Skyrocket Your Annotation Efficiency with
T-Rex Label
T-Rex Label is an out-of-the-box AI annotation tool, dedicated to rapidly building complex scene datasets.
AI Annotate
Cross Image
AI Pre-annotation
Why T-Rex Label ?
T-Rex Label is built for efficient labeling—no fine-tuning, one-step prompting, and ready to use in your browser. Accelerate your data pipeline instantly.
Built for Speed: No Fine-tuning Needed
With its built-in open-set detection model, T-Rex Label provides one-click detection without any additional training or fine-tuning, significantly reducing the time overhead of lengthy pre-trained model pipelines.
Built for Automation — Prompt Once, Annotate Batch
By simply providing a visual prompt, T-Rex Label automatically identifies similar targets in complex scenes and propagates the prompt across images—enabling batch annotation in a single step.
Build for Convenience: Zero-Setup
T-Rex Label is a browser-based annotation tool that requires no installation or setup. It's ready to use out of the box, helping teams get started instantly while minimizing onboarding and maintenance costs.
Adaptable to All Industries and Use Cases
Leveraging its exceptional zero-shot detection capability, T-Rex empowers complex scene annotation across industries without fine-tuning, supporting diverse applications ranging from agriculture to logistics and beyond.
Seamless Integration
With comprehensive support for popular dataset formats, T-Rex Label integrates effortlessly into your visual AI pipeline.
Kaggle Datasets
Roboflow Universe
ModelScope
Hugging Face
Label Studio
FiftyOne
PyToch
TensorFlow
Keras
Roboflow TrainPreferred by Users Wordewide
T-Rex Label has already helped tens of thousands of computer vision engineers accelerate their labeling workflows and build high-quality datasets.
T-Rex2 is a powerhouse in the world of multi-modal AI, designed to excel in a variety of real-world applications. Whether you're in agriculture, industry, livestock monitoring, biology, medicine, OCR, retail, electronics, transportation, or logistics, T-Rex2 has got you covered!
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Mayur Asodara
CV Engineer
I have to say I was very impressed by T-Rex2 model's performance. For context, I only annotated 3 objects(visual prompts) in each of the attached images and the model was able to detect the rest. Worked much better than text prompts for me.
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Eric Kimwatan
Data Scientist
T-Rex Label is so easy to use with zero-shot object detection ability, especially in detecting rare objects in large quantities. For my recent CV projects, I quickly finished annotation tasks with no hassle. Highly recommended!
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William Liu
Principal System Architect
T-Rex2 breaks free from the limitations of traditional models. It takes visual prompts as input. You can give input by drawing a bounding box around an object and it will detect the rest of the similar objects in that image. It also recognizes objects outside of its initial training set without retraining.