We are looking to build a single pipeline within a code repository that cleans, harmonizes, and transforms data to features of interest. We would like to apply that single pipeline code on different inputs and then test how the outputs look.
For example, we would like to test the pipeline on synthetic data, version 1 of 'real' data that includes only retrospective data, and version 2 of 'real' data that includes retrospective and prospective data. The comparison of the outputs could be what percent of patients had diabetes in version 1 compared to version 2.
I saw that you could template code repositories in foundry. Is this a viable option? Could you template your code repository and apply to the three scenarios I have provided? Is there a better option?
If your data scale is reasonably small, I would recommend going down the test-driven path of development here instead of trying to compare and contrast results across a wide variety of datasets. You'll find the iteration time and difficulty in exactly comparing results probably quite high.
For this, you should follow the method I lay out here and create representative datasets for each input you expect as a .csv file in your repo, then you can incorporate these schemas as a unique input to your core code and inspect the outputs with ease.
This will let you 'tighten' your code much easier and faster, after which you can then run this logic on real full-scale data and generate your outputs as you wish.
Templating code is possible but should be incorporated with great care. If what you're truly solving for is comparing and contrasting the execution of your code on arbitrary schemas, then you should use test-driven in-repo development. If what you're after is running a core set of logic across a wide variety of outputs after the code is working, then generated transforms is going to work great. If what you're really after is rolling out a large codebase of transformations across differently-permissioned projects where each needs to be completely independent / configured separately of the other, then maybe you should consider templates. I would stick to test-driven development and generated transforms until you prove otherwise.
I’m new to deep learning and I was reading some state of art papers and I found that mask r-cnn is utterly used in segmentation and classification of images. I would like to apply it to my MSc project but I got some questions that you may be able to answer. I apologize if this isn’t the right place to do it.
First, I would like to know what are the best strategy to get the annotations. It seems kind of labor intensive and I’m not understanding if there is any easy way. Following that, I want to know if you know any annotation tool for mask r-cnn that generates the binary masks that are manually done by the user.
I hope this can turn into a productive and informative thread so any suggestion, experience would be highly appreciated.
Regards
You can use MASK-RCNN, I recommend it, is a two-stage framework, first you can scan the image and generate areas likely contain an object. And the second stage classifies the proposal drawing bounding boxes.
But the two-big question
how to train a model from scratch? And What happens when we want to
train our own dataset?
You can use annotations downloaded from the internet, or you can start creating your own annotations, this takes a lot of time!
You have tools like:
VIA GGC image annotator
http://www.robots.ox.ac.uk/~vgg/software/via/via_demo.html
it's online and you don't have to download any program. It is the one that I recommend you, save the images in a .json file, and so you can use the class of ballons that comes by default in SAMPLES in the framework MASK R-CNN, you would only have to put your json file and your images and to train your dataset.
But there are always more options, you have labellimg which is also used for annotation and is very well known but save the files in xml, you will have to make a few changes to your Class in python. You also have labelme, labelbox, etc.
I'm working on a project that uses parallel methods to convert text from one form to another. We're going to implement a CSV to JSON converter to demonstrate the speedups that are possible using our parallel framework.
We want to benchmark our converter once it's finished. What are the fastest libraries/stand-alone programs/etc out there that are capable of doing CSV-JSON conversion? I found a list of potential candidates here:Large CSV to JSON/Object in Node.js, but I'm not sure how fast the listed options are. In the worst case I'll benchmark them myself, but if someone already knows what the "best in class" converters are it'd save me some time.
Looks like the maintainer of csvtojson has developed a benchmark application. I think I can add my csv to json converter to his benchmark project to test my converter.
if your project can consider in-browser apps, I suggest csvtojson as it is by far the speediest converter on the market as of 2017.
I created it myself so I may be a bit biaised, but I specifically developed it for a bigger project that required big csv to json crunching.
Tell me if it served.
I'm looking for some simple (free!) entry level software that will allow me to create simple 3d models and export them in a format (JSON?) that can then be read into a webGL programme.
Simple geometry would be a start, then textures would be nice too... I've looked at Blender, and it's just far too advanced for me, and the tutorials I've found are hopeless.
Something simple like sketchup would be good, but afaik you can't export in JSON. I've found some converters that will do .dae to .json, but the ones I've found seem to be for advanced users.
WebGL is new enough that there aren't many packages like this built up around it just yet. That doesn't mean you don't have some options though:
Blender is a good modeler, and if you are willing to put a little bit more time into learning it you can use exporters from Three.js or some others that are around the net. This seems to be the most popular option at the moment.
Unity 3D is more of a scene builder than a modeling app, but it has a lot of ways to get content into it and both J3D and myself have implemented exporters from it.
Maya is a great modeling tool if you have a way to get access to it (it's commercial), and has Inka to get WebGL content out.
If you want to use something like SketchUp, it should be able to export to COLLADA, which can then be imported into Blender/Unity/What have you and exported from there using one of the previous methods.
As far as formats go, there's no real standards just yet. Most of the exporters will spit out JSON, mine uses a mix of JSON and Binary for speed/size, and some will actually give you Javascript code to execute. Which format to use probably depends on what you want to do with it. I encourage you to experiment with several and see what you like and what you don't.
I have encountered this topic lately and couldn't understand why they are needed.
Can you explain why I should use them in my projects and how they can ease my life.
Examples will be great, and where from I can learn this topic little more.
At least you have framed the question from the correct perspective =)
The usual reasons for using a code generator are given as productivity and consistency because they assume that the solution to a consistent and repetitive problem is to throw more code at it. I would argue that any time you are considering code generation, look at why you are generating code and see if you can solve the problem through other means.
A classic example of this is data access; you could generate 250 classes ( 1 for each table in the schema ) effectively creating a table gateway solution, or you could build something more like a domain model and use NHibernate / ActiveRecord / LightSpeed / [pick your orm] to map a rich domain model onto the database.
While both the hand rolled solution and ORM are effectively code generators, the primary difference is when the code is generated. With the ORM it is an implicit step that happens at run-time and therefore is one-way by it's nature. The hand rolled solution requires and explicit step to generate the code during development and the likelihood that the generated classes will need customising at some point therefore creating problems when you re-generate the code. The explicit step that must happen during development introduces friction into the development process and often leads to code that violates DRY ( although some argue that generated code can never violate DRY ).
Another reason for touting code generation comes from the MDA / MDE world ( Model Driven Architecture / Engineering ). I don't put much stock in this but rather than providing a number of poorly expressed arguments, I'm simply going to co-opt someone elses - http://www.infoq.com/articles/8-reasons-why-MDE-fails.
IMHO code generation is the only solution in an exceedingly narrow set of problems and whenever you are considering it, you should probably take a second look at the real problem you are trying to solve and see if there is a better solution.
One type of code generation that really does enhance productivity is "micro code-generation" where the use of macros and templates allow a developer to generate new code directly in the IDE and tab / type their way through placeholders (eg namespace / classname etc). This sort of code generation is a feature of resharper and I use it heavily every day. The reason that micro-generation benefits where most large scale code generation fails is that the generated code is not tied back to any other resource that must be kept in sync and therefore once the code is generated, it is just like all the other code in the solution.
#John
Moving the creation of "basic classes" from the IDE into xml / dsl is often seen when doing big bang development - a classic example would be developers try to reverse engineer the database into a domain model. Unless the code generator is very well written it simply introduces an additional burden on the developer in that every time they need to update the domain model, they either have to context-switch and update the xml / dsl or they have to extend the domain model and then port those changes back to the xml / dsl ( effectively doing the work twice).
There are some code generators that work very well in this space ( the LightSpeed designer is the only one I can think of atm ) by acting as the engine for a design surface but often
these code generators generate terrible code that cannot be maintained (eg winforms / webforms design surfaces, EF1 design surface) and therefore rapidly undo any productivity benefits gained from using the code generator in the first place.
Well, it's either:
you write 250 classes, all pretty much the same, but slightly different, e.g. to do data access; takes you a week, and it's boring and error-prone and annoying
OR:
you invest 30 minutes into generating a code template, and let a generation engine handle the grunt work in another 30 minutes
So a code generator gives you:
speed
reproducability
a lot less errors
a lot more free time! :-)
Excellent examples:
Linq-to-SQL T4 templates by Damien Guard to generate one separate file per class in your database model, using the best kept Visual Studio 2008 secret - T4 templates
PLINQO - same thing, but for Codesmith's generator
and countless more.....
Anytime you need to produce large amounts of repetetive boilerplate code, the code generator is the guy for the job. Last time I used a code generator was when creating a custom Data Access Layer for a project, where the skeleton for various CRUD actions was created based on an object model. Instead of hand-coding all those classes, I put together a template-driven code generator (using StringTemplate) to make it for me. The advandages of this procedure was:
It was faster (there was a large amount of code to generate)
I could regenerate the code in a whim in case I detected a bug (code can sometimes have bugs in the early versions)
Less error prone; when we had an error in the generated code it was everywhere which means that it was more likely to be found (and, as noted in the previous point, it was easy to fix it and regenerate the code).
Using GUI builders, that will generate code for you is a common practice. Thanks to this you don't need to manually create all widgets. You just drag&drop them and the use generated code. For simple widgets this really saves time (I have used this a lot for wxWidgets).
Really, when you are using almost any programming language, you are using a "code generator" (except for assembly or machine code.) I often write little 200-line scripts that crank out a few thousand lines of C. There is also software you can get which helps generate certain types of code (yacc and lex, for example, are used to generate parsers to create programming languages.)
The key here is to think of your code generator's input as the actual source code, and think of the stuff it spits out as just part of the build process. In which case, you are writing in a higher-level language with fewer actual lines of code to deal with.
For example, here is a very long and tedious file I (didn't) write as part of my work modifying the Quake2-based game engine CRX. It takes the integer values of all #defined constants from two of the headers, and makes them into "cvars" (variables for the in-game console.)
http://meliaserlow.dyndns.tv:8000/alienarena/lua_source/game/cvar_constants.c
Here is the short Bash script which generated that code at compile-time:
http://meliaserlow.dyndns.tv:8000/alienarena/lua_source/autogen/constant_cvars.sh
Now, which would you rather maintain? They are both equivalent in terms of what they describe, but one is vastly longer and more annoying to deal with.
The canonical example of this is data access, but I have another example. I've worked on a messaging system that communicates over serial port, sockets, etc., and I found I kept having to write classes like this over and over again:
public class FooMessage
{
public FooMessage()
{
}
public FooMessage(int bar, string baz, DateTime blah)
{
this.Bar = bar;
this.Baz = baz;
this.Blah = blah;
}
public void Read(BinaryReader reader)
{
this.Bar = reader.ReadInt32();
this.Baz = Encoding.ASCII.GetString(reader.ReadBytes(30));
this.Blah = new DateTime(reader.ReadInt16(), reader.ReadByte(),
reader.ReadByte());
}
public void Write(BinaryWriter writer)
{
writer.Write(this.Bar);
writer.Write(Encoding.ASCII.GetBytes(
this.Baz.PadRight(30).Substring(0, 30)));
writer.Write((Int16)this.Blah.Year);
writer.Write((byte)this.Blah.Month);
writer.Write((byte)this.Blah.Day);
}
public int Bar { get; set; }
public string Baz { get; set; }
public DateTime Blah { get; set; }
}
Try to imagine, if you will, writing this code for no fewer than 300 different types of messages. The same boring, tedious, error-prone code being written, over and over again. I managed to write about 3 of these before I decided it would be easier for me to just write a code generator, so I did.
I won't post the code-gen code, it's a lot of arcane CodeDom stuff, but the bottom line is that I was able to compact the entire system down to a single XML file:
<Messages>
<Message ID="12345" Name="Foo">
<ByteField Name="Bar"/>
<TextField Name="Baz" Length="30"/>
<DateTimeField Name="Blah" Precision="Day"/>
</Message>
(More messages)
</Messages>
How much easier is this? (Rhetorical question.) I could finally breathe. I even added some bells and whistles so it was able to generate a "proxy", and I could write code like this:
var p = new MyMessagingProtocol(...);
SetFooResult result = p.SetFoo(3, "Hello", DateTime.Today);
In the end I'd say this saved me writing a good 7500 lines of code and turned a 3-week task into a 3-day task (well, plus the couple of days required to write the code-gen).
Conclusion: Code generation is only appropriate for a relatively small number of problems, but when you're able to use one, it will save your sanity.
A code generator is useful if:
The cost of writing and maintaining the code generator is less than the cost of writing and maintaining the repetition that it is replacing.
The consistency gained by using a code generator will reduce errors to a degree that makes it worthwhile.
The extra problem of debugging generated code will not make debugging inefficient enough to outweigh the benefits from 1 and 2.
For domain-driven or multi-tier apps, code generation is a great way to create the initial model or data access layer. It can churn out the 250 entity classes in 30 seconds ( or in my case 750 classes in 5 minutes). This then leaves the programmer to focus on enhancing the model with relationships, business rules or deriving views within MVC.
The key thing here is when I say initial model. If you are relying on the code generation to maintain the code, then the real work is being done in the templates. (As stated by Max E.) And beware of that because there is risk and complexity in maintaining template-based code.
If you just want the data layer to be "automagically created" so you can "make the GUI work in 2 days", then I'd suggest going with a product/toolset which is geared towards the data-driven or two-tier application scenario.
Finally, keep in mind "garbage in=garbage out". If your entire data layer is homogeneous and does not abstract from the database, please please ask yourself why you are bothering to have a data layer at all. (Unless you need to look productive :) )
How 'bout an example of a good use of a code generator?
This uses t4 templates (a code generator built in to visual studio) to generate compressed css from .less files:
http://haacked.com/archive/2009/12/02/t4-template-for-less-css.aspx
Basically, it lets you define variables, real inheritance, and even behavior in your style sheets, and then create normal css from that at compile time.
Everyone talks here about simple code generation, but what about model-driven code generation (like MDSD or DSM)? This helps you move beyond the simple ORM/member accessors/boilerplate generators and into code generation of higher-level concepts for your problem domain.
It's not productive for one-off projects, but even for these, model-driven development introduces additional discipline, better understanding of employed solutions and usually a better evolution path.
Like 3GLs and OOP provided an increase in abstraction by generating large quantities of assembly code based on a higher level specification, model-driven development allows us to again increase the abstraction level, with yet another gain in productivity.
MetaEdit+ from MetaCase (mature) and ABSE from Isomeris (my project, in alpha, info at http://www.abse.info) are two technologies on the forefront of model-driven code generation.
What is needed really is a change in mindset (like OOP required in the 90's)...
I'm actually adding the finishing touches to a code generator I'm using for a project I've been hired on. We have a huge XML files of definitions and in a days worth of work I was able to generate over 500 C# classes. If I want to add functionality to all the classes, say I want to add an attribute to all the properties. I just add it to my code-gen, hit go, and bam! I'm done.
It's really nice, really.
There are many uses for code generation.
Writing code in a familiar language and generating code for a different target language.
GWT - Java -> Javascript
MonoTouch - C# -> Objective-C
Writing code at a higher level of abstraction.
Compilers
Domain Specific Languages
Automating repetitive tasks.
Data Access Layers
Initial Data Models
Ignoring all preconceived notions of code-generation, it is basically translating one representation (usually higher level) to another (usually lower level). Keeping that definition in mind, it is a very powerful tool to have.
The current state of programming languages has by no means reached its full potential and it never will. We will always be abstracting to get to a higher level than where we stand today. Code generation is what gets us there. We can either depend on the language creators to create that abstraction for us, or do it ourselves. Languages today are sophisticated enough to allow anybody to do it easily.
If with code generator you also intend snippets, try the difference between typing ctor + TAB and writing the constructor each time in your classes. Or check how much time you earn using the snippet to create a switch statement related to an enum with many values.
If you're paid by LOC and work for people who don't understand what code generation is, it makes a lot of sense. This is not a joke, by the way - I have worked with more than one programmer who employs this technique for exactly this purpose. Nobody gets paid by LOC formally any more (that I know of, anyway), but programmers are generally expected to be productive, and churning out large volumes of code can make someone look productive.
As an only slightly tangential point, I think this also explains the tendency of some coders to break a single logical unit of code into as many different classes as possible (ever inherit a project with LastName, FirstName and MiddleInitial classes?).
Here's some heresy:
If a task is so stupid that it can be automated at program writing time (i.e. source code can be generated by a script from, let's say XML) then the same can also be done at run-time (i.e. some representation of that XML can be interpreted at run-time) or using some meta-programming. So in essence, the programmer was lazy, did not attempt to solve the real problem but took the easy way out and wrote a code generator. In Java / C#, look at reflection, and in C++ look at templates