Attachments: make the required alternative text when setting up a featured image

In the EU, it will soon be a requirement for public sector websites to have alternative text for uploaded images. However, the users of my organization are dumb to add alternative text, and I am trying to find a way to force them to do so.

The only way I have found so far is to automatically fill in the alternative text with the title of the image, which is not excellent if an image is called "shutterstock_45363627", and could encourage laziness.

Ways I can think of having them write something:

(1) Set the field & # 39; Alternative text & # 39; in & # 39; required & # 39; through the functions.php file (although I read that the default fields cannot be changed through attachment_fields_to_edit, for example).

(2) Find the "Attachment details" file in wp-admin and add a "required" attribute to the field. What is horrible, but it could work.

(3) Use a WordPress hook to verify that the alternative text is completed when configuring an image … Or verify that the alternative text contains a space, since it must be a couple of words.

However, despite the hours of searching on Google, I can't find anything online about how to do any of this. Does anyone have suggestions?

35 mm – black area around the frame and the image, what are those?

I would like to ask and find some idea for this type of problem. So, I am using an analog camer, Olympus OM-1. Lately, I have been developing my roll and have found some strange dark areas along the surface of the film.
enter the description of the image here
This dark area thing only appears during outdoor and sunny photographs, but during or in indoor photographs, they no longer appear.enter the description of the image here
enter the description of the image here
Can anyone help?

What text sources best survive image compression?

I am creating diagrams in Office Excel for people in my community and the platform on which it is loaded has a tendency to compress the images. Sometimes this results in an almost illegible text. It is loaded as an image because that is the desired format of the community.

Can you give me some advice on which sources would probably survive compression better?


Exporting image and scale.

Let's say I have a plot, for example that:


enter the description of the image here

and I would like to export it as a PDF in such a way that if I print the PDF in A4 format (for example), "1" in the plot corresponds to 1 cm in the A4. The curve can be rasterized.

Is there a precise and robust way to do this?

java – How can I zoom an image on android and then be able to select a button that is on it?

I am investigating how to zoom an image in android studio and then press a button that is on it.
The image is as follows:
enter the description of the image here

I would like to be able to zoom in on this image and then press a button that would be placed in any of the frames that divide the image.

A greeting. Thanks in advance.

mysql – I have to store image field data in image table and category field data in category table from a single form using php

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extract a particular MODIS image from a collection of images in the Google Earth engine

I am working with MODIS images in GEE and I am new in its interface. So I was able to access the MODIS ground coverage product (MCD12Q1). I have added images from 2003 to 2016. How can I modify this code to extract images from a particular year, for example? 2005 or 2010 in GEE for the visualization of this collection?. There is only one image per year in this product.

Here is my code to find and show the collection:

var dataset = ee.ImageCollection (& # 39; MODIS / 006 / MCD12Q1 & # 39;)
.select (& # 39; LC_Type1 & # 39;)
.filterDate (& # 39; 2003-01-01 & # 39 ;, & # 39; 2016-12-31 & # 39;)
.map (function (img) {
var d = ee.Date (ee.Number (img.get (& # 39; system: time_start & # 39;)));
var m = ee.Number (d.get (& # 39; month & # 39;));
var y = ee.Number (d.get (& # 39; year & # 39;));
return img.set ({& # 39; month & # 39 ;: m, & # 39; year & # 39 ;: and});
// var igbpLandCover = (& # 39; LC_Type1 & # 39;);
var palette =[
  '152106',//evergreen needleaf forests
  '225129',//evergreen broadleaf forests
  '369b47',//deciduous needleleaf forests
  '30eb5b',//deciduoud broadleaf forests
  '387242',//mixed deciduous forests
  '6a2325',//closed shrubland
  'b76031',//woody savanna
  '111149',//permanenet wetlands
  'cdb33b', //croplands
  'cc0013', //urban
  '33280d', //crop/natural veg. mosaic
  'd7cdcc',//permanent snow/ice
  'f7e084', //barren/desert
  ]join (& # 39;, & # 39;);
Map.setCenter (100,15,6);
Map.addLayer (data set, {& # 39; min & # 39 ;: 0, & # 39; max & # 39 ;: 17, & # 39; palette & # 39 ;: palette}, & # 39; classification IGBP & # 39;);

Pixel image with PHP |

The next script he does is pixelate an image with PHP. Use the PHP GD library to pixel the image.


// Size of the pixel
$ pixel = fifteen;
/ * Pixelate an image * /
$ getImagen = & # 39; mona-lisa.jpg & # 39;;
// We create an image variable from the original image
# $ Image = imagecreatefrompng ($ getImagen); // Uncomment if it is PNG
$ image = imaginary of jpeg($ getImagen);
$ image) exit(& # 39; ERROR & # 39;);
$ width,$ high) =get images($ getImagen);
$ surface Total = $ width*$ high;
$ surfaceCurrent = 0;
$ auxX=0;
$ auxY=0;
$ surfaceCurrent <= $ surface Total) {
$ posX=0;$ posY=0;$ data = Array ();
$ posX <= $ pixel Y (($ auxX + $ posX) < $ width)) {
$ posY=0;
$ posY <= $ pixel Y (($ auxY + $ posY) < $ high)) {
$ rgb = coloring pictures($ image,$ auxX + $ posX),$ auxY + $ posY));
$ r = ($ rgb >> sixteen) & 0xFF;
$ g = ($ rgb >> 8) & 0xFF;
$ b = $ rgb Y 0xFF;
$ data[] = Array ($ r,$ g,$ b);
$ posY++;
$ posX++;

// I look for average
$ r = 0; $ g = 0; $ b = 0;
for each(
$ data as $ d) {
$ r+ = $ dThe[[0];
$ g+ = $ dThe[[one];
$ b+ = $ dThe[[two];
$ totalArray = tell($ data);
$ totalArray == 0) $ totalArray = one;
$ r = $ r/$ totalArray;
$ g = $ g/$ totalArray;
$ b = $ b/$ totalArray;
$ color average = imagecollocalize($ image, $ r, $ g, $ b);
imagefilledrectangle($ image, $ auxX, $ auxY,$ auxX + $ pixel),$ auxY + $ pixel) $ color average);
$ auxX+ = $ pixel;
$ auxX > = $ width) {
$ auxX = 0;
$ auxY+ = ($ pixel+one);
$ surfaceCurrent+ = $ pixel*$ pixel;

Header("Type of content: image / jpeg");
imagejpeg($ image);
imagedestroy($ image);
// End Pixelar an image


artifacts: What can cause a horizontally flipped ghost image when using a monochrome line scanning camera?

Assuming that standard optics (lens elements that are spherical or pseudo-spherical, with rotational symmetry with respect to the optical axis) and "standard" cameras (without beam splitting, or mirrors in the optical path), there is nothing optically this will cause ghost images of lateral reflection of a single axis, either from left to right, from top to bottom or even diagonally. This is because the lenses perform transformations for any set of orthogonal input axes (ie, X Y Y axes). Both dimensions are transformed: the left is changed by the right and the upper part is changed by the lower part (in addition to the scale, and probably also a certain degree of distortion). In linear algebra, swapping. X for -X Y Y for -Y is mathematically equivalent to a rotation of 180 ° on the z axis (ie, on the optical axis of the lens). Thus, in optically generated ghost images (again, with "standard" optics), all ghost elements are reflected through the center of the image, not simply through a vertical or horizontal "fold line".

Moving away from standard optics, cylindrical sector lens elements, which are curved in one dimension (usually laterally) but not in the orthogonal (vertical) dimension, could cause symmetrical phantom patterns from left to right. The anamorphic lenses, or at least the current anamorphic filters and adapters, come to mind. They compress the lateral field of view of a shooting lens, which when printed or processed allows much wider lateral fields of vision than the camera can normally. This is often used to film wide-screen cinema.

In addition to optics, I suppose it is possible that some sensor technologies are susceptible to lateral "ghost images", perhaps because of the way sensor data is read or scanned. But that would be pure speculation on my part.

The last thing I can think of, at least inside the optics or the camera itself, is some kind of reflection of the sensor image, back to some plane in the optical path (like a filter plate or something behind it). the lens, quite close to the plane of the film / sensor), and then back to the sensor. But in order for the reflected image to appear even slightly focused, the aggregate reflection path must be quite short compared to the rear focusing distance of the lens. This implies that the lens focuses extremely close to the subject, and there would be a certain distance from the exit pupil of the lens to the sensor. In addition, that reflection surface would have to be concave (looking from the face of the lens) only in the lateral dimension. Frankly, this last possibility is even more speculative and unlikely than the previous paragraph.

Outside the camera, the most obvious explanation is a reflection through a window, an automotive glass or another surface that is largely transparent but semi-reflective. That would explain the same degree of magnification and the object reflected in the focus as the real object in the image.

What is an image map?

Hello friends,

I would like to know what is an image map?