CompreFace
Google Vision AI
Amazon Rekognition
OpenCV
Facebook Computer Vision Tags
Ximilar
Clarifai
VISUA
KopiKat
Label Studio
Gretel AI Beta²
Generated Photos Datasets
Computer Vision Annotation Tool (CVAT)
Universal Data Tool
This Person Does Not Exist
AWS SageMaker Ground Truth
KopiKat generates a new, visually realistic duplicate of the original image, maintaining all critical data annotations. It alters the environment of the original images, for instance, adjusting factors like weather, seasons, and lighting conditions to add variety to datasets. This is crucial for fields such as object detection, neural network training, and transfer learning.
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KopiKat's answer:
Our goal with Kopikat is to strengthen practical applications, especially in scenarios where collecting an extensive dataset proves to be difficult. Kopikat is ideally designed for datasets containing up to 5,000 images, a common feature of numerous real-world AI initiatives. It equips engineers with the ability to enhance mean average precision (mAP), broaden and vary datasets—a critical edge in fields like object detection, neural network training, and transfer learning.
KopiKat's answer:
KopiKat's operation is remarkably simple and efficient for its users. All a user has to do is upload one image from their dataset. KopiKat then produces numerous images showcasing different scenarios, like alterations in illumination or weather, all the while preserving the annotations consistently. This attribute considerably expands the diversity of the dataset without requiring extra images, and creates a comprehensive, superior-quality model that introduces diversity beyond what traditional data augmentation techniques can offer. This method has demonstrated an improvement of over 5% in mean average precision (mAP), without any alterations to the AI model.
Based on our record, CompreFace seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Looking into this I found Compreface (https://exadel.com/solutions/compreface/) an open source face recognition software. There are alread some controb scripts, like contrib/photils.lua, who take some images, run them through a tool, then tag them with data coming from the tool. Converting this to use Compreface looks likea promising avenue. Source: almost 2 years ago
Does anyone know what the technical interview process for Senior Java position looks like for the company Exadel? Https://exadel.com/. Source: almost 2 years ago
Exadel - holy heck. They gave us talent for DAYS. Source: about 2 years ago
Serhii Pospielov, AI Practice Head at Exadel, reviewed several no-code app builders from a developer's point of view. He tried to create MVPs on 13 different platforms, but only managed to achieve that on five (this doesn’t mean that the other eight aren’t good platforms – just that they didn’t meet his particular business need). Serhii’s favorite no-code app builders were:. - Source: dev.to / over 2 years ago
Free and Open-Source Face Recognition System that can be integrated into any system without prior AI knowledge: https://exadel.com/solutions/compreface/. Source: about 3 years ago
Google Vision AI - Cloud Vision API provides a comprehensive set of capabilities including object detection, ocr, explicit content, face, logo, and landmark detection.
Label Studio - Open Source Data Labeling Platform for AI Model Tuning
Amazon Rekognition - Add Amazon's advanced image analysis to your applications.
Gretel AI Beta² - Generate unlimited synthetic data in minutes
OpenCV - OpenCV is the world's biggest computer vision library
Generated Photos Datasets - Reduce bias in AI systems with synthetic face datasets