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<div align=center> <img src="assets/TRex.png" width=900 > </div> <div align=center> <p >T-Rex is an interactive object counting model that can first detect then count any objects through visual prompting</p> </div> <div align=center>

</div>  <div align=center> <img src="assets/cartoon.gif" width=900 > </div>

What is T-Rex 🦖

T-Rex is an object counting model that can first detect then count any objects through visual prompting, which is highlighted by the following features:
- Open-Set: T-Rex possess the capacity to count any object, without constraints on predefined categories.
- Visual Promptable: Users can provide visual examples to specify the objects for counting.
- Intuitive Visual Feedback: T-Rex is a detection-based model that allows for visual feedback (i.e. detected boxes), enabling users to assess the accuracy of the result.
- Interactive: Users can actively participate in the counting process to rectify any errors.

<div align=center> <img src="assets/about-img.png" width=400 > </div>

How Does T-Rex Work ⚙️

T-Rex provides three major workflows for interactive object counting / detection.
- Positive-only Prompt Mode: T-Rex can detect then count similar objects in an image with just a single click or box drawing. Additional visual prompts can be added for densely packed or small objects.
- Positive with Negative Prompt Mode: To address false detections caused by similar objects, users can correct the outcome by applying negative prompts to the erroneously detected objects.
- Cross Image Prompt Mode: This feature supports counting across different reference and target images, ideal for automatic annotation. Users prompt on one image, and T-Rex annotates the others automatically.

What Can T-Rex Do 📝

T-Rex can be applyed to various domains for counting including but not limited to Agriculture, Industry, Livestock, Biology, Medical, Retail, Electronic, Transportation, Logistics, Human, etc.
T-Rex can also serve as an open-set object detector, which can be applied for automatic annotaion. It process exponential zero-shot detection capability, and offers strong performance in dense and overlapping scenes.
We list some of the potential applications of T-Rex below:

<div align=center> <img src="assets/1.png" width=240 > <img src="assets/2.png" width=240 > <img src="assets/3.png" width=240 > </div> <div align=center> <img src="assets/5.png" width=240 > <img src="assets/6.png" width=240 > <img src="assets/7.png" width=240 > </div>

Try Demo 🚀

Waiting for DDS

BibTeX 📚

Wating for technical report

Acknowledgement 🙏

We would like to thank the DeepDataSpace team for building the demo.

TODO List 📝

A more detailed version of paper
Release the code