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from pandas import DataFrame
from src.application.config import WORD_BREAK
from src.application.formatting import (
color_text,
format_entity_count,
)
from src.application.image.image import ImageDetector
from src.application.text.entity import apply_highlight
from src.application.text.helper import extract_equal_text
from src.application.text.text import TextDetector
def create_governor_table(
aligned_sentences_df: DataFrame,
text: TextDetector,
image: ImageDetector,
):
rows = []
rows.append(format_image_governor_row(image))
for _, row in aligned_sentences_df.iterrows():
if row["input"] is None:
continue
if row["source"] is None:
equal_idx_1 = equal_idx_2 = []
else:
# Get index of equal phrases in input and source sentences
equal_idx_1, equal_idx_2 = extract_equal_text(
row["input"],
row["source"],
)
text.governor_table.append(
[
row,
equal_idx_1,
equal_idx_2,
row["entities"],
],
)
formatted_row = format_text_governor_row(text)
rows.append(formatted_row)
table = "\n".join(rows)
return f"""
<h5>Comparison between input news and source news:</h5>
<table border="1" style="width:100%; text-align:left;">
<col style="width: 170px;">
<col style="width: 170px;">
<col style="width: 30px;">
<col style="width: 75px;">
<thead>
<tr>
<th>Input news</th>
<th>Source (URL in Originality)</th>
<th>Forensic</th>
<th>Originality</th>
</tr>
</thead>
<tbody>
{table}
</tbody>
</table>
<style>
"""
def format_text_governor_row(text):
input_sentences = ""
source_sentences = ""
source_text_urls = ""
urls = []
sentence_count = 0
entity_count = [0, 0] # to get index of [-2]
for row in text.governor_table:
if row[0]["input"] is None:
continue
if row[0]["source"] is not None: # source is not empty
# highlight entities
input_sentence, highlight_idx_input = apply_highlight(
row[0]["input"],
row[3], # entities_with_colors
"input", # key
entity_count[-2], # since the last one is for current counting
)
source_sentence, highlight_idx_source = apply_highlight(
row[0]["source"],
row[3], # entities_with_colors
"source", # key
entity_count[-2], # since the last one is for current counting
)
# Color overlapping words
input_sentence = color_text(
input_sentence,
row[1],
highlight_idx_input,
) # text, index of highlight words
source_sentence = color_text(
source_sentence,
row[2],
highlight_idx_source,
) # text, index of highlight words
input_sentence = input_sentence.replace(
"span_style",
"span style",
).replace("1px_4px", "1px 4px")
source_sentence = source_sentence.replace(
"span_style",
"span style",
).replace("1px_4px", "1px 4px")
else:
if row[0]["source"] is None:
source_sentence = ""
else:
source_sentence = row[0]["source"]
input_sentence = row[0]["input"]
# convert score to HUMAN-based score:
input_sentences += input_sentence + "<br><br>"
source_sentences += source_sentence + "<br><br>"
url = row[0]["url"]
if url not in urls:
urls.append(url)
source_text_urls += f"""<a href="{url}">{url}</a><br><br>"""
sentence_count += 1
if row[3] is not None:
entity_count.append(len(row[3]))
entity_count_text = format_entity_count(sum(entity_count))
return f"""
<tr>
<td>{input_sentences}</td>
<td>{source_sentences}</td>
<td>{text.prediction_label[0]}<br>
({text.prediction_score[0] * 100:.2f}%)<br><br>
{entity_count_text}</td>
<td style="{WORD_BREAK}";>{source_text_urls}</td>
</tr>
"""
def format_image_governor_row(image):
if image.referent_url is not None or image.referent_url != "":
source_image = f"""<img src="{image.referent_url}" width="100" height="150">""" # noqa: E501
source_image_url = f"""<a href="{image.referent_url}">{image.referent_url}</a>""" # noqa: E501
else:
source_image = "Image not found"
source_image_url = ""
return f"""
<tr>
<td>input image</td>
<td>{source_image}</td>
<td>{image.prediction_label}<br>({image.prediction_score:.2f}%)</td>
<td style="{WORD_BREAK}";>{source_image_url}</td>
</tr>"""
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