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QUESTION
ANSWER
Answered 2021-Jun-16 at 01:11The problem is that your CSS selectors include parentheses ()
and dollar signs $
. These symbols already have a special meaning. See:
You can escape these characters using a backslash \
.
QUESTION
I tried 5 different implementations of the Sobel operator in Python, one of which I implemented myself, and the results are radically different.
My questions is similar to this one, but there are still differences I don't understand with the other implementations.
Is there any agreed on definition of the Sobel operator, and is it always synonymous to "image gradient"?
Even the definition of the Sobel kernel is different from source to source, according to Wikipedia it is [[1, 0, -1],[2, 0, -2],[1, 0, -1]]
, but according to other sources it is [[-1, 0, 1],[-2, 0, 2],[-1, 0, 1]]
.
Here is my code where I tried the different techniques:
...ANSWER
Answered 2021-Jun-15 at 14:22according to wikipedia it's [[1, 0, -1],[2, 0, -2],[1, 0, 1]] but according to other sources it's [[-1, 0, 1],[-2, 0, 2],[-1, 0, 1]]
Both are used for detecting vertical edges. Difference here is how these kernels mark "left" and "right" edges.
For simplicity sake lets consider 1D example, and let array be
[0, 0, 255, 255, 255]
then if we calculate using padding then
- kernel
[2, 0, -2]
gives[0, -510, -510, 0, 0]
- kernel
[-2, 0, 2]
gives[0, 510, 510, 0, 0]
As you can see abrupt increase in value was marked with negative values by first kernel and positive values by second. Note that is is relevant only if you need to discriminate left vs right edges, when you want just to find vertical edges, you might use any of these 2 aboves and then get absolute value.
QUESTION
According to the OpenCV Docs, we can use cv::FileStorage
to read/write custom data structure from/to config files (XML, YAML, JSON):
ANSWER
Answered 2021-Jun-15 at 15:05The issue is due to the intruduction of namespace, indeed you can get a similar issue with this code:
QUESTION
I am trying to use thrust with Opencv classes. The final code will be more complicated including using device memory but this simple example does not build successfully.
...ANSWER
Answered 2021-Jun-14 at 14:06As pointed out in the comments, for the code you have shown, you are getting a warning and this warning can be safely ignored.
For usage in CUDA device code:
For a C++ class to be usable in CUDA device code, any relevant member functions that will be used explicitly or implicitly in CUDA device code, must be marked with the __device__
decorator. (There are a few exceptions e.g. for defaulted constructors which don't apply here.)
The OpenCV class you are attempting to use (cv::KeyPoint
), doesn't meet these requirements for use in device code. It won't be usable as-is.
There may be a few options:
Recast your work using
cv::KeyPoint
to use some class that provides similar functionality, that you write yourself, in such a way as to be properly designed and decorated.Perhaps see if OpenCV built with CUDA has an alternate version here (properly designed/decorated) (my guess would be it probably doesn't)
Rewrite OpenCV itself, taking into account all necessary design changes to allow the
cv::KeyPoint
class to be usable in device code.As a variant of suggestion 1, copy the relevant data
.response
to a separate set of classes or just a bare array, and do your selection work based on that. The selection work done there can be used to "filter" the original array.
QUESTION
import cv2
import numpy as np
frameWidth = 640
frameHeight = 480
cap = cv2.VideoCapture(0)
cap.set(3,frameWidth)
cap.set(4,frameHeight)
cap.set(10,150)
myColors=[[5,107,0,19,255,255],
[133,56,0,159,156.255],
[57,76,0,100,255,255]]
def findColors(img,myColors):
imgHSV = cv2.cvtColor(img,cv2.COLOR_BGR2HSV)
for color in myColors:
lower = np.array(color[0:3])
upper = np.array(color[3:6])
mask = cv2.inRange(imgHSV, lower, upper)
cv2.imshow(str(color[0]),mask)
while True:
success, img = cap.read()
findColors(img,myColors)
cv2.imshow("result", img)
if cv2.waitKey(1) & 0xFF == ord ('q'):
break
...ANSWER
Answered 2021-Jun-12 at 23:04there is a typo in your code.
QUESTION
This is my problem : I have a document ( let's call it root) containing an array of another documents (stick), that contain another array of another documents (leaf).
Or simply said : root{ stickChain[leaveschain1[ leaf1, leaf2],leaveschain2[ leaf1, leaf2] ]}
I have access to root _id, stick _id, or whatever it is needed to identify each document.
Basically, the best result I've come so far is, when creating my leaves documents, is to store then at the same level tha sticks, or in another word I've come to create an array of leaves in root.
I'm working in javascript and using mongoose
This is the line I've used:
...ANSWER
Answered 2021-Jun-14 at 09:31I've splitted my dument like this :
- root[stickChain _id]
- stick[leavesChain[leaf]]
Thanks to Andrey Popov for his explications
QUESTION
ANSWER
Answered 2021-Jun-13 at 17:04From cross_val_predict
you already have the predictions. It's a matter of subsetting your data frame where the predictions are not the same as your true label, for example:
QUESTION
I have the following piece of code:
...ANSWER
Answered 2021-Jun-13 at 15:49Pipeline
is used to assemble several steps such as preprocessing, transformations, and modeling. StratifiedKFold
is used to split your dataset to assess the performance of your model. It is not meant to be used as a part of the Pipeline
as you do not want to perform it on new data.
Therefore it is normal to perform it out of the pipeline's structure.
QUESTION
I am new to React and I am trying to create a "CV-Generator" like this like this, What happens here is whenever user puts a value in any of the input it automatically renders to the Render preview(right side),
My problem here is I am rendering a
,
,
, In each of three I process Input onChange and setState
the data, but problem is I need to render this data to again Render Preview(right on the link), But I am confused how can I pass my data from child components(i.e.
,
,
) to the parent Component(
)
App.js
...ANSWER
Answered 2021-Jun-13 at 14:28You have to use callback in child, and then some function in parent to get those data. But remember that you have to trigger the callback function first.
QUESTION
I'm trying to conduct both hyperparameter tuning and feature selection on a sklearn SVC model.
I tried the below code, but am getting an error which I have included.
...ANSWER
Answered 2021-Jun-13 at 14:19You want to perform a grid search over a Pipeline
object. When defining the parameters for the different steps of the pipeline, you have to use the __
syntax:
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