Hello I have the following problem.
I have a product with two different options, size and color. But I didn't know how to related this options when someone is buying a product. For example.
I have 4 T-shirt on my inventory
2 Blue T-shirt size S
1 Green T-shirt size L
1 Yellow T-shirt size XL
I configured the product with these requirement options (size and color), but for example a customer can buy a T-shirt size XL color blue and that's wrong because I didn't have a way to related the color with the size. Any Idea, plugin or suggestion???
Thanks I'd appreciate your help.
take a look in the extension store for dependent options. that seems to be the thing you are after
There is an extension designed for this Related options for OpenCart
Related
I am visualizing sentence embedding using tensorboard. I have label for each sentence embedding. How can I set a color for each label?
For example
embedding vector Labels
[0.2342 0.2342 0.234 0.8453] A
[0.5342 0.9342 0.234 0.1453] B
[0.7342 0.0342 0.124 0.8453] C
[0.8342 0.5342 0.834 0.5453] A
I am able to visualize the embedding vector where each row is labeled by its label. I want to set colors also so that I see points with same label will have same color. Like all "A" will be red, "B" will be green, "C" will be blue and so on?
I searched on Google but didn't get any sample.
Could anyone please share some code to get it done?
Thank you in advanced.
There should be a colour by drop down that you can use.
In case that is not showing up, one of the possible reason could be that you have more than 50 unique labels, which is the hardcoded limit in the current tensorflow code.
Refer to this thread for details.
https://github.com/tensorflow/tensorboard/issues/61
I am having a little but pretty serious problem with opencart inventory control.
Lets say I have a Shirt with 3 colors (Red, Black, White) and 3 sizes (S, M, L) and want to specify quantity for each size and color so, when Red in S is sold old, it should only deduct 1 from Red and not the whole stock/option.
I hope you got my point.
Thank you
That's not possible in the way you described with OpenCart out of the box. You'll either need a third party extension or you need to structure your options explicitly like:
Red S
Red M
Red L
Black S
Black M
Black L
White S
White M
White L
This way you can specify stock amounts for each one and disable them as needed when out of stock.
I had come across several stack overflow questions and solutions, in all the questions the solution is based on a particular color(red or green or blue). I need to identify the color of objects which are of multiple type. I need to detect color which ranged between 0 to 255. So can anybody help me with a solution based on opencv.
Thanks in advance.
If you already know about what could be the possible color then it very simple. I will talk about one example and you can follow the same procedure for rest.
Lets say that you have several possible combinations, for example a t-shirt could have red and cyan color and you already have an image of such a sample. Then you should do the following:
Step-1: Load the template/sample image. Calculate its Hue-histogram (or Hue-Saturation histogram).
Step-2: Load the image for which you want to know the color. Calculte the histogram for this image also.
Step-3: Perform histogram matching() between all the sample/template/example/possbile image's histogram (i.e. step-1) and the image for which you want to know the color (i.e. step-2).
Step-4: For which so ever combination, you get the maximum value...your image has that color. For example, lets say your sample images have an image of red & cyan t-shirt, another image of bule & purple t-shirt and so on. And you get the maximum histogram matching() value for blue& purple , it means that your image for which you want to know have blue and purple color.
The 2nd problem in IOI 2013 states:
You have an Art History exam approaching, but you have been paying
more attention to informatics at school than to your art classes! You
will need to write a program to take the exam for you.
The exam will consist of several paintings. Each painting is an example of one of
four distinctive styles, numbered 1, 2, 3 and 4. Style 1 contains
neoplastic modern art. Style 2 contains impressionist landscapes.
Style 3 contains expressionist action paintings. Style 4 contains
colour field paintings.
Your task is, given a digital image of a painting, to determine which style the painting belongs to.
The image will be given as an H×W grid of pixels. The rows of
the image are numbered 0, …, (H 1) from top to bottom, and the
columns are numbered 0, …, W 1 from left to right. The pixels are
described using twodimensional arrays R , G and B , which give the
amount of red, green and blue respectively in each pixel of the image.
These amounts range from 0 (no red, green or blue) to 255 (the maximum
amount of red, green or blue).
Implementation
You should submit a file
that implements the function style(), as follows:
int style(int H, int W, int R[500][500], int G[500][500], int B[500][500]);
This function should determine the style of the image. Parameters are:
H: The number of rows of pixels in the image.
W: The number of columns of pixels in the image.
R: A twodimensional array of size H×W , giving the amount of red in each pixel of the image.
G: A twodimensional array of size H×W , giving the amount of green in each pixel of the image.
B: A twodimensional array of size H×W , giving the amount of blue in each pixel of the image.
Example pictures are in the problem PDF
I do not want a readymade program. A hint or two to get me started would be nice, as I am clueless about this might be solved.
Since you are provided the image data in RGB format, first prepare a copy of the same image data in YUV. This is essential as some of the image features are easily identified patterns in the Luma(Y) and Chroma(U,V) maps.
Based on the samples provided, here are some of the salient features of each "style" of art :
Style1 - Neoplastic modern art
Zero graininess - Check for large areas with uniform Luma(Y)
Black pixels at edges of the areas(transition between different chroma).
Style2 - Impressionist landscapes
High graininess - Check for high entropy (salt-n-pepper-noise like) patterns in Luma(Y).
Pre-dominantly green - High values in green channel.
Greenavg >> Redavg
Greenavg >> Blueavg
Style3 - Expressionist action paintings
High graininess - Check for high entropy (salt-n-pepper-noise like) patterns in Luma(Y).
NOT green.
Style4 - Color field paintings
Zero graininess - Check for large areas with uniform Luma(Y)
NO black(or near black) pixels at the transition between different chroma.
As long as the input image belongs to one of these classes you should have no trouble in classification by running the image data through functions that are implemented to identify the above features.
Basically it boils down to the following code-flow :
Image has uniform luma?
(If Yes) Image has black pixels at chroma transitions?
(If Yes) Style1
(If No) Style4
(If No) Image is green-ish?
(If Yes) Style2
(If No) Style3
Maybe you can do a first approach using colors and shapes... In neo plastic modern it is likely that there will be only a few number of colors, occupying geometrical areas as in the colour field paintings.
This might gives you a way to differenciate styles 1 and 4 from styles 2 and 3.
In styles 1 and 4 you have large areas with the same color, but in style 4 the color is rarely a solid color but brush strokes of shades of the color.
Anyway you should look into the specialities of each styles, which are the usual colors and methods and then try to make your function "see" it.
I want to develop a program which recolors the input image based on the given theme the same way as ms-powerpoint application does.
I am giving following link that shows what exactly i want to do.
I want to generate images same as images in below link under the Dark Variations and light Variations title based on the current theme.
http://blogs.msdn.com/powerpoint/archive/2006/07/06/658238.aspx
Can anybody give me idea,info regarding how to achieve it efficiently ??
You can give a look to the HSL colorspace to be able to have the same result. HSL means Hue, Saturation, Lightness.
You can keep the lightness of each pixel of your image and change only the hue. I think this will allow you to achieve what you want. You can find the RGB to HSL conversion on the wiki page.
Hope that helps.
Step 1: Choose the colors you want to represent black and white. For the dark variations, choose black and a light color; for the light variations, choose a dark color and white.
Step 2: Convert a pixel to gray. A common formula for this is L = R*0.3 + G*0.59 + B*0.11.
Step 3: Interpolate between the colors using the gray value. output.R = (L/255)*light.R + (1-(L/255))*dark.R and likewise for green and blue.
You can use a library like CxImage and convert the image to grayscale, then use the mix command with another image that you have made that is the same size as the original, and mix the two with the Mix command, using the filters. You can do mix-screen, and this should tint the pixels the color of the second image in the resultant image. Try playing with CxImage a bit, see if it will do what you want it to do. This is all coming off the top of my head, and its been a while since I have tried to do anything like this. YMMV, but this would be the simplest implementation. You could always look at how CxImage does the blend, and apply it to the image yourself.
I must say thanks to Mark and Patrice for ur guidance which helped me achieved it.
For light variation, I have done it by converting the theme colors to HSV colorspace and found relation between output color and theme color for black color (input) .
The relation was found to be linear for saturation and value and hue was almost constant.
I have used interpolation formula to make it generic for any given theme.
I have also make use of color matrix to achieve desired result.
Similarly for dark variation i have used white color as input and apply the same technique.