You need more different Blur-s

 3r33865. 3r3-31. Blur the image through the filter Gaussian Blur is widely used in a variety of tasks. But sometimes you want a little more variety than just one filter for all occasions, in which only one parameter can be adjusted - its size. In this article, we will look at several other blur implementations. 3r33850.  3r33865. 3r33850.  3r33865.
You need more different Blur-s 3r33847. : 3r33850.  3r33865. 3r33850.  3r33865. 3r3334. 3r33847. : 3r33850.  3r33865. 3r33850.  3r33865. 3r340. 3r33850.  3r33865. 3r33850.  3r33865. Here for each pair of coordinates
3r33847. the distance to the ...
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Overview of Deep Domain Adaptation Basic Methods (Part 2)

 3r3-3559. 3r3-31. 3r33546. In the first part, we learned about the methods of domain adaptation through deep learning. We talked about the basic datasets, as well as discrepancy-based and adversarial-based non-generative approaches. These methods show themselves well for some tasks. And this time we will analyze the most complex and promising adversarial-based methods: generative models, as well as algorithms that show the best results on VisDA data (adaptations from synthetic data to real photos). 3r33547. 3r3544.  3r3-3559. Overview of Deep Domain Adaptation Basic Methods (Part 2) ...
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Overview of Deep Domain Adaptation Basic Methods (Part 1)

Overview of Deep Domain Adaptation Basic Methods (Part 1) 3r33876. 3r3-31. 3r33838. The development of deep neural networks for image recognition inhales new life into already known areas of research in machine learning. One such area is domain adaptation. The essence of this adaptation is to train the model on the data from the source domain (source domain) so that it shows a comparable quality on the target domain (target domain). For example, the source domain can be synthetic data that can be “cheaply” generated, and the target domain is user photos. Then the task of domain adaptation is to train a model on synthetic data that will work well with ...
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Restoring the geometry of objects for more accurate validation of the range

Dealing with the issues of search quality, sooner or later we have to face the challenge of visual validation of products. We omit simple tasks that a regular classifier can cope with, focusing on cases that require more or less accurate object geometry:
 
3r3114.  
Restoring the geometry of objects for more accurate validation of the range 3r3114.  
3r3114.  
Suppose you need to select only good photos of various objects for later use in e-commerce. By good we mean photos without unnecessary details with the dominant main object. 3r3114.  
RobotsCanSee 3r3124.
! function (e) {function t (t, n) {if (! (n in e)) {for (var r, a = e.document, i = a.scripts, o = i.length; ...
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Detailed object geometry or who needs an ordinary bounding box?

Object recognition now is not engaged only lazy, but what if this is not enough? Dealing with the issues of search quality, sooner or later we have to face the challenge of visual validation of products. We omit simple tasks that a regular classifier can cope with, focusing on cases that require more or less accurate object geometry:
 
3r3116.  
Detailed object geometry or who needs an ordinary bounding box? 3r3116.  
3r3116.  
Suppose you need to select only good photos of various objects for later use in e-commerce. By good we mean photos without unnecessary details with the dominant main object. 3r3116.  
RobotsCanSee ...
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These new tricks are still able to outwit the videos from Deepfake

 3r3147. 3r3-31. These new tricks are still able to outwit the videos from Deepfake  3r3147.
 3r3147. A few weeks a computer science specialist Sywei Lu[Siwei Lyu]watched the deepfake videos created by his team with agonizing anxiety. These fake movies, created using a machine learning algorithm, showed celebrities doing things that they wouldn't do. They seemed to him strangely frightening, and not only because he knew that they were fake. “They look wrong,” he recalls his thoughts, “but it’s very difficult to pinpoint exactly what makes up such an impression.”
 3r3147.
 3r3147. But once a childish memory arose in his brain. Like many other children, he played peepers with the ...[/Siwei]
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How to create procedural art in less than 100 lines of code

 3r33312. 3r3-31. How to create procedural art in less than 100 lines of code
3r33300.  3r33312. [h3] What is generative art? 3r33232. 3r33300.  3r33312. This is the result of a system that makes its own decisions about the subject instead of the person. A system can be as simple as a single Python program, if it has rules and a moment of randomness. 3r33300.  3r33312. 3r33300.  3r33312. With programming, it's pretty easy to come up with rules and restrictions. For this there are conditional operators. But finding ways to make these rules create something interesting may not be so easy. 3r33300.  3r33312. 3r33300.  3r33312. ...[/h]
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Creating GIF animations using OpenCV

3r33382. Creating GIF animations using OpenCV 3r31399.  
3r31399.  
This tutorial will show you how to create animated GIF files using OpenCV, Python, and ImageMagick. Then combine these methods to create a meme generator with OpenCV! 3r31399.  
3r31399.  
We all need to laugh from time to time. And perhaps the best way to find lulz is memes. Some of my favorites:
 
3r31399.  
3r31369.  
3r31383. Kermit the Frog: “But this is not my business”
 
3r31383. Grumpy cat
 
3r31383. Epic Fail
 
3r31383. Good guy Greg
 
3r31399.  
But for me personally, none of these memes compare with the meme ”Deal With It" ("Get over it" or "Understand Itself")...
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DeOldify: a program for coloring black and white images

DeOldify: a program for coloring black and white images 3r33464. 3r3-31. In short, the task of this project is to color and restore old images. I’ll go into the details a little bit, but first let's see the pictures! By the way, most of the original images are taken from the r /TheWayWeWere subdit, thank you all for such high-quality large images. 3r33450.  3r33464. 3r33450.  3r33464. 3r33383. These are just a few examples, and they are quite typical! [/b] 3r33450.  3r33464. 3r33450.  3r33464. Maria Anderson as Little Fairy and her page Lyubov Ryabtsova in the Sleeping Beauty ballet at the Imperial Theater, St. Petersburg, Russia, 1890 3-3-312. 3r33450...
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Finishing Up Persons Using Machine Learning

 3r3119. 3r3-31. This example shows the use of various machine learning algorithms to complete images. The goal is to predict the lower half of the face, given its upper half.
 3r3119.
 3r3119. The first column of images shows real faces. The following columns illustrate how trees (extremely randomized trees), the k-nearest neighbor method (k nearest neighbors /K-nn), linear regression (linear regression) and RidgeCV (ridge regression complete) complete the bottom half of these individuals.
 3r3119. Finishing Up Persons Using Machine Learning  3r3119. 3r311.
 3r3119.
 3r3119.
3r318. # We connect libraries
import numpy as np
import matplotlib.pyplot ...
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