How to Use the Roboflow Model Library

Key Takeaways

they're it's Joseph from Roma flow today I'm gonna show you all about the Robo flow model library and how you can use it to train the highest quality computer vision models on your own custom data sets ok so what is the role model library where can you find the role of full model library and how do you use the ROFL model library to Train high-performing computer vision models well the first thing that you can do is visit models dot Rho F o dot AI now you're directed to this page here you know you'll notice that the rouble phone model library is completely free to use and we support today two types of vision model architectures object detection and classification you'll notice that we have over ten object detection model implementations and over three classification models if there's a model that you want to see support for but you don't see it in the robot flow model library drop us a comment in this video and we'll get back to you about when we plan to support it ok so what's in here the Robo full model library contains overviews of notebooks tutorials and resources so that you can use any computer vision model that you might need for your given problem for example you'll notice that all these obsolete xyn models we actually have some of the same models implemented in different frameworks for example for Yolo v3 we have a Gila v3 implementation in chaos and a yellow 8-3 implementation and pi torch depending on what best suits your needs for faster our CN n we have any limitation both in tensorflow and into Techtron too now let me click into one of these examples you can see what's included in the Robo flow model library so for Yolo v5 for example which is implemented native to PI torch so this is a PI torch implementation we have links to a tutorial so that you can follow along with a blog to train on your custom data set a video which might contain someone that you know or even the source code on the repo on github for you to be able to have the code available for training Gibbs actually down at the time we're recording here it is so you can actually go to the source code and edit and use however you need now the last thing is this : notebook which allows you to train your model using free GPU resources now before I jump into training let me just walk through a few things the room flow model library contains details about each of the models like when they were released the general performance that you can expect the model size how it performs in the cocoa benchmark and a little bit more but I can always go back and have a look at any of these other models too and this allows me to do things like try out a bunch of different model architectures basically for free which allows me to select the best architecture that's best for my problem now you might be wondering how do you decide between computer vision architectures surely it's not just guess and check and you're right we'll do more videos on comparing and contrasting different model architecture decisions but generally choosing one model over another comes down to the age-old speed versus accuracy trade-off if you want a model that's faster generally that model needs to be smaller in parameters which might make it slightly less accurate the inverse is true a model that's more accurate might be generally bigger in its parameters and run a little bit slower as a result another consideration is making sure that you choose a framework that works best for your type of problem so for example if you're doing a framework like I don't know you may be using PI torch or you're gonna use tensorflow light these are all considerations that allow you to decide which architecture is going to work best so let's zoom back into the the Yola v5 example here how do I actually use Yolo v5 with my given data set well I already have my data in Robo full here and I'll put a link in the description for how you can get your data into Robo flow but once it's in there you're able to export that data in any format that you need so for example my chess pieces data set here I have three different versions this version called sample is just a regular old export that just does a type of resize my raw data set and my other data sets etc now when I half my data in rubble flow I've already performed all my annotation checks I've pre-processed it I've done augmentation I've made everything generally work the way that I need it to work the question then becomes how do I get the data from Roma flow in to my model so I can do my training I go in and click export and you'll notice that when you export you're provided with a wide array of different formats so you need to match the format for your images and annotations to the format that the model library calls for so for example if I'm going to use Yolo v5 the pie tours version naturally I'm gonna select a yellow v5 pie George model type that could continue here it zips it up and it gives me the link to my data set if I'm gonna use Yolo v4 darknet which of these do you think I would use hmm I actually don't see you all of you for called out but I do see yellow darknet because Yolo v4 is a part of the darknet family in fact that is the one that I would need to train my Yolo before darknet model on this specific format ok so I'm gonna say them doing Yolo v5 so from the model library I'm in the OB 5 I clicked open the collab notebook so this collab notebook is the Robo flow version of the collab notebook now watch what I'm gonna do here I'm gonna click file save a copy in Drive this creates your own copy of the notebook so now you can make any edits you can run it you can change all sorts of stuff that's what you need to do so up here I'm gonna rename this and call it I don't know demo example river flow custom yellow v5 now once I'm in here I have just a basic Jupiter notebook hosted on Google collab so it runs just like a JUCO notebook where I can run each of my cells with control-enter I can add text cells I can add code cells all that good stuff now this notebook has a lot of documentation about what's happening step by step but generally you just basically run each of the cells one after another and you'll be good to go but you'll note when you get to the step of downloading their correctly form or to format a data set this is where you need to get your data from Robo flow and correct version into this given model so you'll see here this curl link matches what your data set should be so I say your data set here so if I go back to my data set go back to my data set and I click export I wanted Yola v5 I torch continue I get this link and this link is super secret do not share this link with anyone outside of your team oops got a little patient there so with this link you'll notice that my key is intentionally blacked out so you actually can't see my key dear viewer so I'm gonna copy that I'm gonna drop it right on in to this line here now I'm actually not gonna do that on screen because I don't want you to see my data or my key specifically so I've actually already started one demo example over a year and so my demo example over here at the top I dropped in my data set I already cleared the name and then it ran I got my data in here and then I kicked off training for 200 epics and after those 200 epics I get some results so this train train train to Train you can see here that a train for fourteen minutes is all and then I can visualize my results so I can run the next cell after that visualize these output graphs visualize these output graphs and have a look at how my model performed and I see that actually the recall does quite well as does precision and it's leveling off so my model is getting better and I can even see you know my ground truth data my ground truth data with augmentations all those chess pieces I can see my weights and I can run inference with those weights and then I can print out the results of all of those inference from my weights in this exact notebook and you'll notice here that yellow e5 does inference quite quickly quite quickly and when I get my model results back they print out exactly in this Jupiter notebook and so you can see look at this model it does extremely well after just being trained for 200 epochs on how many images on 289 images is all and it does a great job of recognizing all these pieces and then I could go ahead and export my weights into my Google Drive folder I could download them I can do whatever I want and the nice thing is that I can do this for any of these notebooks that I find in the robo flow model library so if I want to do the same thing for Yolo before darknet I would grab the Yolo v4 darknet no book I would file save a copy to drive get my link drop it in run my selves and bam I have a trained yo la vie for model that could compare head to head so that's largely it each of these models are already for you to use and we're constantly improving them and constantly adding more drop a comment for models that you want to see us add to the Robo phone model library and don't forget to Like and subscribe to the rubble flow channel so that you can be updated when we post more content happy training and good luck