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---
license: apache-2.0
language:
- en
pipeline_tag: object-detection
tags:
- code
---
# David YOLOS Model
This repository contains a custom YOLOS model fine-tuned on the [Balloon Dataset](https://github.com/matterport/Mask_RCNN/tree/master/samples/balloon) for object detection tasks. The model was trained using the PyTorch Lightning framework and is available for inference and further fine-tuning.
## Model Details
- **Model Architecture**: YOLOS (You Only Look One-level Object Structure)
- **Base Model**: `hustvl/yolos-small`
- **Training Framework**: PyTorch Lightning
- **Dataset**: Balloon Dataset
- **Number of Classes**: 1 (Balloon)
## Installation and Usage
### Installation
You can install the necessary libraries using:
```bash
pip install transformers torch torchvision
```
# Usage
You can load and use the model with the following code:
```python
from transformers import AutoModelForObjectDetection, AutoFeatureExtractor
from PIL import Image
import torch
# Load model and feature extractor
model_name = "your-username/my-custom-yolos-model"
model = AutoModelForObjectDetection.from_pretrained(model_name)
feature_extractor = AutoFeatureExtractor.from_pretrained(model_name)
# Load an image
image = Image.open("path/to/your/image.jpg")
# Preprocess the image
inputs = feature_extractor(images=image, return_tensors="pt")
pixel_values = inputs['pixel_values']
# Perform inference
model.eval()
with torch.no_grad():
outputs = model(pixel_values=pixel_values)
# Visualize the results
# (Insert visualization code here)
```
# Model Performance
- Training Loss: 0.0614
- Validation Loss: 0.1784
- Training Dataset: Balloon Dataset (XXX images)
- Validation Dataset: Balloon Dataset (XXX images)
- Number of Epochs: 75
# Citation
If you use this model in your research, please cite:
```bibtex
Copy code
@misc{my-custom-yolos-model,
author = {Your Name},
title = {YOLOS Fine-tuned on Balloon Dataset},
year = {2024},
publisher = {Hugging Face},
howpublished = {\url{https://huggingface.co./your-username/my-custom-yolos-model}},
}
```
# License
This model is licensed under the MIT License. Feel free to use, modify, and distribute it as you see fit.
# Copy code
You can copy and paste this Markdown into your README file on Hugging Face. |