| import gradio as gr | |
| import pandas as pd | |
| from jiwer import wer | |
| import re | |
| import os | |
| REGEX_YAML_BLOCK = re.compile(r"---[\n\r]+([\S\s]*?)[\n\r]+---[\n\r]") | |
| def parse_readme(filepath): | |
| """Parses a repositories README and removes""" | |
| if not os.path.exists(filepath): | |
| return "No README.md found." | |
| with open(filepath, "r") as f: | |
| text = f.read() | |
| match = REGEX_YAML_BLOCK.search(text) | |
| if match: | |
| text = text[match.end() :] | |
| return text | |
| def compute(input): | |
| preds = input['prediction'].tolist() | |
| truths = input['truth'].tolist() | |
| print(truths, preds, type(truths)) | |
| err = wer(truths, preds) | |
| print(err) | |
| return err | |
| description = """ | |
| To calculate WER: | |
| * Type the `prediction` and the `truth` in the respective columns in the below calculator. | |
| * You can insert multiple predictions and truths by clicking on the `New row` button. | |
| * To calculate the WER after inserting all the texts, click on `Submit`. | |
| """ | |
| demo = gr.Interface( | |
| fn=compute, | |
| inputs=gr.components.Dataframe( | |
| headers=["prediction", "truth"], | |
| col_count=2, | |
| row_count=1, | |
| label="Input" | |
| ), | |
| outputs=gr.components.Textbox(label="WER"), | |
| description=description, | |
| title="WER Calculator", | |
| article=parse_readme("README.md") | |
| ) | |
| demo.launch() | |