pixels | 🦀 | Graphics library
kandi X-RAY | pixels Summary
kandi X-RAY | pixels Summary
A tiny hardware-accelerated pixel frame buffer. .
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of pixels
pixels Key Features
pixels Examples and Code Snippets
function getElementUnderClientXY(elem, clientX, clientY) {
var display = elem.style.display || '';
elem.style.display = 'none';
var target = document.elementFromPoint(clientX, clientY);
elem.style.display = display;
if (!target || target
def convert_to_negative(img):
# getting number of pixels in the image
pixel_h, pixel_v = img.shape[0], img.shape[1]
# converting each pixel's color to its negative
for i in range(pixel_h):
for j in range(pixel_v):
Community Discussions
Trending Discussions on pixels
QUESTION
I am using Perceptual hashing technique to find near-duplicate and exact-duplicate images. The code is working perfectly for finding exact-duplicate images. However, finding near-duplicate and slightly modified images seems to be difficult. As the difference score between their hashing is generally similar to the hashing difference of completely different random images.
To tackle this, I tried to reduce the pixelation of the near-duplicate images to 50x50 pixel and make them black/white, but I still don't have what I need (small difference score).
This is a sample of a near duplicate image pair:
Image 1 (a1.jpg):
Image 2 (b1.jpg):
The difference between the hashing score of these images is : 24
When pixeld (50x50 pixels), they look like this:
rs_a1.jpg
rs_b1.jpg
The hashing difference score of the pixeled images is even bigger! : 26
Below two more examples of near duplicate image pairs as requested by @ann zen:
Pair 1
Pair 2
The code I use to reduce the image size is this :
...ANSWER
Answered 2022-Mar-22 at 12:48Rather than using pixelisation to process the images before finding the difference/similarity between them, simply give them some blur using the cv2.GaussianBlur()
method, and then use the cv2.matchTemplate()
method to find the similarity between them:
QUESTION
I'm trying to test a Text
that on my component I can print it in different colors, so on my test I'm verifying it gets the expected color. I was looking for a method to return the color but I did not find any.
From now I'm asserting that the text is correct and the visibility is correct, but when trying to find the method to get the colour I get too deep and I'm looking for a simpler solution.
...ANSWER
Answered 2022-Feb-11 at 09:02I am by no means a compose expert, but just looking at compose source code, you could utilize their GetTextLayoutResult accessibility semantic action. This will contain all the properties that are used to render the Text
on a canvas.
Some quick and dirty extension functions I put up for convenience:
QUESTION
I don't know if this is possible, but I am trying to take the image of a custom outdoor football field layout and have the players' GPS
coordinates correspond to the image x
and y
position. This way, it can be viewed via the app to show the players' current location on the field as a sort of live tracking.
I have also looked into this Convert GPS coordinates to coordinate plane. The problem is that I don't know if this would work and wanted to confirm beforehand. The image provided in the post was for indoor location, and it was from 11
years ago.
I used Location
and Google Maps
packages for flutter. The player's latitude
and longitude
correspond to the actual latitude
and longitude
that the simulator in the android studio shows when tested.
The layout in question and a close comparison to the result I am looking for.
Any help on this matter would be appreciated highly, and thanks in advance for all the help.
Edit:
After looking more at the matter I tried the answer of this post GPS Conversion - pixel coords to GPS coords, but it wasn't working as intended. I took some points on the image and the correspond coordinates, and followed the same logic that the answer used, but reversed it to give me the actual image X
, Y
positions.
The formula that was given in the post above:
...ANSWER
Answered 2022-Jan-12 at 08:20First of All, Yes you can do this with high accuracy if the GPS coordinates are accurate.
Second, the main problem is rotation if the field are straight with lat lng lines this would be easy and straightforward (no bun intended).
The easy way is to convert coordinate to rotated image similar to the real field then rotated every X,Y point to the new straight image. (see the image below)
Here is how to rotate x,y knowing the angel:
QUESTION
(Solution has been found, please avoid reading on.)
I am creating a pixel art editor for Android, and as for all pixel art editors, a paint bucket (fill tool) is a must need.
To do this, I did some research on flood fill algorithms online.
I stumbled across the following video which explained how to implement an iterative flood fill algorithm in your code. The code used in the video was JavaScript, but I was easily able to convert the code from the video to Kotlin:
https://www.youtube.com/watch?v=5Bochyn8MMI&t=72s&ab_channel=crayoncode
Here is an excerpt of the JavaScript code from the video:
Converted code:
...ANSWER
Answered 2021-Dec-29 at 08:28I think the performance issue is because of expandToNeighbors
method generates 4 points all the time. It becomes crucial on the border, where you'd better generate 3 (or even 2 on corner) points, so extra point is current position again. So first border point doubles following points count, second one doubles it again (now it's x4) and so on.
If I'm right, you saw not the slow method work, but it was called too often.
QUESTION
I'm trying to learn Python/Pygame and I made a simple Pong game. However I cannot get the square to bounce off the sides at the perfect pixel as the drawing of the square is updating let's say 3 pixels every frame.
I have a code to decide when the square is hitting the edges and bounce in a reverse direction like this:
...ANSWER
Answered 2021-Dec-26 at 20:16You also need to correct the position of the ball when changing the direction of the ball. The ball bounces on the boundaries and moves the excessive distance in the opposite direction like a billiard ball:
e.g.:
QUESTION
I have created a working CNN model in Keras/Tensorflow, and have successfully used the CIFAR-10 & MNIST datasets to test this model. The functioning code as seen below:
...ANSWER
Answered 2021-Dec-16 at 10:18If the hyperspectral dataset is given to you as a large image with many channels, I suppose that the classification of each pixel should depend on the pixels around it (otherwise I would not format the data as an image, i.e. without grid structure). Given this assumption, breaking up the input picture into 1x1 parts is not a good idea as you are loosing the grid structure.
I further suppose that the order of the channels is arbitrary, which implies that convolution over the channels is probably not meaningful (which you however did not plan to do anyways).
Instead of reformatting the data the way you did, you may want to create a model that takes an image as input and also outputs an "image" containing the classifications for each pixel. I.e. if you have 10 classes and take a (145, 145, 200) image as input, your model would output a (145, 145, 10) image. In that architecture you would not have any fully-connected layers. Your output layer would also be a convolutional layer.
That however means that you will not be able to keep your current architecture. That is because the tasks for MNIST/CIFAR10 and your hyperspectral dataset are not the same. For MNIST/CIFAR10 you want to classify an image in it's entirety, while for the other dataset you want to assign a class to each pixel (while most likely also using the pixels around each pixel).
Some further ideas:
- If you want to turn the pixel classification task on the hyperspectral dataset into a classification task for an entire image, maybe you can reformulate that task as "classifying a hyperspectral image as the class of it's center (or top-left, or bottom-right, or (21th, 104th), or whatever) pixel". To obtain the data from your single hyperspectral image, for each pixel, I would shift the image such that the target pixel is at the desired location (e.g. the center). All pixels that "fall off" the border could be inserted at the other side of the image.
- If you want to stick with a pixel classification task but need more data, maybe split up the single hyperspectral image you have into many smaller images (e.g. 10x10x200). You may even want to use images of many different sizes. If you model only has convolution and pooling layers and you make sure to maintain the sizes of the image, that should work out.
QUESTION
I’m writing a pretty complex app in React/Redux/Redux Toolkit, and I came across a situation which I’m not really sure how to handle. I found a way to do it, but I’m wondering if it can cause issues or if there is a better way. The short version is that I want the reducer to communicate to the caller without modifying the state, and the only way I’ve found is to mutate the action.
Description:
To simplify, let’s say that I want to implement a horizontal scrollbar (but in reality it’s significantly more complicated). The state contains the current position, a number capped between some min
and max
values, and the UI draws a rectangle that has that position and that can be clicked and dragged horizontally.
Main property: If the user clicks and drags further than the min/max value, then the rectangle does not move further, but if the user then moves in the other direction, the rectangle should wait until the mouse is back at its original position before starting to move back (exactly like scrollbars behave on most/all operating system).
Keep in mind that my real use case is significantly more complex, I have a dozen of similar situations, sometimes capping between min and max, sometimes snapping every 100 pixels, sometimes more complicated constraints that depend on various parts of the state, etc. I’d like a solution that works in all such cases and that preserves the separation between the UI and the logic.
Constraints:
- I do not want the UI/component/custom hook to have the responsibility to compute when we reach the min/max, because in my use case it can be pretty complex and depend on various parts of the state. So the reducer is the only place that knows whether we did reach the min/max.
- On the other hand, in order to implement the Main property above, I do need to somehow remember where we clicked on the rectangle, or how many pixels of a given "drag" action was handled, in order to know when to start moving back. But I don’t want to store that in the state as it’s really a UI detail that doesn’t belong there (and also because I have quite a few different situations where I need to do that and my state would become significantly more complex, and unnecessary state changes will be performance heavy).
Problem:
So the reducer is the only part that knows if we reached the min/max, and the only way a reducer usually communicates to the rest of the app is through the state, but I don’t want to communicate that information through the state.
Solution?
I actually managed to find a way to solve it, which seems to work just fine but feels somewhat wrong: mutating the action object in the reducer.
The reducer takes the action "dragged by 10 pixels", realizes that it can only drag by 3 pixels, creates a new state where it has been dragged by 3 pixels, and adds an action.response = 3
field to the action.
Then after my custom hook dispatched the "dragged by 10 pixels" action, it looks at the action.response
field of the return value of dispatch
to know how much was actually handled, and it remembers the difference with the expected value (in this case it remembers that we are 7 pixels away from the original position).
In this way, if at the next mousemove we drag by -9 pixels, my custom hook can add that number to the 7 pixels it remembers, and tell the reducer that we only moved by -2 pixels.
It seems to me that this solution preserves separation of UI/logic perfectly:
- The reducer only needs to know by how many pixels we moved and then return the new state and how many pixels were actually handled (through mutating the action)
- The custom hook can remember how far off we are from the original position (without having to know why), and then it will simply correct
event.movementX
to compensate with how much the reducer didn’t handle in previous actions, and then send the correct delta to the reducer.
It also works just fine with things like snapping at every 100 pixels or such.
The only weird thing is that the reducer mutates the action, which I would assume is not supposed to happen as it should be a pure function, but I couldn’t find any issue with it so far. The app just works, Redux Toolkit doesn’t complain, and the devtools work just fine as well.
Is there any issue with this solution?
Is there another way it could be done?
...ANSWER
Answered 2021-Nov-19 at 16:23At a technical level, I can see how this could work. But I'd also agree it feels "icky". Very technically speaking, mutating the action itself qualifies as a "side effect", although it's not one that would meaningfully break the rest of the app.
It sounds as if the key bit of logic here is more at the "dispatch an action" level. I think you could likely call getState()
before and after the dispatch to compare the results, and derive the additional needed data that way. In fact, this might be a good use case for a thunk:
QUESTION
I am looking for an easy way to count the number of the green pixels in the image below, where the original image is the same but the green pixels are black.
I tried it with numpy.diff()
, but then I am counting some pixels twice. I thought about numpy.gradient()
– but here I am not sure if it is the right tool.
I know there have to be many solutions to this problem, but I don't know how to google for it. I am looking for a solution in python.
To make it clearer, I have only one image (only black and white pixels). The image with the green pixel is just for illustration.
...ANSWER
Answered 2021-Nov-14 at 13:19You can use the edge detection kernel for this problem.
QUESTION
I am trying to linearly scale an image so the whole greyscale range is used. This is to improve the lighting of the shot. When plotting the histogram however I don't know how to get the scaled histogram so that its smoother so it's a curve as aspired to discrete bins. Any tips or points would be much appreciated.
...ANSWER
Answered 2021-Nov-02 at 14:07I'm not sure if this is possible if you're linearly scaling the image. However, you could give OpenCV's Contrast Limited Adaptive Histogram Equalization a try:
QUESTION
Unhandled promise rejection: Error: No native splash screen registered for given view controller. Call 'SplashScreen.show' for given view controller first.
I get the following warning only on my ios emulator when I first launch the app. Not on my ios physical device or android emulator. I am using expo-splash-screen
for my splash screen. Is this something I can just ignore or do I need to resolve it because I can't figure out how to resolve it. The splash screen seems to load fine. Is it an error with expo-splash-screen
? I followed expo's tutorial on setting it up.
warning:
...ANSWER
Answered 2021-Sep-29 at 15:01The problem is caused because u're using AppLoading
, this component is currently having this bug on iOS.
You can solve this avoid using this component until the bug is resolved, an alternative is create a Screen like your Splashscreen and replace to
... or in a ruder and lazy way (bad UX) just change to
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Rust is installed and managed by the rustup tool. Rust has a 6-week rapid release process and supports a great number of platforms, so there are many builds of Rust available at any time. Please refer rust-lang.org for more information.
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