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langutang/
protege-lg

Name: protege-lg
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🧠⚡ Protoge-LG: Scalable Object Detection & Tracking (GPU/TPU-Ready)

Protoge-LG is a large-scale object detection and tracking algorithm using computer vision and TensorFlow. Optimized for GPU and TPU inference, this model can detect and track over 1000 object classes in real-time, with flexibility for targeted tracking of selected labels.

🚀 Highlights

🧠 Detects & tracks 1000+ object categories
🌀 Supports both full-label and targeted detection modes
⚡ Accelerated with GPU or TPU support
🧰 Uses TensorFlow’s object detection API and integrates with OpenCV for real-time video processing
📦 Exportable to TensorFlow Lite, TF.js, and compatible with Google Cloud TPU infrastructure

🔬 Applications

Advanced robotics and autonomous systems
Industrial visual inspection and surveillance
Healthcare AI in smart facilities
Cloud-scale computer vision pipelines

⚙️ How It Works

python

import tensorflow as tf

# Load the model
model = tf.saved_model.load("path/to/protoge-lg")

# Enable GPU/TPU if available
# Configure strategy if deploying on TPU

# Run full detection or provide custom labels
target_labels = ["robot arm", "conveyor belt", "monitor"]
detections = model(input_tensor, labels=target_labels)

# 🧪 Supported Modes
## 🔍 Full Mode
Detect and track all 1000+ categories in a single pass. Best used for exploratory environments or full-scene awareness.

## 🎯 Selective Mode
Pass in a list of labels to optimize speed and accuracy on known targets. Ideal for constrained detection environments like industrial automation or healthcare.

#📊 Performance Overview
Classes Supported =	 1000+
Acceleration	  =  GPU / TPU
Model Size	      =  ~60MB
Inference Speed	  <  40ms (TPU)
Video Tracking	  <= 60 FPS

## 📖 Citation

If you use **Celestial-Mini** in your work, please consider citing:

@misc{celestialmini2025, title={Celestial-Mini: A Lightweight Real-Time Object Detector}, author={Lang, John}, year={2025}, howpublished={\url{https://huggingface.co/langutang/celestial-mini}} }


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## 📬 Contact & License

- 📫 For questions or collaboration, open an issue or contact the maintainer.
- ⚖️ License: MIT (see LICENSE file for details)

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## 🌠 Hugging Face Model Hub

To load from Hugging Face:

```python
from transformers import AutoFeatureExtractor, TFModelForObjectDetection

model = TFModelForObjectDetection.from_pretrained("langutang/protege-lg")
extractor = AutoFeatureExtractor.from_pretrained("langutang/protege-lg")

Transform your edge AI projects with the power of Protege-Lg 🌠