I just started to work with QGIS. I would like to automatically calculate, for example,
NDMI=(NIR-SWIR)/(NIR+SWIR)=(B08-B11)/(B08+B11)
for Sentinel-2 and other indices that use bands other than the RGB/NIR ones when downloading a batch of Sen2 or Landsat-8 images in QGIS using the SCP plugin.
For this, I need to define a general formula with general names for the bands to be uploaded as a TXT file in the "Band calc" that will work on all the images. I know, for example, that the special name for Sen2 B08 is "#NIR#", but "#SWIR#" does not work for B11, probably because B11 is just one of the SWIR bands available in Sen2.
I couldn't find a list or table containing the special names for Sen2 and Landsat8 bands other than the RGB/NIR ones in the SCP documentation and on the internet. I would be very grateful if someone could post this information.
Luca Congedo, the developer/owner of the SCP plugin, responded by e-mail that: "you can use the band number of the bandset for identifying bands in the band calc. For instance Sentinel-2 band 11 should be "bandset#b9" in the Band calc". In my case, the number of the bandset was 4, because I was downloding only the bands B2, B4, B8 and B11 of Sentinel-2, so I used "bandset#b4" in the formula. It worked perfectly.
Related
I want to use a different language pair at the example provided in TernsorFlow website, Google Colab notebook only picks spanish-english
https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/r2/tutorials/text/nmt_with_attention.ipynb
I tried changing the link to the esp-eng data that download's from it, but that didn't help
How can I try a different language set, without locally setting-up colab, it did mention at the end on that page, that I can try a different language set.
The final note on using a different dataset refers to this website which includes tab-delimited files.
You mainly need to change the values in this cell according to the link to the zip file you need.
# Download the file
path_to_zip = tf.keras.utils.get_file(
'spa-eng.zip', origin='http://storage.googleapis.com/download.tensorflow.org/data/spa-eng.zip',
extract=True)
path_to_file = os.path.dirname(path_to_zip)+"/spa-eng/spa.txt"
You can try other datasets from:
OPUS
WMT
However, in these corpora, the source and target are in two separate files, so you have to adjust the code that extracts pairs, instead of split('\t') it should open two files and get the source and target line by line.
Is there a way to script a pair of dual-EELS SIs so that DM recognises them as siblings (say, for use in the "SI->Align SI by Peak" menu option)?
I have a script which performs a transformation on a pair of dualEELS SIs where the results are given in new images with all the tags copied from the original. The new SIs do not seem to be acknowledged by the SI options as a pair, however. A MWE of how this occurs is below:
image a, b
GetTwoLabeledImagesWithPrompt("Get SI", \
"Get DualEELS SIs", \
"Low-Loss", a, \
"High-Loss", b)
image LL, HL
LL := a.ImageClone()
HL := b.ImageClone()
LL.ShowImage()
HL.ShowImage()
Assuming that the two inputs are real dualEELS SIs. Attempting afterward to run a method like "SI->Align SI by Peak" on the outputs does not recognise the second SI as a sibling.
I suspect that my issue is in properly assigning the four EELS:Dual acquire sibling:UID tags highlighted in the image provided, however I have no idea how (or if) these are accessible from the scripting language.
Thanks in advance for any help you are able to render.
Yes, "siblings" in DigitalMicrograph are recognized by tag-checks and tagging of the Unique Image Id (UID).
Depending on the exact application/plugin, there might be additional tag-checks before a sibling can be accepted (i.e. "is it EELS data?", "is it spatially compatible?", etc.) but he prime-mechanism is using the UID.
A bit of background info
The UID is a set of four long-numbers generated at random whenever a new image data is created, and then subsequently stored with the data. It is "unique" by the assumption that a set of four randomly generated 8-byte longs are "unique".
If you create an image, save it to disc, and open it, the UID will be the same. (It is stored with the data.)
If you ImageClone() an image, it gets a new UID.
If you copy a image file on the hard drive and rename it, it will retain the UID.
Creating and using UIDs
The commands to get an image's UID are described in the F1 help documentation here:
And the example section even has a script showing how one uses UID to "link" data together:
I have a dataset with country names (to and from) which is similar to travel starting country and the destination country.
For example: if the travel is between India to Australia then the country origin will be India and the destination will be Australia.
I have collected the latitude and longitude for both origin and destination place.
Now I want to plot the lat and log for origin and destination country using Qlikview tool.
I'm using Qlikview11 Personal edition.
Two ways to achieve this case:
1. Using GeoQlik extension
Install GeoQlik extension in Qlikview Click to Install GeoQlik
Open GeoQlik extension in Webmode and choose Line Graph.
Add the dimensions as Country Origin and Country Destination
Add the lat and log positions as in below image.
Similarly you can do it for Country Destination.
You can also adjust the line width and color properties also.
Demerit: In GeoQlik trial version, you cant able to save the visualizations.(need to be licensed version to enjoy all the features)
2. Using Line Graph
Ref from : http://qvdesign.wordpress.com/2012/06/22/new-qlikview-chart-type-dynamic-network-flow-charts/
They used static image of world map as background. They created a line graph with X and Y coordinates running axes from 0 to 200 and set as transparent.
Here the fuzzy thing is I don't know how they calculated lat and long positions!
You can use the Qlikview Mapping Extension that installs with the product. See the "Extension Examples.qvw" in the installed examples. Note the instruction on the first sheet that directs you to complete the installation by launching the .qar file. In the Extension Examples is a sample showing how to plot lines and points on a map.
I am entirely new to API, so sorry if the question is silly.
I would like to get all images in a category in Commons let's say X, but exclude those which are also in another one (Y). I do not understand if I can actually do this.
https://commons.wikimedia.org/w/api.php?action=query&list=categorymembers&cmtype=file&cmtitle=Category:X
will get all of them, how to exclude some?
moreover I would like in the result to have the description of the images, not just the name of the file, is that possible?
MediaWiki has - by default - no built-in support for category building and querying intersections. To accomplish this task, extensions or external tools or multiple API queries and result processing is required.
CirrusSearch API
On Wikimedia Commons, like on the whole Wikimedia Wiki farm, CirrusSearch powers filtered search, including search for category intersections and is also available through API (action=query&list=search&srsearch=incategory:A+-incategory:B, this is Category:A minus Category:B).
FastCCI
One of the tools I can recommend (because it's a dedicated high-performance solution and actually running) is fastcci, developed by Daniel Schwen; specifically for Wikimedia Commons, there is already a database maintained and a webservice running but it's possible to set it up for any wiki, provided the tool set has a host to run on and has database access.
Query
Consider the following query URL:
https://fastcci.wmflabs.org/?c1=3302993&c2=15516712&d1=0&d2=0&s=200&a=not&t=js
https://fastcci.wmflabs.org/ - Host Wikimedia Commons fastcci runs on
c1 - ID of category 1
c2 - ID of category 2
d1 - depth of category 1 to search in (fastcci by default considers sub-categories)
d2 - depth of category 2 to search in (fastcci by default considers sub-categories)
s - Number or results to return
o - Offset
a - conjunction
t - connection type (t=js for a JSONP response; otherwise assumes being used as websocket)
Response
fastcciCallback( [ 'RESULT 27572680,0,0|1675043,0,0|27577015,0,0|27577043,0,0|27577106,0,0|27576896,0,0|27576790,0,0|23481936,0,0|17560964,0,0|11009066,0,0', 'OUTOF 10', 'DBAGE 378310', 'DONE'] );
RESULT followed by a | separated list of up to 50 integer triplets of the form pageId,depth,tag. Each triplet stands for one image or category
Resources
Sample client side implementation - to see it in action, just visit any category and next to the Good pictures button in any category page.
Example is FilesOf('Category:Saaleck') - FilesOf('Category:Rapeseed fields in Saxony-Anhalt')
Server application
Presentation on YouTube
Slides
A note on pageIDs
page IDs → page titles: GET /w/api.php?action=query&pageids=page_IDs_separated_by_pipe
page titles → page IDs: GET /w/api.php?action=query&titles=Titles_separated_by_pipe
AFAIK, there is no way to get that directly using the API. But, assuming both categories are reasonably small, you could get all images from both of them and then compute the complement in your code.
To retrieve the description, you can use prop=imageinfo&iiprop=extmetadata&iiextmetadatafilter=ImageDescription.
In the context of your example query, it would look like this:
https://commons.wikimedia.org/w/api.php?action=query&generator=categorymembers&gcmtype=file&gcmtitle=Category:X&prop=imageinfo&iiprop=extmetadata&iiextmetadatafilter=ImageDescription
I have already downloaded the jar files to eclipse.
http://opennlp.apache.org/documentation/1.5.3/apidocs/opennlp-tools/index.html
How do I do the following:
1.) Be able to add my own names and tags.
2.) Be able to get the names and tags that were in the dictionary.
3.) Configure between case sensitive and insensitive.
For example, let's say, I add the name "Mike Smith" with name tag "Author".
If I have text that has that name, it should be able to recognize that its there along with the tag.
Please give actual java code!!!
I have asked a very similar question here:
Is it possible to conduct 'Context Analysis' for precise entity extraction with OpenNLP?
general concensus is that its 2 steps, first to identify if your sentence contains Author, the second to find the name.
I too would like to do it in 1 step (where the analysis of the corpus includes the words within itself as a way to determine the context of the name)