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README.md

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-license: mit
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+# Multiple Car & Person Detection — YOLOv8x (Fine-Tuned)
+
+This repository provides a fine-tuned YOLOv8x model for real-time detection of multiple cars and persons in images and videos.  
+It is designed for applications such as traffic monitoring, smart-city analytics, pedestrian awareness, and video surveillance.
+
+## Key Features
+
+- Detects multiple objects per frame:
+  - car
+  - person
+- Real-time performance depending on hardware
+- High detection accuracy using YOLOv8x
+- Works on both images and videos
+- Built with Ultralytics YOLOv8
+
+## Model Details
+
+| Property | Value |
+|----------|-------|
+| Base Architecture | YOLOv8x |
+| Task | Object Detection |
+| Framework | Ultralytics |
+| Detected Classes | person, car |
+| Input | Images / Video |
+| Output | Bounding boxes + confidence scores |
+
+This model was fine-tuned on datasets containing vehicles and pedestrians in urban environments, optimized for scenarios where multiple vehicles and people appear in the same scene.
+
+## Installation
+
+Install the required dependencies:
+
+```bash
+pip install ultralytics opencv-python torch torchvision
+```
+
+
+## Model Files
+
+Multiple_car_detection.pt.pt - Best model from training
+
+
+## Example 
+
+![image](https://cdn-uploads.huggingface.co/production/uploads/67bc31088cf27f32cbcf927f/-dofHf6uErv0FzIKmBhrq.png)
+
+
+## Citation
+
+If you use this model, please cite:
+
+```bibtex
+@misc{multiple-car-detection-2025,
+  author       = {Malek Messaoudi and Yassine Mhirsi},
+  title        = {Multiple Car and Persons Detection},
+  year         = {2025},
+  publisher    = {Hugging Face},
+}
+
+```
+
+
+## license
+
+license: mit