kps | Ondokuz Mayıs Üniversitesi Kimlik Paylaşım Sistemi Ruby | Application Framework library
kandi X-RAY | kps Summary
kandi X-RAY | kps Summary
Bu gem Ondokuz Mayıs Üniversitesi BİDB tarafından sunulan kimlik paylaşım sistemin ruby istemcisidir.
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Top functions reviewed by kandi - BETA
- Initialize new id
- Checks if the identity is valid
- Gets information about the application .
- Builds the address .
- Returns true if the email is valid
- The address address for this address .
- Checks if the number is legit
- Return true if this number belongs to another account
- Check if the address is valid for this domain .
kps Key Features
kps Examples and Code Snippets
Community Discussions
Trending Discussions on kps
QUESTION
I have a react component
...ANSWER
Answered 2021-Jun-05 at 15:20Why do you need a state here? Can't you just do agreementInfos[index].agreement_scan_copy = res.data.data.url;?
QUESTION
I'm using SIFT feature detector in OpenCV 4.5.2. By tuning the nOctaveLayers parameter in cv::SIFT::create(), I get these results from detectAndCompute():
To my understanding, there should be less computation with fewer octave layers, but why SIFT costs significantly more time with only 1 octave layer?
I also tested detect() and compute() separately, and they both cost more time when nOctaveLayers is 1, which confuses me a lot.
The test image is here (from TUM open dataset). Thanks ahead for any help.
[Edit for @Micka] My test code:
...ANSWER
Answered 2021-May-13 at 12:13After hours of profiling, I finally found out the reason: GaussianBlur.
The pipeline of SIFT algorithm is:
- Create initial image: convert data type of source image to
float, double the resolution, and doGaussianBlur(sigma=1.56) - Build gaussian pyramid
- Find key points: build DoG pyramid and find scale space extrema
- Calculate descriptors
The num of octaves is calculated according to image resolution (see here). And nOctaveLayers controls num of layers (nOctaveLayers + 3 for GaussianPyramid) in each octave.
Indeed, when nOctaveLayers increases, nums of layers and keypoints both increase. As a result, time cost of step 3 & 4 increases. However, in parallel computation, this time increment is not very remarkable (several milliseconds).
In contrast, the step 2 costs more than half of the total time. It costs 25.27 ms (in 43.49 ms) when nOctaveLayers is 3, and 51.16 ms (in 63.10 ms) when nOctaveLayers is 1. So, why is this happening?
Because the sigma for GaussianBlur() increases faster when layers are fewer, and it's critical for the time consumed by GaussianBlur(). See test below:
QUESTION
I have a react component where I submit a form using formik
...ANSWER
Answered 2021-May-10 at 14:33 function nonEmptyObject(obj: any) {
for (const propName in obj) {
if (
obj[propName] === null ||
obj[propName] === undefined ||
obj[propName] === ""
) {
delete obj[propName];
}
}
return obj;
}
if (values.key_personnel) {
reqbody.key_personnel = values.key_personnel;
}
if (values.category_head) {
reqbody.category_head = values.category_head;
}
if (values.bdm) {
reqbody.bdm = values.bdm;
}
if (values.kam) {
reqbody.bdm = values.kam;
}
if (values.vm) {
reqbody.vm = values.vm;
}
const finalPayload = nonEmptyObject(reqbody);
const res = await createShop(finalPayload);
console.log({ finalPayload });
console.log({ res });
QUESTION
Using tensorflow 2.4.1
When I run my program, I'm getting this error and can't use my gpu.
I'm using CUDA 11.0, cudnn 8.0
ANSWER
Answered 2021-Feb-07 at 18:08watch this video to solve this problem,
this file not found error arises due to the missing of Microsoft visual studio C++ reproducible file in the CUDA folder.
additional;
with the PyTorch in conda environment, there is no addition CUDA and Cudnn installation, because after type conda install pytorch, conda installs both CUDA and cudnn into that conda environment.
QUESTION
I have an ASCII file which looks like this (the file is large, so pasting only partial contents):
...ANSWER
Answered 2020-Nov-23 at 14:42Your code does exactly what you specified it to do. Takes an input stream and loads sizeof(frame_t) bytes into your uf. One thing to note is that your file/stream is read from "left to right", "byte by byte", so first two bytes (beacause you specified uint16_t) that you will load from ffff ffff ffff ffff 0064 000a 000a 000c ... into frame_t.kps will be ffff and not 000c. Good way to investigate further is to setup few breakpoints and debug your code step by step. You will learn important debugging technique and learn more about how your code works.
On a side note, I'm surprised you don't get stack overflow exception. That struct is huge.
QUESTION
I have a large list of data frames with different dimensions. The dimensions of my real data are too big, so I create a new list (myList) for an instant as follow:
...ANSWER
Answered 2020-Nov-05 at 21:47For each data frame you can find the number of columns with ncol and then the position of the Event column with the which function. For example with mtcars assume the wt column is the "Event" column.
QUESTION
ORB doesn't find keypoints near the edge of an image and I don't understand why. It seems worse that SIFT and SURF and I would expect the opposite.
If I understand correctly then SIFT/SURF use a 16x16 and 20x20 square block respectedly around the test-point so I would expect them not to find keypoints 8 and 10 pixels from an edge. FAST/ORB uses a circle of diameter 7 around the test-point so I expected it to find keypoints even closer to the edge, perhaps as close as 4 pixels (though I think the associated algorithm, BRIEF, to describe keypoints uses a larger window so this would remove some keypoints).
An experiment makes nonsense of my prediction. The minimum distance from the edge in my experiments vary with the size and spacing of the squares but examples are
- SIFT .. 5 pixels
- SURF .. 15 pixels
- ORB .. 39 pixels
Can anyone explain why?
The code I used is below. I drew a grid of squares and applied a Gaussian blur. I expected the algorithms to latch onto the corners but they found the centres of the squares and some artifacts.
...ANSWER
Answered 2020-Aug-31 at 09:26Usually, keypoints at the edge of the image are not useful for most applications. Consider e.g. a moving car or a plane for aerial images. Points at the image border are often not visible in the following frame. When calculating 3D reconstructions of objects most of the time the object of interest lies in the center of the image. Also the fact you mentioned, that most feature detectors work with areas of interest around pixels is important since these regions could give unwanted effects at the image border.
Going into the source code of OpenCV ORB (848-849) uses a function with an edgeThreshold that can be defined using cv::ORB::create() and is set to a default value of 31 pixels. "This is size of the border where the features are not detected. It should roughly match the patchSize parameter."
QUESTION
I have a list of 16 data frames with 65 rows and 225 columns (e.g., df1). I want to add a column (Time) to all of these data frames from the column of another data frame (e.g., df2) with 265 rows and 4 columns when they have the match ID. Let clarifying the problem by the following reproducible example.
...ANSWER
Answered 2020-Jul-29 at 23:55We can use regex_left_join and it is much simpler and can work for various cases i.e. even if the strings vary at the beginning or end
QUESTION
Dear all my brother i have this Json Data enter image description here
...ANSWER
Answered 2020-Apr-29 at 09:32QUESTION
I want to apply multiple filter in PowerShell script as of now I am able to add only single filter like below
ANSWER
Answered 2019-Mar-15 at 15:50To filter on more than one condition, use the Include parameter instead of the -Filter.
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