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title: Open-World Object Intelligence Platform
emoji: 👁️
colorFrom: indigo
colorTo: blue
sdk: gradio
sdk_version: 4.44.1
app_file: app.py
pinned: false
license: mit
hardware: gpu
---
# Open-World Object Intelligence Platform
[](https://huggingface.co/spaces)
[](https://www.python.org/downloads/)
[](https://opensource.org/licenses/MIT)
> **Complete System Architecture, Product Specification, ML Pipelines, Live Testing, Downloads, Guides, API, Database, and Hugging Face Deployment Plan**
---
## 🌟 Key Features
1. **Known Object Detection (RT-DETR)**: Fast, predictable object detection for standard COCO classes using RT-DETR.
2. **Open-Vocabulary Discovery (YOLO-World)**: Zero-shot visual concept detection driven by dynamic text prompts without detector retraining.
3. **Specific Object Recognition (Visual Embeddings)**: Deep PyTorch vision feature extractor + cosine similarity search to teach and recognize specific physical objects (*e.g. My Cup* vs generic *cups*).
4. **🔒 Lock Mode Target Filtering**: Restricts output bounding boxes so that **ONLY** objects matching your lock target (*e.g., 'My Cup', 'red backpack'*) are displayed on the live feed. Non-matching objects are completely suppressed.
5. **Result Fusion Engine**: Smart Non-Maximum Suppression (NMS) and IoU deduplication that prioritizes specific taught object identities over generic category labels.
6. **Hugging Face Spaces & Gradio Web App**: Sleek glassmorphic web interface built with Gradio and FastAPI ready for 1-click Hugging Face Spaces deployment.
7. **Python SDK & OpenCV Examples**: Clean client SDK (`object_intelligence`) with ready-to-run OpenCV webcam scripts.
8. **Portable Custom Object Database**: Portable SQLite database with ZIP import/export capabilities for taught object libraries.
---
## 🏗️ System Architecture
```
OBJECT INTELLIGENCE PLATFORM
|
+-----------------------+-----------------------+
| | |
v v v
KNOWN OBJECTS OPEN VOCABULARY SPECIFIC OBJECTS
RT-DETR YOLO-World Embeddings
| | |
+-----------------------+-----------------------+
|
v
RESULT FUSION
|
+--------+--------+
| |
v v
NORMAL MODE LOCK MODE
| |
| Target matching
| |
| v
| Only target boxes
| |
+--------+--------+
|
v
OBJECT KNOWLEDGE DB
```
---
## 🚀 Quick Start
### 1. Installation
```bash
git clone https://github.com/user/Object-Intelligence.git
cd Object-Intelligence
pip install -r requirements.txt
```
### 2. Run Application Locally
```bash
python app.py
```
Open your browser at `http://localhost:7860`.
---
## 🐍 Python SDK Usage
```python
from object_intelligence import ObjectDetector
import cv2
# Initialize detector client
detector = ObjectDetector()
# Select mode ('combined', 'known', 'open_vocabulary', 'specific')
detector.set_mode("combined")
# Enable Lock Mode for a specific target
detector.lock("My Cup")
# Process frame
frame = cv2.imread("sample.jpg")
annotated_frame, detections = detector.detect_and_draw(frame)
# Save result
cv2.imwrite("output.jpg", annotated_frame)
```
---
## 🧠 Teaching Custom Objects
Teach the system new physical objects using reference photos:
```python
from object_intelligence import ObjectDetector
detector = ObjectDetector()
detector.add_object(
name="My Cup",
images=["cup_front.jpg", "cup_back.jpg", "cup_side.jpg"],
category="Drinkware",
description="Personal blue mug with handle"
)
```
---
## 🌐 Deploying to Hugging Face Spaces
1. Create a new **Gradio** Space on Hugging Face.
2. Upload this repository (`app.py`, `requirements.txt`, `backend/`, `object_intelligence/`, `docs/`, `examples/`).
3. Hugging Face Spaces will automatically install dependencies and run `app.py`!
---
## 📄 License
Distributed under the MIT License. See `LICENSE` for details.
|