Learn how to monitor assembly line throughput with computer vision ..read more

Learn how to identify solar panel locations with computer vision ..read more

Learn how to build a Consumer Packaged Goods inventory management system with computer vision ..read more

MobileNetV4 is a state-of-the-art convolutional neural network architecture designed for efficient mobile and edge device performance, offering a balance between high accuracy and low computational cost. MobileNetV4 was developed by Apple. With that said, Apple have not yet released pre-trained weights using the architecture. Hugging Face, however, have trained their own weights using the MobileNetV4 architecture. The Hugging Face weights achieve strong accuracy on classification tasks, so we will use them in this guide to demonstrate MobileNetV4 in use. In this article, we will guide you thr ..read more

OpenAI’s vision models such as GPT-4o perform well at a wide range of tasks, from visual question answering to image classification. One of the most exciting applications of these capabilities is optical character recognition (OCR), which allows the model to interpret and convert images of handwritten or printed text into digital text.  This tutorial will guide you through setting up GPT-4’s vision model to translate paper notes and save the contents in a Google Document. We will use Roboflow Workflows, a low-code computer vision application builder, to create our application. Let’s get ..read more

PaliGemma is a multimodal vision model architecture developed by Google Research. The architecture was released in May 2024 with the ability to fine-tune PaliGemma models, and a series of existing weights that were trained on various benchmark datasets. You can use PaliGemma to detect objects, segment objects, and for VQA. Here is an example of the results from a fine-tuned model that can detect shipping containers and container information: Note: This model was only trained for 512 steps. Training the model for more steps will increase accuracy. We are excited to announce that you can now de ..read more

This past weekend, around 30 million people tuned in to watch the 2024 Euro Cup and COPA America Cup finals. The two tournaments hosted the finest players in the world for a month of competitive and fast-paced football (or soccer), drawing in fans from all over the world watching from their phones, laptops, and TV screens. Amongst these fans are likely those with visual impairments who benefit greatly from high contrast colors used where possible. For example, jerseys that have high colour contrasts are more readable and thus accessible to a wider audience.   While we know which cou ..read more

The article below was contributed by Timothy Malche, an assistant professor in the Department of Computer Applications at Manipal University Jaipur. Early detection and diagnosis of diseases affecting plant leaves can significantly reduce crop losses and improve productivity in agricultural environments. In this project, we use computer vision to predict tomato leaf diseases. In this blog post I will guide you through how to build a robust object detection model using Roboflow, which is trained to identify and classify various diseases affecting tomato leaves.  The user interface for our ..read more

Ensuring the safety of workers is crucial in industrial settings. One effective method to enhance safety is by creating a computer vision system to identify “red zones,” where heavy machinery is passed around, and where workers need to be extremely cautious.  This tutorial will guide you through the process of building a red zone detection system using computer vision. By the end of the guide, you will have a working model that can identify and highlight hazardous areas in real-time. 0:00 /0:13 1× Step 1. Build a Model First, sign up for Roboflow and create an account. Next, go to worksp ..read more

The article below was contributed by Timothy Malche, an assistant professor in the Department of Computer Applications at Manipal University Jaipur. In this blog post, we will guide you through creating a system for library management to detect books and retrieve relevant information such as the book title, author, and publisher details. This computer vision-based book inventory system offers numerous features, including the ability to automatically extract the book details and prepare book inventory data for a library management system without the need of manually typing each of these detail ..read more