I have some thermal images with a temperature scale associated.
I'm trying to get for each temperature value the corresponding pixel color.
I've isolated the scales and obtained some jpg files like this one :
Temperature Scale
The final goal is to find any hot spot with a temperature value higher than 80°, so I can focus only on max values of each scale.
This is an example of my whole image.
Jpg image
Related
Some of the folks on my team, including myself, find it pretty disorienting that in a Bokeh scatter plot, say using the circle method, that for an initial autoscale fit of the data on the figure we can dial in a reasonable size for our data, using for example something like plot.circle( x , y , size=3 )
However when we interactively zoom into our data the glyph sizes as displayed are invariant to the zoom. Is there a way to have them scale proportionally to the zoom we've dialed into? Something akin to an vector graphics interaction (eg svg). If memory serves me right matlab figures and matplotlib figures should maintain zoom proportionality behavior. To demonstrate the behavior we're seeing consider the first image and the red box I approximately zoom into on the second image.
Just as a quick demo using Powerpoint to illustrate the sort of desired behavior...
For circles, set the radius kwarg instead of the size value. (There similar, glyph-specific values for the other glyph-types).
i.e.:
plot.circle(x=[1,2,3], y=[1,2,3], radius=0.5)
size is always rendered in screen coordinates (pixels), but radius and the related properties are computed in data coordinates and should change in magnitude with zooming.
Here's a good demo by Bryan Van de Ven showing the difference between pixel coordinates (size) and data coordinates (radius) given in this conference talk:
Intro to Data Visualization with Bokeh - Part 2 - Strata Hadoop San Jose 2016
... the point is all of these attributes can be vectorized. We could
for instance say size equals you know 2, 4, 6, 8, 10, and now the size
is modulated right. So we have one that has size 2 and one that has
size 4. Size is usually in pixels, radius is usually in data dimension
units. But all the other ones here as well all the colors, all the
visual attributes can be vectorized in this way. You can either give
them a single value as we've done for instance with the line fill
color, or you can give them a vector of values in which case all of
the things are different.
So next exercise here you go to this
notebook this is that second notebook "02 - plotting" it is to try to
create the same example but now set the radius instead of the size and
sort of see what's the difference if you set if you set radius instead
of size.
I am trying to write a R-Script that saves a series of Maps with Dots on it. For the Map I used ggmap and geom_point for the Dots. There is a map for each day in a certain time range.
The size of the Dots depends on a certain variable, but I have a problem scaling them. I am supposed to create later an animation of all the maps changing the dots' size through time, that means that I need a global scale for the dimension of the dots, spacing from the smallest value (zero) to the biggest value of that variable (the global maximum). In the most maps the biggest value is not reached.
I tried with:
scale_size_area(max_size = max(my_variable))
because scale_size_area allows to plot very tiny dots for the 0 values. I was hoping that the so written code would scale the dots correctly, using the global maximum as maximum size, but it doesn't seem to work. Every map has still a locally biggest dot that has the same size of any biggest dot in every map. Here's an example where two points with different values have the same size:
I hope I could explain my problem. I'd be glad to hear some suggestion.
To set the maximum and minimum values in a scale (size or otherwise), use limits:
scale_size_area(limits = c(NA, max(your_varible))
NA computes the minimum
I want to increase pixel density per unit area on every zoom operation in 'QPixmap'.
To increasing pixel density I create pixmap on every zoom according to the rectangle get from sceneboundingrect() but I think it does not increase the pixel density
The QPixmap is a raster image, that means a finite amount of pixels, making it bigger will not make it clearer (as it does on CSI).
You will need a considerably bigger / larger resolution image to begin with, then you will downsample it when you render it "un-zoomed" and the more you zoom in the closer you render it to its original size.
A-Frame sky default radius= 5,000
diameter=10,000
So if I was to create a equirectangular image in photoshop or other program, which size should I use? 10,000 x 5,000 pixels or 10,000 x 5,000 meters?
It doesn't matter much. The exported size of the image only counts for resolution. You can balance between having a higher-resolution image or saving on file size over the network. Keep it at a minimum resolution that you are satisfied with.
Just wondering why we need the overlay and when we will need it?
I have a Scout image with overlay, what do these dots mean and what do these numbers or fractions mean?
How these numbers are drawn on the image?
DICOM standard allows two specific types of overlays (graphics and ROI) along with the image and overlays are stored as 1-bit image in Overlay Data (60XX, 0050) attribute. A dataset can have up to 16 separate overpay planes (using the repeating groups encoding).
The overlay plane that represents region of interest (ROI) will have value of “R” for Overlay Type (60xx, 0040) attribute and ROI Area (60xx, 1301), ROI Mean (60xx,1302) and ROI Standard Deviation (60xx, 1303) can be used for the corresponding values of ROI. All bits representing ROI will have a value of 1 that represents the pixels under the boundaries of the actual image data.
Graphic Overlay will have value of “G” in Overlay Type (60xx, 0040) attribute and it is used for expressing reference marks (reference line), graphic annotation, or bitmap text etc. Again, all visible values in an overlay plane are set to 1.
The Overlay Rows (60xx, 0010) and Overlay Columns (60xx,0011) specifies the width and height of the overlay plane. Overlay Bits Allocated is always 1 and Overlay Bit Position is 0 (it was used in previous version and usage has been retired). Overlay Origin (60xx, 0050) is used to described the first overlay point with respect to the pixel in the image and 1\1 represents upper left pixel of the image.
Overlays can be used to display any data over an image. You could, for example, allow users to make annotations or graphics marks. You cannot mark the original data, so the overlay is stored in a separate layer.
In your case, the creator of the overlay should explain its meaning.
The meaning of the overlay is:
i.e. 2/16 -> Series number 2 and slice number 16