Versatility
The tool should be capable of handling different types of data, including 2D and 3D images, videos and point clouds generated by LiDAR sensors.
Industry
Agriculture
Boost agriculture AI with Keylabs' expertly accurate annotation services
Data annotation tools have become an essential component in various industries, including agriculture. With the rise of precision agriculture and the use of AI and machine learning, accurate data has become critical for farmers to make informed decisions. In agriculture, this process is crucial for identifying crop types, detecting diseases and predicting yields.
At Keylabs, we understand the importance of data annotation in agriculture. Our platform enables the development of successful agriculture applications and is the perfect choice for farmers and developers alike.
Applications
Annotation tools in agriculture applications
01 / Aerial crop analytics
Aerial crop analytics has become an essential tool in precision agriculture. Powered by AI technology and drone geospatial intelligence platforms, these tools enable farmers to monitor their crops more efficiently and detect pest infestations and plant diseases early on. By using smart spraying and seeding techniques based on data collected through aerial surveys, farmers can increase their agricultural efficiency while reducing costs.
02 / Automated harvesting & fruit picking
Accurate detection and localization of fruit are crucial for successful automation in agriculture. Keylabs provides annotations for all types of images and videos to create the best training data for computer vision projects. With high-quality training data, automated harvesting systems can accurately detect ripe fruit without harming unripe or overripe ones.
03 / Grading and sorting
Automating produce grading and sorting with AI computer vision can save time, reduce labor costs and increase accuracy. Keylabs data annotation platform is a perfect tool for agriculture apps looking to implement this technology. In addition to traditional image datasets, Keylabs also offers perfect video annotation that supports object tracking for grading and sorting purposes.
04 / Pest and plant disease detection
Precision agriculture aims to use technology to optimize crop production and increase yield. Plant disease and pest detection using machine vision utilizes deep learning approaches to train models on large datasets of images of diseased or pest-infected plants. These models can then be used for early detection and prevention, leading to improved crop yield.
05 / Yield estimation
Accurate yield estimation is critical in agriculture as it enables farmers to make more informed decisions on resource management. Remote sensing systems have emerged as a powerful tool to improve yield production. Sophisticated models can provide accurate estimates of crop yields based on inputs such as soil moisture, temperature, rainfall and nutrient levels.
Platform requirements
Key features
There are several key features that a robust data annotation tool for agriculture should possess:
Precision
High-quality annotations are crucial for the accuracy of AI models. The tool should enable precise labeling of objects and features, minimizing the chances of misinterpretation.
Scalability
A data annotation tool should be scalable to handle large datasets efficiently, streamlining the annotation process and reducing the time required for model training.
Automation
AI-powered data annotation tools can leverage machine learning algorithms to automate parts of the annotation process, speeding up the workflow and increasing overall efficiency.
Collaboration
A good data annotation tool should facilitate collaboration among team members, enabling multiple annotators to work together on the same dataset for consistency and speed.
Quality control
To ensure the highest level of accuracy, the tool should have built-in quality control features that allow for easy review and verification of annotated data.
Customization
A flexible data annotation tool should allow for customization to meet the unique needs of each project and adapt to new challenges in the industry.
Integration
The tool should integrate seamlessly with various machine learning frameworks and platforms, making it easier for developers to use annotated data for training.
Data security
A data annotation tool must prioritize data security and privacy, ensuring that the information is protected at all stages of the annotation process.
Applications
Use cases
Aerial crop analytics
Fully compatible with all data formats, our platform ensures meticulous annotation, critical for accurate crop health assessments and yield predictions.
Box & line
Automated harvesting & fruit picking
The data annotation platform powers advanced harvesting and fruit picking applications. With a diverse suite of labeling tools, we provide high-quality datasets specially tailored for the precise identification of ripe produce.
Multi-type
Grading & sorting. Disease detection
Keylabs platform, adept in handling diverse data formats, provides precise annotation, accurate pest and plant disease detection, leading to more effective crop management.
Box & polygon
Yield estimation
Keylabs platform, compatible with all data formats, ensures meticulous annotation — enabling reliable yield predictions that empower smarter, more efficient farming.
Box & line
Privacy first
Data security
Using the Keylabs annotation tools comes with a commitment to data safety. Keylabs employs a range of security measures to protect valuable and sensitive data. This includes comprehensive infrastructure security if you choose to access Keylabs through the cloud. Alternatively, Keylabs can be installed on premises, guaranteeing you total control over access. We will continue to emphasize data protection as a priority by utilizing a diverse array of security measures and industry best practices.
Learn more
Platform
Top features
Keylabs is created as a platform that incorporates state-of-the-art, performance oriented tools and processes.
ML assisted data annotation
Keylabs is a streamlined data labeling platform with AI-enhanced annotation. Tailored for easy integration with any client model and time & cost efficiency. Keylabs' advanced algorithms provide quick, accurate data prep for superior model training.
3D tool
Keylabs is a super-fast tool, soaring through Lidar files at ultra speeds. It seamlessly handles all file formats, ensuring a consistent, efficient workflow regardless of file complexity.
High performance video annotation
With the Keylabs platform's technical and software capabilities, video annotation is highly accurate (precision of up to 99.9% depending on project needs) and fast.
Magic wand
Speeds up the annotation process by automatically detecting closed shapes of the same color or color gradient in a highly precise manner.
Object interpolation
Object interpolation accelerates annotation across a sequence of frames. Annotators label shape in the first and last keyframes, and the algorithm automatically generates labels for intermediate frames.
A-Z order
Objects can be placed on different leveled layers, which allows operators to correctly detect and work with those objects and their boundaries.
Multilayer annotation
Multilayer annotation allows multiple diverse annotations on a single piece of data such as an image or video frame, enriching the dataset with multiple facets of detail.
Object linking
Connects different instances of the same object across multiple frames or images, ensuring continuity and consistency of the annotation.
Hierarchical attributes
Using attribute hierarchies, it is possible to define structures of metadata for each item in the dataset using dependent attributes.
Workflow and task distribution
Workflow includes custom stages of annotation, verification, and final delivery. Task distribution ensures the right work goes to the right team member.
Data management
Data management is about strategically handling and organizing data throughout its lifecycle, from collection to annotation to archival.
Attributes interpolation
Attributes metadata can be interpolated between frames, automatically estimating object properties across keyframes.
Toolkit
Annotation types
Keylabs gives developers access to a full suite of annotation techniques:
Bounding box
A rectangular box defined by coordinates that encapsulates an object of interest within an image.
Oriented bounding box
A rotated rectangle that tightly encloses an object, accommodating its orientation and shape more precisely than a standard bounding box.
Polygon
A closed plane figure made up of several line segments joined together, used to define irregular shapes in an image.
Points
The point annotation tool places dots on images or videos, ideal for highlighting details like facial features, expressions and body postures.
Lines & multilines
Annotate linear structures like lane markings, cables and roads using straight or multi-segment lines.
Skeletons
Define custom skeleton topologies with any number of joints and connections for pose estimation and motion tracking.
Cuboid
3D bounding box capturing depth, height and width — essential for autonomous driving and AR/VR applications.
3D point cloud
Annotate LiDAR and 3D scene data with spatially-referenced points for high-fidelity spatial understanding.
Semantic segmentation
Pixel-level classification where every pixel in the image is assigned to a class label.
Instance segmentation
Pixel-level classification that distinguishes between multiple instances of the same object class.
Bitmap
Pixel-wise raster mask annotation allowing for highly precise object boundaries and gaps.
Mesh
Interconnected vertices forming polygonal structures — ideal for 3D reconstructions and digital twins.
Custom
Combine any of the above annotation techniques to accomplish specific annotation goals for your project.
Compliance
Enterprise-grade. Built for trust.
Keylabs meets the highest standards of data security and privacy.
