yolov6s / README.md
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metadata
language: en
license: mit
library_name: pytorch
tags:
  - object-detection
  - yolo
  - autogenerated-modelcard
model_name: yolov6s

Model Card for yolov6s

Table of Contents

  1. Model Details
  2. Uses
  3. Bias, Risks, and Limitations
  4. Training Details
  5. Evaluation
  6. Model Examination
  7. Environmental Impact
  8. Technical Specifications
  9. Citation
  10. Glossary
  11. More Information
  12. Model Card Authors
  13. Model Card Contact
  14. How To Get Started With the Model

Model Details

Model Description

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: yolov6t, yolov6n
    • Parent Model: N/A
  • Resources for more information: The official GitHub Repository

Uses

Direct Use

This model is meant to be used as a general object detector.

Downstream Use [Optional]

You can fine-tune this model for your specific task

Out-of-Scope Use

Don't be evil.

Bias, Risks, and Limitations

This model often classifies objects incorrectly, especially when applied to videos. It does not handle crowds very well.

Recommendations

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

[More Information Needed]

Training Procedure

Preprocessing

[More Information Needed]

Speeds, Sizes, Times

[More Information Needed]

Evaluation

Testing Data, Factors & Metrics

Testing Data

[More Information Needed]

Factors

[More Information Needed]

Metrics

[More Information Needed]

Results

[More Information Needed]

Model Examination

[More Information Needed]

Environmental Impact

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

[More Information Needed]

Compute Infrastructure

[More Information Needed]

Hardware

[More Information Needed]

Software

[More Information Needed]

Citation

BibTeX:

[More Information Needed]

APA:

[More Information Needed]

Glossary [optional]

[More Information Needed]

More Information [optional]

Please refer to the official GitHub Repository

Model Card Authors [optional]

@nateraw

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.

Click to expand

[More Information Needed]