Model Card for yolov6t
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Table of Contents
- Model Details
- Uses
- Bias, Risks, and Limitations
- Training Details
- Evaluation
- Model Examination
- Environmental Impact
- Technical Specifications
- Citation
- Glossary
- More Information
- Model Card Authors
- Model Card Contact
- How To Get Started With the Model
Model Details
Model Description
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YOLOv6 is a single-stage object detection framework dedicated to industrial applications, with hardware-friendly efficient design and high performance.
- Developed by: [More Information Needed]
- Shared by [Optional]: @nateraw
- Model type: [More Information Needed]
- Language(s) (NLP): [More Information Needed]
- License: [More Information Needed]
- Related Models: yolov6s, yolov6n
- Parent Model: N/A
- Resources for more information: The official GitHub Repository
Uses
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Direct Use
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This model is meant to be used as a general object detector.
Downstream Use [Optional]
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You can fine-tune this model for your specific task
Out-of-Scope Use
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Don't be evil.
Bias, Risks, and Limitations
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This model often classifies objects incorrectly, especially when applied to videos. It does not handle crowds very well.
Recommendations
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recomendations.
Training Details
Training Data
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[More Information Needed]
Training Procedure
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Preprocessing
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Speeds, Sizes, Times
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Evaluation
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Testing Data, Factors & Metrics
Testing Data
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[More Information Needed]
Factors
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Metrics
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Results
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Model Examination
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Environmental Impact
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Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type: [More Information Needed]
- Hours used: [More Information Needed]
- Cloud Provider: [More Information Needed]
- Compute Region: [More Information Needed]
- Carbon Emitted: [More Information Needed]
Technical Specifications [optional]
Model Architecture and Objective
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Compute Infrastructure
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Hardware
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Software
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Citation
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BibTeX:
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APA:
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Glossary [optional]
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More Information [optional]
Please refer to the official GitHub Repository
Model Card Authors [optional]
Model Card Contact
@nateraw - please leave a note in the discussions tab here
How to Get Started with the Model
Use the code below to get started with the model.
<details> <summary> Click to expand </summary>
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