tags:
- image-classification
- timm
- chart
- charts
- fintwit
- stocks
- crypto
library_name: timm
license: mit
datasets:
- StephanAkkerman/fintwit-charts
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.
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/fintwit-charts: 1,978 images.
More Information
For a comprehensive overview, including the training setup and analysis of the model, visit the chart-recognizer GitHub repository.
Usage
Using HuggingFace's transformers library the model can be converted into a pipeline for image classification.
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 file for details.