Many tasks in computer vision require images taken in the wild (ie. Road, Events, etc. ), but building a Dataset for Human behavior related task can be tricky. GDPR does not allow storage of pictures taken without consent, that’s normal you might say !
It would be a shame to limit AI applications due to GDPR right ? At Picsell.ia, we are dedicated to help people build better CV models, so that was kind of obvious for us to build an anonymizer that could help you build GDPR-Compliant Human-related Dataset !
At Picsell.ia, we are devoted to provide the most efficient way to build a computer vision system at low cost.
As everyone know, the labeling and training costs for deep learning are high, but over the past few years, we saw the emergence of interesting techniques to make it more affordable.
Today, I’ll talk about 2 of them:
This will be a bit long, so grab a cup of coffee and get ready to dive behind the scenes of Picsell.ia platform with me.
Summer is coming, you are probably going to dive into the ocean soon, but you definitely don’t want to be surrounded by trashes in the water. That is one of the reason we started to create the trashes detector in water.
During the Part I, we fine tuned a Faster-RCNN model pre-trained on COCO on the Dataset Taco trashes, but the results were not very accurate. In fact we figured out after looking for a loophole that there were several metadata of pictures among the Dataset that involved issues.
Therefore, as we succeeded in fixing this, we are now in…
As we try to keep you updated every weeks on the new datasets that have been made available publicly on our platform, here is a short list of what has been added recently.
You may have read this article from last week about how we can build a trash detector helping to clean the oceans, the Dataset used in this project is the “Taco Trash Dataset” and has the particularity to be build with extremely precise segmentation of trashes.
An estimated 5 to 25 million tons of plastic are thrown in our oceans every year. Although we know that those devastating trashes for biodiversity and environment mainly come from rivers and beaches, it remains really tough to catch them all, especially in some poor and neglected countries.
From this observation, we decided to consider a solution using deep learning to detect rubbish with a camera.
Is it possible to generate a trash detector which would be the first step to clean up our rivers?
Such an issue is the kind we want to address at Picsell.ia.
Sometimes it’s complicated to run several models against each other to find the most efficient, not the right environment, lost the weights, can’t run the program on someone else’s PC …
That’s why we created the “Playground”, where you will be able to run inference on images of your choice with some of the models you trained before (or some you found in our Hub), and see the results on any of your images.
Whether you used a segmentation, object detection or classification model, you will be able to see what your model predicts for your images. And above all…
The quest for the perfect Dataset for your project is always a never ending story. But what if I told you that those times spending weeks on the Internet searching for data are finally over ?
Actually, among all the Datasets that we or some of our users have released on our Hub, you will certainly find the perfect fit.
By going to our Dataset Hub, you will be able to navigate through our public Datasets.
Here are three examples of Datasets recently released that could interest you :
Every new Computer Vision experiment is the same story
And then it’s only one training but now you have to fine-tune your model, compare the…
Today is a big day for us at Picsell.ia as we have just released a brand new version of our platform. We chose to focus on the tech during the recent crisis in order to bring up a totally new and more complete solution that what we had earlier (an image annotation platform).
Although the image annotation is still available in the platform, we now include what we called the “Open Datasets Hub”.
TLDR: You can find every free public dataset on our platform at www.picsellia.com
It’s a place where every user on the platform can publish Dataset and make…
Even if those fields are already known for their AI exploits, there has been unexpected events recently which makes me believe that they will continue to grow exponentially in 2020, let’s see why together !
The recent events with the COVID19 epidemic gave birth to new breakthroughs in Artificial Intelligence and noticeably for the computer vision field.
Indeed, the signs of pneumonia caused by the coronavirus can now be detected from CT lung scans as it was done for lung cancer few years ago.
Several companies, including Alibaba, Infervision and Ping An, studied how to detect the virus really soon…
CEO at Picsell.ia & AI engineer