KopiKat VS Labelbox
Compare KopiKat VS Labelbox and see what are their differences
B2B SaaS: Make your app enterprise-ready!
Authentication - SAML/OIDC SSO, Directory Sync (SCIM 2.0), Audit Logs, Data Privacy Vault, and more!
featured
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
Labelbox
Playment
V7
Supervisely
CloudFactory
Hive
Universal Data Tool
CrowdFlower
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.
A complete solution for your training data problem with fast labeling tools, human workforce, data management, a powerful API and automation features.
KopiKat LabelboxNo features have been listed yet.
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.
Service goes down often. Very slow team. Slow support.
Based on our record, Labelbox seems to be more popular. It has been mentiond 8 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.
Labelbox | Remote | Frontend / WebGL, Backend, Engineering Managers | https://labelbox.com Labelbox is building the training data platform to power breakthroughs in machine learning. We provide an end to end solutions for the full AI lifecycle from creating catalogs of unstructured data all the way to building the tools for humans to label the data to teach machines. Why choose us? - Source: Hacker News / over 1 year ago
Hey, I have currently developed a U-Net model for segmentation and I am trying to use the model assisted labeling feature on LabelBox to annotate some masks, so I can save time on relabeling. I am just wondering if anyone is familiar with this feature or can give me a step by step guideline on how to go about doing this. I went through the examples on their GitHub but I’m honestly still very confused. Any help... Source: almost 2 years ago
By now, I hope you see where I'm going with this. What is MDR doing? They're creating the labelled data used to train severance chips. They get a raw download of human brains in encoded format, and go about manually labelling the different pieces based on their most basic elements. Then, based on this manually labelled data, an algorithm can be trained to create a severance chip. MDR is basically Labelbox for... Source: almost 2 years ago
LabelBox - they provide free versions for research. Source: about 2 years ago
Doing some progress, labelbox.com allows me to do the Video annotation, and access all data through python SDK/API... Working on converting myself to CSV GCP format :-). Source: about 2 years ago
Label Studio - Open Source Data Labeling Platform for AI Model Tuning
Playment - Playment is a fully-managed solution offering training data for AI, transcription, data collection and enrichment services at scale.
Gretel AI Beta² - Generate unlimited synthetic data in minutes
V7 - Pixel perfect image labeling for industrial, medical, and large scale dataset creation. Create ground truth 10 times faster.
Generated Photos Datasets - Reduce bias in AI systems with synthetic face datasets
Supervisely - Supervisely helps people with and without machine learning expertise to create state-of-the-art...