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GitHub / AmareshMuddebihal / Pedestrian-detection-assistance-system
This repository contains a real-time pedestrian detection and tracking system implemented using deep learning techniques, specifically leveraging the YOLO (You Only Look Once) V8 architecture. The system is designed to detect and track pedestrians in low-light conditions, making it suitable for applications such as night-time driving scenarios.
Stars: 0
Forks: 0
Open Issues: 0
License: None
Language: Jupyter Notebook
Repo Size: 36.5 MB
Dependencies:
46
Created: 28 days ago
Updated: 24 days ago
Last pushed: 24 days ago
Last synced: 24 days ago
Topics: car, car-assistant, object-detection, pedestrian-detection, pedestrians
Files
Dependencies
- Pillow ==10.3.0
- accelerate ==0.29.3
- albumentations ==1.4.4
- authlib ==1.3.0
- bitsandbytes ==0.43.1
- codecarbon ==2.3.5
- cryptography ==42.0.5
- datasets *
- diffusers ==0.27.2
- einops ==0.7.0
- evaluate ==0.4.1
- fastapi ==0.110.2
- hf-transfer *
- httpx ==0.27.0
- huggingface_hub ==0.22.2
- invisible-watermark ==0.2.0
- ipadic ==1.0.0
- itsdangerous ==2.2.0
- jiwer ==3.0.3
- joblib ==1.4.0
- loguru ==0.7.2
- nltk ==3.8.1
- nvitop ==1.3.2
- optuna ==3.6.1
- packaging ==24.0
- pandas ==2.2.2
- peft ==0.10.0
- protobuf ==4.23.4
- py7zr ==0.21.0
- pydantic ==2.7.1
- pyngrok ==7.1.6
- python-multipart ==0.0.9
- requests ==2.31.0
- rouge_score ==0.1.2
- sacremoses ==0.1.1
- scikit-learn ==1.4.2
- sentencepiece ==0.2.0
- seqeval ==1.2.2
- tensorboard ==2.16.2
- tiktoken ==0.6.0
- tqdm ==4.66.2
- transformers ==4.40.1
- trl ==0.8.6
- uvicorn ==0.29.0
- werkzeug ==3.0.2
- xgboost ==2.0.3