When searching my company, “Tattini Boots”, on a mobile device you will see that the following cut off image is displayed next to the search result (see image below). This is not the image that I have set in Yoast or the Featured Image for Search Results on my index page. Can someone dive into the source and allocate why this image is being chosen? This image is simply a slider overlay on the main page: www.TattiniBoots.com
I need to photograph an image containing a steganographically hidden message, then decode the stego content from the photograph without recourse to the original image data. Are there any steganography algorithms that would make the task more reliable?
Note: I tried the Least Significant Bit (LSB) method, but when I processed the photos from the camera there was too much distortion.
I have an image code with srcset and sizes like this:
<img src="/uploads/2012/12/Multitronics-TC-750-300x175.jpg" class="attachment-medium size-medium wp-post-image lazyloaded" alt="Multitronics TC 750" srcset="/uploads/2012/12/Multitronics-TC-750-300x175.jpg 300w, /uploads/2012/12/Multitronics-TC-750-513x265.jpg 513w, /uploads/2012/12/Multitronics-TC-750.jpg 1260w" sizes="(max-width: 300px) 100vw, 300px">
How to get the maximum image size (like Multitronics-TC-750.jpg 1260w) using the function? For example wp_calculate_image_srcset ()?
I am try to image steganoggaphy using c++. I tried serverla method LSB , MSB, Descretate Cosing Traformation etc. all of them success when decording take original stego image. I need to take photo (stego image) from camara(andorid) and decode it.
so , when i take photo of stago image , and decode it , every thing vanish.
are their any method to do , strgnography such kind of situation ? (I do steganography my pc and take stego image photo from android camara and try to decode it)
Hi everyone and happy new year 2020,
I need to set up different image dimensions for each category of a website.
To set these dimensions for Category 1:
Catalog Images = 240 x 320px
Single Product Image = 470 x 627px
Product thumbnails = 75 x 100px
And these dimensions for category 2:
Catalog Images = 245 x 245px
Single Product Image = 470 x 470px
Product thumbnails = 75 x 75px
I use woocommerce.
How to do this? Is there any code or filter to affect to that a named…
Custom image dimensions for each category
I am creating a second level Warlock and I was planning on taking the Misty Visions Invocation. This Invocation gives the ability to cast Silent Image at will. I have been doing a search online for uses of this spell and I constantly see posts on various websites saying to make X creatures doing whatever. I have seen nowhere a post saying it is not possible. I have found a question on here Does the Major Image spell allow the caster to fill the 20 ft cube with as many "body doubles" as he/she sees fit? asking about Major Image doing it and it was said it is not possible. That is a different spell and of a higher level. I would assume that it is not possible to create multiples in the 15ft cube but I can’t find anything stating that fact.
Can Silent Image create multiple creatures or objects in the space alloted to the spell on one casting?
I use python3 to find out the proportion of the mentioned image features. They are originally 8-bit greyscale TIFF images with a resolution of 2048×2168 pixels. I have binarised it into an image composing of the matrix (white) and component particles (black). The particles have random morphologies. I would like to widely categorise them as:
- Points which can range between 1×1 to 3×3 blocks of independent square pixels completely surrounded by the matrix
- Threads which are linear or diagonal sets of continuous pixels of at least 3 pixels in length and at most 3 pixels in width
- Clusters which are any randomly shaped closed morphologies with more than 10 pixels in overall area (or any arbitrary high value)
- Others which by any chance is not included the three listed above
Here is an Example(400×400) portion of the image.
First of all, I am confused about the order of progress in this situation. I could scan the whole image pixel by pixel and extract the points in my first step. A second scanning can see for threads and final scanning can look for clusters using boundary tracing.
As you can see, the component is spread in a very uneven manner. To a human eye, the threads appear as blocks with very low aspect ration (AR). Points as noises and clusters as blocks of distinguishable larger areas. Therefore the accuracy level of this classification scheme does not needfully be a high score. The objective, however, is minimal user interaction (fully automatic). One another thing to note is that holes within clusters or threads (that does not break it) can be ignored. The ultimate aim is to get the area percentage of each of the objects so that the detection method can be limited keeping it in mind.
Some specific questions:
- Let us say that I identify a large cluster of pixels within the image. How can I split this into a surface (high AR) and thread (low AR)? (something similar to Watershed Algorithm)
- Should I go for the OpenCV contouring method like Border Following or border tracing (and later ignoring the holes) or something more suitable
- I was curious to know if there have been approaches in the past that used random sampling of pixels instead of a pixel by pixel scanning across the entire image.
I would like to know the steps a computer scientist would follow in such a scenario. I am a beginner in image processing and any reference material would be appreciated. For anybody interested in metallography, the images are micrographs and what we see are defects. I am trying to separate cracks, porosities and other openings based on pixel density.
Can the “Minor Illusion” cantrip or “Silent Image” spell be used to emulate the casting of other spells?
Thus hopefully tricking another spell caster into wasting a 3rd lvl or higher spell slot to cast “Counterspell” or “Dispel”?
If you have played any spellcaster capable of casting Counterspell you know every time someone announces what spell they are casting like a well placed “Fireball” you or your foe jumps right up screaming “Counterspell”. So far I have seen no one describe the visual appearance of the casting of a spell any spell other than a DM before/after announcing the spell´s name and level.
I’m specifically thinking of using the cantrip to emulate the casting of a different spell, not the effect. Just enough of a deception attempt to look like a spell is starting to complete casting, to make another spellcaster react.
A ball of fire to emulate Fireball or a similar imagery like a bright glow at the tip of the PCs pointing finger to emulate the casting of said spell or even “Delayed Fireblast Fireball”.
Covering yourself in illusory flames to emulate “Investiture of Flame”.
Making your hand glow brightly to emulate “Sunbeam”.
A levitating disk of light to emulate “Portal”
I expect that in most of these cases an opposed or contested ability check would be required from one or both spell casters.
At a 60ft distance (maximum range for Counterspell) you would not hear the verbal incantations nor see the somatic movements very clearly if at all. So, the best indication would be any visible change like a glowing hand or finger. “Minor Illusion” only has a Vocal and a Material (a bit of fleece). “Fireball” (for example) has a Vocal (that would not be easy to heard), the Material (tiny ball of sulfur or bat guano) would be in your closed hand/fist (unable to be seen), and the Somatic component could be made mockingly or completely improvised. So, by making your finger glow, you could fool another spellcaster into thinking you are casting “Fireball”.
I’d like to load an image of a series of images on a page. Each image should be different each time the page is visited.
i.e. A different, single, random image (with link) is loaded each time a user visits the page.
Is this possible with JS?
Respect & regards,
As we all know, Gaussian Noise follows Gaussian or Normal distribution, and that distribution follows a $ BELL$ $ CURVE$ .
As we can see that most of the values are centered around the mean.
Now consider this image
When I add Gaussian noise to this image I get something like this
As we can see that the noise appears to be $ UNIFORMLY$ $ DISTRIBUTED$ throughout the image. There is no region where we can say that the noises concentrated around the mean value
So how can these be called Gaussian Noise?
The Code that I have used in octave is given below
pkg load image; I=imread('C:\Users\Hirak\Desktop\apple.jpg'); I=rgb2gray(I); J = imnoise(I,'gaussian',0.02); K = medfilt2(J); imshow(J);