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langutang/
celestial-mini

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🌌 Celestial-Mini: Lightweight Object Detection Model (TF)

Celestial-Mini is a compact, high-performance object detection model designed to recognize up to 80 distinct object classes. Built with TensorFlow, it balances speed and accuracy for deployment in edge devices and real-time applications.

🚀 Key Features

🔍 Detects up to 80 different object categories
⚡ Optimized for real-time inference
🧠 Built on a lightweight backbone
📦 TensorFlow SavedModel format for easy deployment
🧰 Compatible with TensorFlow Lite and TensorFlow.js

🧪 Intended Use

Celestial-Mini is designed for:

Robotics and drones
Smart home devices
Augmented Reality (AR) systems
Mobile applications
Educational and prototyping environments

🏷 Object Classes

Includes detection support for the standard 80-class COCO-style object categories such as:

person, bicycle, car, motorcycle, airplane, bus, train, truck, boat, traffic light, ...

📦 How to Use

python

import tensorflow as tf

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

# Run inference
detections = model(input_tensor)

📊 Performance

Metric	Value
Classes	80
Model Size	~15MB
Inference Time	< 50ms/image
Framework	TensorFlow

📌 Performance may vary depending on hardware and TensorFlow backend optimizations.

🧠 Training & Dataset

Celestial-Mini was trained on a custom variant of the COCO dataset, emphasizing generalization and real-time inference. Model architecture includes quantization-friendly layers and depthwise separable convolutions.

📖 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}}
}

📬 Contact & License

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

🌠 Hugging Face Model Hub

To load from Hugging Face:

python

from transformers import AutoFeatureExtractor, TFModelForObjectDetection

model = TFModelForObjectDetection.from_pretrained("langutang/celestial-mini")
extractor = AutoFeatureExtractor.from_pretrained("langutang/celestial-mini")

Transform your edge AI projects with the power of Celestial-Mini 🌠