--- tags: - image-classification - timm - chart - charts - fintwit - stocks - crypto library_name: timm license: apache-2.0 datasets: - StephanAkkerman/fintwit-charts language: - en metrics: - accuracy - f1 - precision - recall pipeline_tag: image-classification base_model: efficientnet_b0 --- # 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/fintwit-charts](https://huggingface.co/datasets/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](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.