Blurry | Image Blurring in Swift | iOS library
kandi X-RAY | Blurry Summary
kandi X-RAY | Blurry Summary
Image blurring in Swift. This library is a small CoreImage wrapper that performs a variety of blurring techniques based on the given parameters. Need a different version of Swift?.
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QUESTION
I would like to extract the definitions from the book The Navajo Language: A Grammar and Colloquial Dictionary by Young and Morgan. They look like this (very blurry):
I tried running it through the Google Cloud Vision API, and got decent results, but it doesn't know what to do with these "special" letters with accent marks on them, or the curls and lines on/through them. And because of the blurryness (there are no alternative sources of the PDF), it gets a lot of them wrong. So I'm thinking of doing it from scratch in Tesseract. Note the term is bold and the definition is not bold.
How can I use Node.js and Tesseract to get basically an array of JSON objects sort of like this:
...ANSWER
Answered 2021-Jun-15 at 20:17Tesseract takes a lang
variable that you can expand to include different languages if they're installed. I've used the UB Mannheim (https://github.com/UB-Mannheim/tesseract/wiki) installation which includes a ton of languages supported.
To get better and more accurate results, the best thing to do is to process the image before handing it to Tesseract. Set a white/black threshold so that you have black text on white background with no shading. I'm not sure how to do this in Node, but I've done it with Python's OpenCV library.
If that font doesn't get you decent results with the out of the box, then you'll want to train your own, yes. This blog post walks through the process in great detail: https://towardsdatascience.com/simple-ocr-with-tesseract-a4341e4564b6. It revolves around using the jTessBoxEditor to hand-label the objects detected in the images you're using.
Edit: In brief, the process to train your own:
- Install jTessBoxEditor (https://sourceforge.net/projects/vietocr/files/jTessBoxEditor/). Requires Java Runtime installed as well.
- Collect your training images. They want to be .tiffs. I found I got fairly accurate results with not a whole lot of images that had a good sample of all the characters I wanted to detect. Maybe 30/40 images. It's tedious, so you don't want to do TOO many, but need enough in order to get a good sampling.
- Use jTessBoxEditor to merge all the images into a single .tiff
- Create a training label file (.box)j. This is done with Tesseract itself.
tesseract your_language.font.exp0.tif your_language.font.exp0 makebox
- Now you can open the box file in jTessBoxEditor and you'll see how/where it detected the characters. Bounding boxes and what character it saw. The tedious part: Hand fix all the bounding boxes and characters to accurately represent what is in the images. Not joking, it's tedious. Slap some tv episodes up and just churn through it.
- Train the tesseract model itself
- save a file:
font_properties
who's content isfont 0 0 0 0 0
- run the following commands:
tesseract num.font.exp0.tif font_name.font.exp0 nobatch box.train
unicharset_extractor font_name.font.exp0.box
shapeclustering -F font_properties -U unicharset -O font_name.unicharset font_name.font.exp0.tr
mftraining -F font_properties -U unicharset -O font_name.unicharset font_name.font.exp0.tr
cntraining font_name.font.exp0.tr
You should, in there close to the end see some output that looks like this:
Master shape_table:Number of shapes = 10 max unichars = 1 number with multiple unichars = 0
That number of shapes should roughly be the number of characters present in all the image files you've provided.
If it went well, you should have 4 files created: inttemp
normproto
pffmtable
shapetable
. Rename them all with the prefix of your_language
from before. So e.g. your_language.inttemp
etc.
Then run:
combine_tessdata your_language
The file: your_language.traineddata
is the model. Copy that into your Tesseract's data folder. On Windows, it'll be like: C:\Program Files x86\tesseract\4.0\tessdata
and on Linux it's probably something like /usr/shared/tesseract/4.0/tessdata
.
Then when you run Tesseract, you'll pass the lang=your_language
. I found best results when I still passed an existing language as well, so like for my stuff it was still English I was grabbing, just funny fonts. So I still wanted the English as well, so I'd pass: lang=your_language+eng
.
QUESTION
can anybody help me please about how to show a page using iframe with blurry background after submit ,
what I mean by submit is after submitting a form with the submit bouton ( Example
...ANSWER
Answered 2021-Jun-09 at 21:34This is a replica of the image you showed.On click of a button, I used a div to mimic a transparent background and centered an iframe in it to be displayed. Manipulate the last rgba value to increase or decrease the opacity of the background(0 is fully transparent, 1 is opaque).
QUESTION
I try to import a .png
file via url()
in CSS, but the button ends up being a solid color from within the image, instead of the image itself. I've tried different images and it just loads a different solid color.
The Navbar should be a solid color and there are buttons in the corner but its affected by the blur from surrounding elements. I tried messing with the z-index
, but that doesn't change anything. I tried removing blur, and it fixes the blurry gradient, but thats not an issue for me, the .png
is still not loading correctly.
I'm still trying to under CSS and this is more than likely because of mixing of different tutorials without understanding the core of CSS, but I'd like to understand why they clash.
...ANSWER
Answered 2021-May-28 at 15:28The problem is that your image URL is returning HTML instead of the image. Try going to https://tumuy.csb.app/assets/icons/x.png.
See: Is it possible to serve Static files with create-react-app from public folder?
QUESTION
The smallest innermost circle in the snippet below has a backdrop-filter
blur of 10rem
that's not being applied. It looks like the span
element is inheriting the same exact amount of blur from it's parent instead of taking the higher value that should be applied. Any idea why and/or have any known workarounds?
ANSWER
Answered 2021-Jun-07 at 15:09Don't nest the elements, keep them separate.
Here is another idea to achieve what you want
QUESTION
Context: I am trying to find the directional heading from a small image of a compass. Directional heading meaning if the red (north) point is 90 degrees counter-clockwise from the top, the viewer is facing East, 180 degrees is south, 270 is west, 0 is north. etc. I understand there are limitations with such a small blurry image but I'd like to be as accurate as possible. The compass is overlaid on street view imagery meaning the background is noisy and unpredictable.
The first strategy I thought of was to find the red pixel that is furthest away from the center and calculate the directional heading from that. The math is simple enough.
The tough part for me is differentiating the red pixels from everything else. Especially because almost any color could be in the background.
My first thought was to black out the completely transparent parts to eliminate the everything but the white transparent ring and the tips of the compass.
True Compass Values: 35.9901, 84.8366, 104.4101
These values are taken from the source code.
I then used this solution to find the closest RGB value to a user given list of colors. After calibrating the list of colors I was able to create a list that found some of the compass's inner most pixels. This yielded the correct result within +/- 3 degrees. However, when I tried altering the list to include every pixel of the red compass tip, there would be background pixels that would be registered as "red" and therefore mess up the calculation.
I have manually found the end of the tip using this tool and the result always ends up within +/- 1 degree ( .5 in most cases ) so I hope this should be possible
The original RGB value of the red in the compass is (184, 42, 42) and (204, 47, 48) but the images are from screenshots of a video which results in the tip/edge pixels being blurred and blackish/greyish.
Is there a better way of going about this than the closest_color() method? If so, what, if not, how can I calibrate a list of colors that will work?
...ANSWER
Answered 2021-Jun-04 at 08:45If you don't have hard time constraints (e.g. live detection from video), and willing to switch to NumPy, OpenCV, and scikit-image, you might use template matching. You can derive quite a good template (and mask) from the image of the needle you provided. In some loop, you'll iterate angles from 0° to 360° with a desired resolution – the finer the longer takes the whole procedure – and perform the template matching. For each angle, you save the value of the best match, and finally search for the best score over all angles.
That'd be my code:
QUESTION
I'm trying to stitch two pre-warped images together seamlessly using multi-band blending. I have two input images (that have already been warped) and one mask. However, when I apply MBB, the area surrounding the seams glow brighter and as a result, they become more visible which is the opposite of the objective here. I have absolutely no idea what I'm doing wrong.
To better explain the problem, here are the images and the output:
Target:
Source:
Mask:
And once I blend the source image into the target, this is what I get:
Here's my code for reference:
...ANSWER
Answered 2021-Jun-03 at 17:30here's a C++ answer, but the algorithm is easy.
QUESTION
I'd like to know how can I up-size a UIImage in a UIButton so that when it is scaled up to fill the button, it has sharp edges, instead of blurry?
I.e for use in 8-bit styled artwork. The UIImage I have saved is 64px by 64 px, but is being displayed on a much larger frame.
...ANSWER
Answered 2021-May-30 at 06:00I solved this myself by resizing the UIImage to the size of the UIButton with antialiasing turned off.
QUESTION
I took an equirectangular envMap
from the three.js docs sample where it appears sharp on a sphere.
If I load the same material into my aframe scene with the following params
...ANSWER
Answered 2021-May-25 at 20:44That happens because you are using a PBR material in your code since the default material of A-Frame is MeshStandardMaterial. Meaning a material that tries to render physically correct. The official three.js
example uses MeshLambertMaterial which is no PBR material. Both type of materials implement environment maps differently.
When using a PBR material, it's recommended to use a HDR environment map which is also pre-processed with PMREMGenerator
like in this example: https://threejs.org/examples/webgl_loader_gltf
QUESTION
I am trying to make publication-quality in Jupyter-lab using matplotlib and LaTeX fonts. I have created a simple document following instructions found here: https://matplotlib.org/stable/tutorials/text/usetex.html
The graph was created with beautiful fonts; however, saved eps file was blank. The same graph could be successfully saved as png, but it looked blurry when import to LaTeX even using dpi=2400
option. Eps files WITHOUT LaTeX fonts were sharp as a razor when imported into LaTeX file.
Suggestions? Workarounds?
Thanks, Radovan
PS. One workaround I found was using gnuplot and cairolatex
terminal ... resulting *.tex file could be compiled with Pdflatex
with excellent results. But that a different story :-).
ANSWER
Answered 2021-May-23 at 20:16I gave this another try. At the end, it did work! Here is the code:
QUESTION
I'm having a problem with the main baner image on my website.test website click here use right click inspect element then check the "toggle device toolbar" or use ctrl+shift+m ....
as you will see the main image is repeating itself in mobile mode:
the code:
html:
...ANSWER
Answered 2021-May-18 at 16:00The problem is not to do with background images repeating.
What has happened is that there is still a full size image in the div just above the start of the mobile-sized slideshow.
See the below code which shows you the position of the div which has an inline style giving it the larger background image.
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