traffic_perception_deep_learning_yolov8
Submission for Krackhack'25 in Deep Learning Domain PS "Intelligent Traffic Perception"
https://github.com/tomoeooseven/traffic_perception_deep_learning_yolov8
Science Score: 31.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (8.5%) to scientific vocabulary
Repository
Submission for Krackhack'25 in Deep Learning Domain PS "Intelligent Traffic Perception"
Basic Info
- Host: GitHub
- Owner: tomoeOOseven
- Language: Jupyter Notebook
- Default Branch: main
- Size: 15.9 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Traffic Perception Deep Learning - YOLOv8
Submission for Krackhack'25 in the Deep Learning Domain - Problem Statement: Intelligent Traffic Perception
Installation & Setup
1. Download Model Weights
Download the trained model weights from Google Drive and place them in the appropriate directories for testing.
2. Install Dependencies
Ensure you have the required dependencies installed with GPU acceleration where possible: onnxruntime pytorch opencv ultralytics numpy
3. Install NVIDIA CUDA
Download and install NVIDIA CUDA from the official website.
For Live Testing
1. Download and Unzip LocalHost Source Files
Ensure you have all necessary files for running the live server.
2. Run the Python Script
Execute the Python script to start the real-time processing
3. Open Localhost Link
Once the script is running, open the terminal to find the localhost URL. Access it through a web browser to see live real-time video from the webcam with overlays.
Or
1. Download Python File and run
Webcam will start and feed will be overlayed.
For File Testing
1. Download Python File
Ensure the test video and model weights are in the same directory.
2. Run the Script
Important Notes:
- Ensure that all files (model weights, scripts, and test video) are in the same directory.
- Use a system with an NVIDIA GPU for optimal performance.
Owner
- Name: Pramukto Mandal
- Login: tomoeOOseven
- Kind: user
- Repositories: 1
- Profile: https://github.com/tomoeOOseven
Citation (citations.md)
Dataset: https://www.kaggle.com/datasets/jahnavimurali/bdd10k Codes: https://www.kaggle.com/code/jahnavimurali/av-perception-obj-det-generative-modelling
GitHub Events
Total
- Member event: 1
- Push event: 2
- Public event: 1
Last Year
- Member event: 1
- Push event: 2
- Public event: 1