Channel Avatar

LearnOpenCV @UCeoXXZ2u_cUQ6CJ-oXpss9w@youtube.com

57K subscribers - no pronouns :c

Welcome to LearnOpenCV, a comprehensive YouTube channel dedi


Welcoem to posts!!

in the future - u will be able to do some more stuff here,,,!! like pat catgirl- i mean um yeah... for now u can only see others's posts :c

LearnOpenCV
Posted 1 day ago

With advancements in Generative AI, interactions with voice assistants are now real-time and feel like talking to a real person.

In our latest article, we explore the Speech-to-Speech pipeline from HuggingFace, covering:

- How speech-to-text transforms spoken language into accurate transcriptions with Whisper.
- The role of LLMs in understanding context and generating meaningful, human like responses
- How text-to-speech models like parler-tts converts these responses back into lifelike audio.

learnopencv.com/speech-to-speech/

#llms #speech2speech #GenAI #huggingface #whisper

18 - 0

LearnOpenCV
Posted 1 week ago

3D U-Net, an efficient paradigm in medical segmentation, excels at analyzing volumetric data, allowing it to capture a holistic view of brain scans.
The Brain Tumor Segmentation (BraTS), is an annual challenge that aims to use advanced state-of-the-art deep learning models and techniques to segment lesions in brain regions.

In this guide, we will explore how to train a 3D U-Net model using the BraTS2023-GLI dataset.

learnopencv.com/3d-u-net-brats/

30 - 0

LearnOpenCV
Posted 2 weeks ago

Unveiling DETR: The Future of Object Detection
Curious about cutting-edge advancements in Computer Vision? Explore DETR (Detection Transformer) and learn how it revolutionizes object detection with transformer architecture! In this comprehensive overview, you'll dive into its working principles, real-world applications, and inference performance. Perfect for anyone looking to stay ahead in the AI and CV space!
Check out the full article here: learnopencv.com/detr-overview-and-inference/
#ComputerVision #AI #DETR #ObjectDetection #MachineLearning #Transformers #DeepLearning

34 - 0

LearnOpenCV
Posted 4 weeks ago

Are you curious about self-supervised learning but not sure where to start? This article makes it easy to understand the core concepts of Self-Supervised Learning and introduces you to Facebook AI's DINO model.

It also shows how to apply DINO to a real-world challenge: road segmentation of Indian roads using the IDD dataset. Follow the step-by-step guide to preprocess data, build and fine-tune DINO on downstream segmentation task.
learnopencv.com/fine-tune-dino-self-supervised-lea…

21 - 0

LearnOpenCV
Posted 1 month ago

Sapiens, a powerful new model family from Meta Reality Labs, has been introduced for human-centric vision tasks such as 2D pose estimation, body-part segmentation, depth estimation, and surface normal prediction.

Human Vision Models like Sapiens are game changers in Metaverse, facilitating the creation of life-like human avatars.


We will explore the pretraining, task specific fine-tuning details from the Sapiens paper and perform inference with the Sapiens-1B model across multiple tasks.


Individuals working at the intersection of Computer Vision and Mixed Reality will find this read very interesting


learnopencv.com/sapiens-human-vision-models/




#sapiens #humanvision #humanvisionmodel #computervision

37 - 1

LearnOpenCV
Posted 1 month ago

ColPali, is a novel approach for Efficient Document Retrieval using Vision Language Models developed by the team at Illuin Tech. It outperforms standard retrievers by a huge margin with less latency and complexity.

We will explore and test this through a much demanding industrial use case by building a Multimodal RAG application with Colpali and Gemini on finance reports.

learnopencv.com/multimodal-rag-with-colpali/


Individuals and companies seeking to enhance their document analysis capabilities with RAG will find this read more useful.


#ColPali #DocumentRetrieval #VisionLanguageModels #IlluinTech #MultimodalRAG #AIinFinance #Gemini #DocumentAnalysis #RAGModel #FinanceTech

24 - 1

LearnOpenCV
Posted 1 month ago

In this chapter of our robotics blog series, we’ll embark on the exciting challenge of building an Autonomous Path-Following Vehicle using ROS2 and CARLA in Python!


With a special focus on the control aspect—one of the four key pillars of robotics: sensing, perception, planning, and control—we’ll walk you through the process of achieving a smooth waypoint following using a PID controller.

learnopencv.com/pid-controller-ros-2-carla/


Get ready to explore the innovative techniques driving the control systems of autonomous vehicles!


#robotics #autonomousvehicles #pidcontroller #ros2

25 - 0

LearnOpenCV
Posted 1 month ago

In this article, we address the complex problem of recognizing handwritten text using OCR. We will train the TrOCR model for handwritten note recognition on the Goodnotes dataset.
learnopencv.com/handwritten-text-recognition-using…
The dataset, which has been curated from several users, is versatile and complex. Pretrained OCR models fail to recognize the text in these documents, but fine-tuning the model with proper hyperparameter tuning makes it extremely performant on the dataset.

#OCR #HandwrittenTextRecognition #TrOCR #AI #MachineLearning #DeepLearning #Dataset #DataScience #AIResearch

34 - 0

LearnOpenCV
Posted 2 months ago

Learn the essentials to build a CLIP-like model from scratch for a fashion apparel search app with image retrieval.

CLIP was trained on a massive dataset of image-text pairs, which allows it to excel as a zero-shot classification model. It can take a given text prompt or labels and efficiently retrieve matching images from a database, identifying those that share similar features with the query.

learnopencv.com/clip-model/

The article primarily dicusses:
How to implement the Vision and Text Encoder of CLIP from Scratch using PyTorch
Techniques involved in training a CLIP on a Fashion Images Dataset
Finally, how to build an apparel search app with Gradio

#CLIPModel, #ImageRetrieval, #MachineLearning, #PyTorch, #DeepLearning, #ImageSearch, #AI, #ComputerVision, #FashionTech, #ModelTraining

29 - 0

LearnOpenCV
Posted 2 months ago

LiDAR Odometry and Mapping are among the most reliable methods for SLAM, yet few resources cover the fundamentals. In this article, we explore two of the most influential papers: LOAM and LeGO-LOAM.

learnopencv.com/lidar-slam-with-ros2/



We break down the mathematics behind LiDAR positioning and mapping and dive into the C++ code to understand their implementation. We also provide a step-by-step guide to running LeGO-LOAM in ROS 2.

#lidar #slam #loam #ros2 #robotics

38 - 0