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Runtime error
| from constants import RESOURCES | |
| from data_preprocessing import RandomizeImageTransform | |
| from utils import beam_search_decode | |
| import streamlit as st | |
| import PIL | |
| import torch | |
| import torchvision.transforms as T | |
| MODEL_PATH = RESOURCES + "/model_2tcuvfsj.pt" | |
| transformer = torch.load(MODEL_PATH) | |
| image_transform = T.Compose(( | |
| T.ToTensor(), | |
| RandomizeImageTransform(width=transformer.hparams['image_width'], | |
| height=transformer.hparams['image_height'], | |
| random_magnitude=0) | |
| )) | |
| st.title("Image to TeX") | |
| st.image("resources/frontend/fraction_derivative.png", width=500) | |
| st.image("resources/frontend/positional_encoding.png") | |
| st.image("resources/frontend/taylor_sequence_expanded.png") | |
| # st.image("resources/frontend/taylor_sequence.png") | |
| # st.image("resources/frontend/maclaurin_series.png") | |
| # st.image("resources/frontend/gauss_distribution.png") | |
| image_file = st.file_uploader("Upload an image with equation", type=([".png", ".jpg", ".jpeg"])) | |
| if image_file is not None: | |
| image = PIL.Image.open(image_file) | |
| image = image.convert("RGB") | |
| texs = beam_search_decode(transformer, image, image_transform=image_transform) | |
| # streamlit latex doesn't support boldmath | |
| tex = texs[0].replace("\\boldmath", "") | |
| st.latex(tex) | |
| st.markdown(tex) | |