Annotify
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Annotify v1.0.0By Bakiotic

Label Your Dataset
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Instantly label images with AI — no manual clicks, no coding.

SAVES 90% TIME

Upload your video/images or folders

Describe → Click → Done. Seriously, that's it.

Focus on training

Model Training Ready

Export your datasets while others are still labeling

✨ Create your dataset in seconds ✨

Zero-Shot Auto Annotation

Describe what you need in plain English. Get perfect annotations before your coffee gets cold

Input Image
Raw input image
Prompt

"fighter knocked out"

Annotify labelling
✅ Done
Annotated Result
Annotated output

No manual labeling • Just pure AI magic

How It Works

A seamless, five-step journey from data to detection.

Step 1: Prepare

Upload your dataset (video,images,folders) and specify the keywords/classes for detection.

Step 2: Upload

Files are securely uploaded to the cloud for processing.

Step 3: Annotate

Take your coffee while Annotify automatically handle your dataset with Runpod blazing-fast GPUs speeds.

Step 4: Export

Download your annotated dataset in any major format.

Step 5: Done!

Get results in minutes, not days. Time wasted: zero.

Demo – Real Match Glove Detection

See how you can automatically detect boxing gloves in a real match using Annotify and Grounding DINO. No code. No model training. Just plug & play.

Upload Your Dataset

Simply drag and drop your folders, images, or videos here. Add your keywords and classes — we’ll handle the rest, making annotation effortless and fast.

Classes & Keywords

Add a class name and/or give a description of your classes.
E.g. If you want to specifically detect a character with a hat, just write "character with a hat".

Upload Files

Drop images or videos here

JPG, PNG, MP4, MOV, etc.

Powerful Features

Everything you need to accelerate your machine learning pipeline

Latest Zero-Shot Models

State-of-the-art zero-shot detection models for accurate annotation without training.

Supports Video & Images

Multiple formats supported: JPG, PNG, WEBP, MP4, MOV, AVI and more.Process folder that contains images and videos files at once.

GPU-Powered Annotation

Annotify leverages GPU acceleration for lightning-fast annotation processing and real-time results.

Powered by Runpod

Export All Formats

Export annotations in all major formats: COCO JSON, Pascal VOC, YOLO, csv, and custom formats.

Real-time Processing

Get instant results with our optimized pipeline. No waiting, just immediate annotation feedback.

Simple, Transparent Pricing

No subscriptions, no hidden fees. Pay only for what you use.

500

ESTIMATED COST

$13.90

500 credits required

Pricing Policy:

  • 0–500 images: 2.78¢ per image
  • 501–1000 images: 2.60¢ per image
  • 1001+ images: 2.18¢ per image

1 credit = 2 images

Special Use Cases?

For high-volume usage, educational institutions, research labs, or custom integrations — get in touch with us for tailored solutions.

Why Choose Annotify?

We do what others do — but faster, simpler, and without the headaches.

No Account Needed.

With Annotify we don't require an account to automatically annotate your dataset. Perfect for starting direcly the project without needing to set up.

Better Price

The current version of Annotify v1.0.0 use Ground DINO v1 as the model for automatically annotate your dataset. The competitors such as Roboflow and V7 also uses this model and still our prices are lower than them. We will change the model to Ground DINO V1.5 in the up coming versions. Ground DINO V1.5 is the most capable model currently in this field and the competitors do not provide it.

Supports Images & Video

Upload individual images, folders, or full videos — all processed seamlessly in one pipeline. Competitors like Roboflow let you upload only 10MB while we let you 160MB of upload capacity on the web interface.

No Data Selling

Compared to the competitors Annotify do not store your dataset nor sell it at any company or services. The images are uploaded to the GPU and after inference we delete them from the Cloud. The competitors do use your dataset for their services.