated!
Nvmd I figured it out.
What you have to do is use the Raster package to export a shapefile.
raster::shapefile(site2_ttops,"Products/site2plot_ttops.shp")
I am trying to rewrite the code of this paper: https://doi.org/10.1038/s42003-020-0837-0
I have written the code step-by-step based on the instructions mentioned in the methods section. But after clustering, for plotting the clusters by dimplot, I receive a dissimilar plot compared to the same plot in the paper.
I wonder what is the problem? I have tailored every parameter to receive the same plot but it hasn't worked yet.
Graph of the paper
My graph
Please help me to solve this issue.
I would like to use ggmap to plot several data points on top of a koppen-geiger climate map.
The kopper-geiger data and GIS/KMZ maps can be downloaded here:
http://koeppen-geiger.vu-wien.ac.at/present.htm
I've managed to have a code to plot the points on regular maps, obtained through the get_map function but I fail to use other maps such as koppen-geiger.
Any help will be appreaciated!
Your basic problem is that the map you are attmepting to use is an image file that is not georeferenced. So unless you want to go through the unnecessary and probably time consuming process of georeferencing this image yourself, you will be better taking an alternative approach. There are perhaps a few ways to do this. But, unless you have very few data points to overlay on the map which you can place manually using the lat-long grid of the image, then the least painful method will certainly be to redraw the map yourself using the shapefile.
This is not the right place to give you an introductory lesson on GIS, but the basic steps are to
Download shapefile (which is available at the same website as the image you linked)
Project map to desired coordinate system
Plot map, coloring by climate class
Color the ocean layer
Add labels, legend, and graticule, as desired
Overplot with your own climate data, and legend for these.
If you are unsure how to approach any of these steps, then take an introductory course on GIS, and search the Web for instructional materials. You may find this resource useful.
https://cran.r-project.org/doc/contrib/intro-spatial-rl.pdf
I have a code to plot a world map with a meteorological field for one moment (or one measure).
Is it possible to successively plot the map for different moments (for i from 1 to 125) in order to view a sort of video when we run the code?
Yes, look at the animation package.
It can creates an animated gif for you (as well as other tricks). There are live examples you can look at as eg Buffon's needle, a CLT demo and much more.
The package abstracts away some of the OS-dependent layers. If you know the basics, you can of course just call the corresponding tool from the imagemagick project which is likely to be available on OS of choice too.
I recently found this web page Crime in Downtown Houston that I'm interested in reproducing. This is my first learning experience with mapping in R and thus lack the vocabulary and understanding necessary to make appropriate decisions.
At the end of the page David Kahle states:
One last point might be helpful. In making these kinds of plots, one
might tempted to use the map raster file itself as a background. This
method can be used to make map plots much more quickly than the
methods described above. However, the method has one very significant
disadvantage which, if not handled properly, can destroy the entire
purpose of using the map.
In very plain English what is the difference between the raster file
approach and his approach?
Does the RgoogleMaps package have the ability to produce these types
of high quality maps as seen on the page I referenced above that
calls a google map into R?
I ask not because I lack information but the opposite. There's too much and I want to make a good decision(s) about the approach to pursue so I'm not wasting my time on outdated or inefficient techniques.
Feel free to pass along any readings you think would benefit me.
Thank you in advance for your direction.
Basically, you had two options at the time this plot was made:
draw the map as a layer using geom_tile, where each pixel of the image is mapped onto the x,y axes (slow but accurate)
add a background image to the plot, as a purely "cosmetic" annotation. This method is faster, because you can use grid.raster which draws images more efficiently, but the image is not constrained by the axes of the plotting region. In other words, you have to manually adjust the x and y axes limits to make sure that the image corresponds to the actual positions on the plot.
Now, I would suggest you look at the new annotation_raster in ggplot2 v. 0.9.0. It should have the advantage of speed and leaner output files, and still conform to the data space of the plot. I believe that this function, as well as geom_raster and annotation_map did not exist when David made those plots.