README.md

---
title: Apartment Before-After Object Comparison
emoji: 🏠
colorFrom: indigo
colorTo: purple
sdk: docker
pinned: false
license: mit
---

# 🏠 DINO (RT-DETR) + SAM 2/3 + ByteTrack Apartment Inspector

This Hugging Face Space hosts the **Apartment Before-After Object Comparison** application, built using Gradio, Ultralytics RT-DETR (DINO architecture), ByteTrack/BoT-SORT tracking, and the Segment Anything Model (SAM 2/SAM 3) for pixel-level mask segmentation.

## Features
- **Dual Video Input:** Upload and analyze "Before" and "After" videos of apartment spaces.
- **Deep Tracking & Segmentation:** Combined class-aware detection (RT-DETR/YOLO) with high-fidelity segmentation (SAM 2/SAM 3).
- **Persistent Tracking IDs:** Assigns persistent IDs to objects across frames using ByteTrack or BoT-SORT to keep counts precise and handle occlusions.
- **Detailed Inventory Reports:** Outputs differences between Before and After scenes, showing added/removed counts and detailed lists of specific tracking IDs per category (e.g. `Chair 🪑: 3 items (IDs: #1, #3, #4)`).
- **Interactive Tuning:** Control Confidence, IoU, tracking parameters, and frame rates dynamically.

## Run Locally
You can run this application locally by installing the dependencies:
```bash
pip install -r requirements.txt
python app.py
```
Or by building the Docker container:
```bash
docker build -t apartment-inspector .
docker run -p 7860:7860 apartment-inspector
```