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---
tags:
- image-classification
- timm
- chart
- charts
- fintwit
- stocks
- crypto
library_name: timm
license: mit
datasets:
- StephanAkkerman/crypto-charts
- StephanAkkerman/stock-charts
- StephanAkkerman/fintwit-images
language:
- en
metrics:
- accuracy
- f1
- precision
- recall
pipeline_tag: image-classification
base_model: timm/efficientnet_b0.ra_in1k
---
# Chart Recognizer
chart-recognizer is a finetuned model for classifying images. It uses efficientnet as its base model, making it a fast and small model.
This model is trained on my own dataset of financial charts posted on Twitter, which can be found here [StephanAkkerman/fintwit-charts](https://huggingface.co/datasets/StephanAkkerman/fintwit-charts).
## Intended Uses
chart-recognizer is intended for classifying images, mainly images posted on social media.
## Dataset
chart-recognizer has been trained on my own dataset. So far I have not been able to find another image dataset about financial charts.
- [StephanAkkerman/crypto-charts](https://huggingface.co/datasets/StephanAkkerman/crypto-charts): 4,880 images.
- [StephanAkkerman/stock-charts](https://huggingface.co/datasets/StephanAkkerman/stock-charts): 5,203 images.
- [StephanAkkerman/fintwit-images](https://huggingface.co/datasets/StephanAkkerman/fintwit-images): 4,579 images.
### Example Images
The following images are not part of the training set and can be used for testing purposes.
#### Chart
#### Non-Chart
This can be any image that does not represent a (financial) chart.
## More Information
For a comprehensive overview, including the training setup and analysis of the model, visit the [chart-recognizer GitHub repository](https://github.com/StephanAkkerman/chart-recognizer).
## Usage
Using [HuggingFace's transformers library](https://huggingface.co/docs/transformers/index) the model can be converted into a pipeline for image classification.
```python
from transformers import pipeline
# Create a sentiment analysis pipeline
pipe = pipeline(
"image-classification",
model="StephanAkkerman/chart-recognizer",
)
# Get the predicted sentiment
print(pipe(image))
```
## Citing & Authors
If you use chart-recognizer in your research, please cite me as follows:
```
@misc{chart-recognizer,
author = {Stephan Akkerman},
title = {chart-recognizer: A Specialized Image Model for Financial Charts},
year = {2024},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/StephanAkkerman/chart-recognizer}}
}
```
## License
This project is licensed under the MIT License. See the [LICENSE](https://choosealicense.com/licenses/mit/) file for details. |