Recently, Roboflow machine learning engineer Jacob Solawetz sat down with Elisha Odemakinde, an ML researcher and Community Manager at Data Science Nigeria, for a Fireside chat. During the conversation, Jacob
At Roboflow, we often get asked, what is the train, validation, test split and why do I need it? The motivation is quite simple: you should separate you data into train, validation, and test splits to prevent your model from overfitting and to accurately evaluate your model. T
Keeping track of images and their corresponding annotations is a challenge. Knowing which annotations map to which class, viewing image metadata, and seeing which images correspond to a training, validation,
Roboflow is enabling any developer to use computer vision (without being a machine learning expert). Computer vision is the first technology that fundamentally allows us to rewrite human-computer interaction. Until
This guide will take you the long distance from unlabeled images to a working computer vision model deployed and inferencing live at 15FPS on the affordable and scalable Luxonis OpenCV AI Kit (OAK) device.
How Transport for Cairo is Improving Commuting for Millions with Computer Vision Reducing traffic in well-planned cities where bus routes are well-mapped, subways are running on a predictable cadence, and
The below post is a lightly edited guest post from Result! Data, a Netherlands-based consultancy providing leading digital services. The Roboflow team thanks Gerard Mol (Managing Partner) and Brand Hop
With Roboflow Pro, you can now remap and omit class labels within Roboflow as a preprocessing step for your dataset version. Class management is a powerful tool to get the most out of your training data and your hard earned class label annotations.
We appreciate the machine learning community's feedback, and we're publishing additional details on our methodology.(Note: On June 14, we've incorporated updates from YOLOv4 author Alexey Bochkovskiy, YOLOv5 author Glenn
An animated drone flying through a correctly identified gate. (Image provided via Victor Antony, animated by Roboflow)Drones are enabling better disaster response, greener agriculture, safer construction, and so much
Impatient? Jump to our VGG-16 Colab notebook. Image classification models discern what a given image contains based on the entirety of an image's content. And while they're consistently getting better,
The recommended Roboflow setting is "Auto-Orient: Enabled"When should you auto-orient your images?The short answer: almost always.When an image is captured, it contains metadata that dictates the orientation
YOLOv3 is known to be an incredibly performant, state-of-the-art model architecture: fast, accurate, and reliable. So how does the "new kid on the block," EfficientDet, compare? Without spoilers, we were
Roboflow improves datasets without any user effort. This includes dropping zero-pixel bounding boxes and cropping out-of-frame bounding boxes to be in-line with the edge of an image. Roboflow also notifies
We've seen tremendous interest in Roboflow from the research community. Faculty and students from institutions ranging from California to Malta to Taiwan have been using Roboflow to accelerate their computer
The appeals of synthetic data are alluring: you can rapidly generate a vast amount of diverse, perfectly labeled images for very little cost and without ever leaving the comfort of your office. The good news is: it's easy to try! And we're about to show you how.
We're introducing a new experiment this week: Roboflow is launching a Roboflow YouTube channel.We've been encouraged by the popularity of our computer vision tutorials. When Googling for some architectures,
TensorFlow expedites the machine learning process markedly. From abstracting complex linear algebra to including pre-trained models and weights, getting the most out of TensorFlow is a full-time job. However, when
As global coronavirus case numbers continue to climb, troubling stories of hospital shortages, deaths, and disrupted communities fill the news. Frankly, it can leave one feeling disempowered – especially when the
The success of your machine learning model starts well before you ever begin training. Ensuring you have representative images, high quality labels, appropriate preprocessing steps, and augmentations to guard against
By using Roboflow, data scientist Alaa Senjab reduced his time to train a custom object detection model detecting guns in security camera footage while increasing machine learning model accuracy. Alaa's