I'm trying to figure out what the best way to generate a hashlist of nfts from a collection with a specific trait...not sure if there is an existing tool or script that can accomplish this? For example, say a collection has three traits: red, green, blue. I would like to be able to create a hashlist of just the nfts with the red trait.
Have looked at magiceden's hashlist generator but it only seems to generate the whole collection list and has no options for doing it by specific trait...Any assistance or direction on this would be greatly appreciated - cheers!
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I am writing an webapp for a used thrift store. We are planning to add all items to a database, and I will be using Laravel and MySQL for this.
We also want to get a barcode scanner in order to scan and add items.
But I've never worked with barcodes before and info regarded this for a website like mine is hard to find info on, so is the barcode-scanners so I'm asking help from someone with experience.
I'm not sure which barcodes we should use, but I'm thinking a 3D one, like QR would do good. I've found several qr-generators, but I'm unsure on how I should create them properly from items.
Say the store is named Brukten. And it has items, with number IDs. Should I then generate barcodes out of "Brukten_53" or something, or just the ID, or how is a smart way? Because I can use an option like this instead of storing the generated barcode, right, and its better to generate a QR each time instead of storing the data about it?
At first we will use a web interface to add items, and later on we want to get a barcode-scanner to help scan things, so I'm guessing it would be nice with a scanner that could take pictures and add to database. So we want the DB to be ready for this, and properly made to work with such systems. So I'm wondering also if anyone can recommend me a device for this. I've seen several but unsure what to choose. 2d, 3d, something with camera, or is there other devices we could use?
What we want a device for is:
We want to store in the db: Old things, new things
We want to retrieve: all things
We want to alter info: edit things, sell, check things
Something easier than going around with a laptop, phone or a tablet and entering stuff.
Building the site is no problem for me, PHP, MySQL, Laravel framework and all is old stuff, but barcodes is a new world for me.
You only have to make sure that every single distinct physical item has a unique ID.
A simple way to accomplish this is using category ids as prefixes.
Suppose your "used men clothes category" is ID 25, and when you enter a pair on jeans of that category into the system, you app assign them ID 12345.
You can reference that item as 002500012345. You only need to calculate the 13rd digit using this function (http://edmondscommerce.github.io/php/barcode/ean13-barcode-check-digit-with-php.html) and you have a full-fledged EAN13 barcode you can print using this font (http://www.fontpalace.com/font-details/EAN-13/) and read with virtually any code scanner.
The other approach is generating a unique url for each product:
http://www.example.com/25/12345.html
And embed the url into a QR code.
You can generate the image for the QR code using this library:
http://phpqrcode.sourceforge.net/
I think I'm missing something fundamental about CouchDB views.
Let's say I'm storing cars in a database. I want to get all cars that are blue or red, but NOT green, AND they are Hondas. But this query is dynamic using keys. How do?
Map Function:
function(car) {
emit([car.color, car.make],car);
}
I can't find a way to format keys to make anything like this possible. I'm not married to this map function either, I just want to know how someone would handle a request like this on the fly. Do you have to just narrow it down as far as possible in Couch and then do more process with the returned data? Seems like there should be a way to do this...
One option would be to include the keys parameter with your query:
http://localhost:5984/cars/_design/all-cars/_view/by-color-and-make?keys=[["red","honda"],["blue","honda"]]
More likely though, you have a search page with a bunch of different characteristics, and the user is picking and choosing values to search by. They might choose 4 door, all wheel drive, and priced below 10,000.
You won't be able to make views to satisfy all the different combinations. couchdb-lucene is a good option to solve this problem.
And if you use cloudant.com, it's automatically included: https://cloudant.com/for-developers/search/
I am new at the idea of programming algorithms. I can work with simplistic ideas, but my current project requires that I create something a bit more complicated.
I'm trying to create a categorization system based on keywords and subsets of 'general' categories that filter down into more detailed categories that requires as little work as possible from the user.
I.E.
Sports >> Baseball >> Pitching >> Nolan Ryan
So, if a user decides they want to talk about "Baseball" and they filter the search, I would like to also include 'Sports"
User enters: "baseball"
User is then taken to Sports >> Baseball
Now I understand that this would be impossible without a living - breathing dynamic program that connects those two categories in some way. It would also require 'some' user input initially, and many more inputs throughout the lifetime of the software in order to maintain it and keep it up to date.
But Alas, asking for such an algorithm would be frivolous without detailing very concrete specifics about what I'm trying to do. And i'm not trying to ask for a hand out.
Instead, I am curious if people are aware of similar systems that have already been implemented and if there is documentation out there describing how it has been done. Or even some real life examples of your own projects.
In short, I have a 'plan' but it requires more user input than I really want. I feel getting more info on the subject would be the best course of action before jumping head first into developing this program.
Thanks
IMHO It isn't as hard as you think. What you want is called Tagging and you can do it Automatically just by setting the correlation between tags (i.e. a Tag can have its meaningful information plus its reation with other ones. Then, if user select a Tag well, you related that with others via looking your ADT collection (can be as simple as an array).
Tag:
Sport
Related Tags
Football
Soccer
...
I'm hoping this helps!
It sounds like what you want to do is create a tree/menu structure, and then be able to rapidly retrieve the "breadcrumb" for any given key in the tree.
Here's what I would think:
Create the tree with all the branches. It's okay if you want branches to share keys - as long as you can give the user a "choice" of "Multiple found, please choose which one... ?"
For every key in the tree, generate the breadcrumb. This is time-consuming, and if the tree is very large and updating regularly then it may be something better done offline, in the cloud, or via hadoop, etc.
Store the key and the breadcrumb in a key/value store such as redis, or in memory/cached as desired. You'll want every value to have an array if you want to share keys across categories/branches.
When the user selects a key - the key is looked up in the store, and if the resulting value contains only one match, then you simply construct the breadcrumb to take the user where you want them to go. If it has multiple, you give them a choice.
I would even say, if you need something more organic, say a user can create "new topic" dynamically from anywhere else, then you might want to not use a tree at all after the initial import - instead just update your key/value store in real-time.
I'm really stuck right now. I want to apply LIBSVM for Image Classification. I captured lots of Training-Images (BITMAP-Format), from which I want to extract features.
The Training-Images contain people who are lying on the floor. The classifier should decide if there is a person lying on the floor or not in the given Image.
I read lots of papers, documentary, guides and tutorials, but in none of them is documented how to get a LIBSVM-Package. The only thing that is described is how to convert a LIBSVM-Package from a CSV-File like this one: CSV-File. On the LIBSVM-Website several Example-Data can be downloaded. The Example-Data is either prepared as CSV-Files or as ready-to-use Training- and Testdata.
If you look at the Values which are in the CSV-File, the first column are the labels (lying person or not) and the other Values are the extracted features, but I still can't reconstruct how those values are achieved.
I don't know if it's that simple that nobody has to mention it, but I just can't get trough it, so if anybody knows how to perform the feature extraction from Images, please help me.
Thank you in advance,
Regards
You need to do feature extraction first. There are many methods that are available. These include LBP,Gabor and many more.. These methods will help you get the features to input into libsvm..Hope this helps...
I am looking for some sort of code to add members to a Distribution List in GAL. We are moving to a new DL naming convention in the new system and I need to add hundreds of users to new distribution lists without fail. Manually doing this will take ages and I am looking for achieving this programmatic-ally.. I was searching for the past 4hrs with no luck. I don't even know where to start. Any help is appreciated...
http://msdn.microsoft.com/en-us/library/bb645998.aspx