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2025-10-30 09:38:00 +09:00
parent 37932cce6d
commit 328d5f3ce8
276 changed files with 188 additions and 3333 deletions
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113
workspace/ocr_eval_app.py
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@@ -1,11 +1,10 @@
# ocr_eval_app.py
import base64
import json
import difflib
import json
from pathlib import Path
import pandas as pd
import io
import pandas as pd
import streamlit as st
from ocr_eval_engine import OCREvaluator
@@ -15,8 +14,9 @@ EDIT_KEY = "parsed"
# --- 헬퍼 함수 ---
def get_evaluable_sessions():
""" "shared_sessions"에서 'groundtruth' 폴더를 포함하는 세션 목록을 가져옵니다. """
""" "shared_sessions"에서 'groundtruth' 폴더를 포함하는 세션 목록을 가져옵니다."""
if not SESSION_BASE_PATH.exists():
return []
evaluable = []
@@ -25,9 +25,11 @@ def get_evaluable_sessions():
evaluable.append(d.name)
return sorted(evaluable)
def get_session_path(seed):
return SESSION_BASE_PATH / seed
def display_pdf(file_path):
"""PDF 파일을 iframe으로 표시합니다."""
bytes_data = file_path.read_bytes()
@@ -37,6 +39,7 @@ def display_pdf(file_path):
unsafe_allow_html=True,
)
def generate_hyp_html(ref: str, hyp: str) -> str:
"""
difflib.SequenceMatcher를 사용하여 가설(hyp) 텍스트의 오류를 시각화하는 HTML을 생성합니다.
@@ -45,18 +48,23 @@ def generate_hyp_html(ref: str, hyp: str) -> str:
html_out = ""
for tag, i1, i2, j1, j2 in matcher.get_opcodes():
hyp_chunk = hyp[j1:j2]
hyp_chunk_display = hyp_chunk.replace("&", "&amp;").replace("<", "&lt;").replace(">", "&gt;")
hyp_chunk_display = hyp_chunk_display.replace("\n", "<br>").replace(" ", "&nbsp;")
hyp_chunk_display = (
hyp_chunk.replace("&", "&amp;").replace("<", "&lt;").replace(">", "&gt;")
)
hyp_chunk_display = hyp_chunk_display.replace("\n", "<br>").replace(
" ", "&nbsp;"
)
if tag == 'equal':
if tag == "equal":
html_out += f'<span style="color: black;">{hyp_chunk_display}</span>'
elif tag == 'replace':
elif tag == "replace":
html_out += f'<span style="color: red; background-color: #ffdddd; font-weight: bold;">{hyp_chunk_display}</span>'
elif tag == 'insert':
elif tag == "insert":
html_out += f'<span style="color: green; background-color: #ddffdd; font-weight: bold;">{hyp_chunk_display}</span>'
return f'<div style="font-family: monospace; border: 1px solid #ddd; padding: 10px; border-radius: 5px; white-space: normal; word-break: break-all; line-height: 1.6;">{html_out}</div>'
def match_evaluation_files(seed):
"""
세션 폴더 내에서 평가에 필요한 파일들의 목록을 찾아서 매칭합니다.
@@ -86,6 +94,7 @@ def match_evaluation_files(seed):
}
return matched
def display_evaluation_for_file(files):
"""선택된 파일에 대한 평가 결과를 표시합니다."""
st.header("📊 성능 평가 결과")
@@ -98,9 +107,15 @@ def display_evaluation_for_file(files):
with open(files["upstage_file"], "r", encoding="utf-8") as f:
upstage_data = json.load(f)
gt_text = (gt_data[0] if isinstance(gt_data, list) else gt_data).get(EDIT_KEY, "")
paddle_text = (paddle_data[0] if isinstance(paddle_data, list) else paddle_data).get(EDIT_KEY, "")
upstage_text = (upstage_data[0] if isinstance(upstage_data, list) else upstage_data).get(EDIT_KEY, "")
gt_text = (gt_data[0] if isinstance(gt_data, list) else gt_data).get(
EDIT_KEY, ""
)
paddle_text = (
paddle_data[0] if isinstance(paddle_data, list) else paddle_data
).get(EDIT_KEY, "")
upstage_text = (
upstage_data[0] if isinstance(upstage_data, list) else upstage_data
).get(EDIT_KEY, "")
if not gt_text:
st.warning("정답 텍스트가 비어있어 평가할 수 없습니다.")
@@ -118,7 +133,7 @@ def display_evaluation_for_file(files):
m_col2.metric("엄격한 CER", f"{paddle_results['strict_cer']:.2%}")
m_col1.metric("유연한 WER", f"{paddle_results['flexible_wer']:.2%}")
m_col2.metric("유연한 CER", f"{paddle_results['flexible_cer']:.2%}")
with col2:
st.markdown("#### Model 2: Upstage OCR")
m_col1, m_col2 = st.columns(2)
@@ -128,13 +143,16 @@ def display_evaluation_for_file(files):
m_col2.metric("유연한 CER", f"{upstage_results['flexible_cer']:.2%}")
with st.expander("상세 텍스트 비교", expanded=True):
st.markdown("""
st.markdown(
"""
<style>.legend{display:flex;align-items:center;margin-bottom:10px;}.legend-box{width:20px;height:20px;margin-right:10px;border:1px solid #ccc;}</style>
<b>범례 (Legend)</b>
<div class="legend"><div class="legend-box" style="background-color:white;"></div><span>일치하는 텍스트</span></div>
<div class="legend"><div class="legend-box" style="background-color:#ddffdd;"></div><span><b>삽입된 텍스트</b> (정답에 없음)</span></div>
<div class="legend"><div class="legend-box" style="background-color:#ffdddd;"></div><span><b>치환된 텍스트</b> (정답과 다름)</span></div>
""", unsafe_allow_html=True)
""",
unsafe_allow_html=True,
)
st.markdown("---")
text_col1, text_col2, text_col3 = st.columns(3)
@@ -153,6 +171,7 @@ def display_evaluation_for_file(files):
except Exception as e:
st.error(f"성능 평가 중 오류 발생: {e}")
@st.cache_data
def generate_all_results_df(_matched_files):
"""세션의 모든 파일에 대한 평가 결과를 집계하여 DataFrame으로 반환합니다."""
@@ -166,34 +185,56 @@ def generate_all_results_df(_matched_files):
with open(files["upstage_file"], "r", encoding="utf-8") as f:
upstage_data = json.load(f)
gt_text = (gt_data[0] if isinstance(gt_data, list) else gt_data).get(EDIT_KEY, "")
gt_text = (gt_data[0] if isinstance(gt_data, list) else gt_data).get(
EDIT_KEY, ""
)
if not gt_text:
continue
evaluator = OCREvaluator(gt_text)
# Paddle 모델 평가
paddle_text = (paddle_data[0] if isinstance(paddle_data, list) else paddle_data).get(EDIT_KEY, "")
paddle_text = (
paddle_data[0] if isinstance(paddle_data, list) else paddle_data
).get(EDIT_KEY, "")
paddle_results = evaluator.evaluate(paddle_text)
paddle_results['model'] = 'paddle_ocr'
paddle_results['file'] = basename
paddle_results["model"] = "paddle_ocr"
paddle_results["file"] = basename
all_results.append(paddle_results)
# Upstage 모델 평가
upstage_text = (upstage_data[0] if isinstance(upstage_data, list) else upstage_data).get(EDIT_KEY, "")
upstage_text = (
upstage_data[0] if isinstance(upstage_data, list) else upstage_data
).get(EDIT_KEY, "")
upstage_results = evaluator.evaluate(upstage_text)
upstage_results['model'] = 'upstage_ocr'
upstage_results['file'] = basename
upstage_results["model"] = "upstage_ocr"
upstage_results["file"] = basename
all_results.append(upstage_results)
except Exception:
# 오류가 있는 파일은 건너뜀
continue
df = pd.DataFrame(all_results)
# 컬럼 순서 재정렬
ordered_cols = ['file', 'model', 'strict_wer', 'strict_cer', 'flexible_wer', 'flexible_cer', 'word_hits', 'word_substitutions', 'word_deletions', 'word_insertions', 'char_hits', 'char_substitutions', 'char_deletions', 'char_insertions']
ordered_cols = [
"file",
"model",
"strict_wer",
"strict_cer",
"flexible_wer",
"flexible_cer",
"word_hits",
"word_substitutions",
"word_deletions",
"word_insertions",
"char_hits",
"char_substitutions",
"char_deletions",
"char_insertions",
]
return df[ordered_cols]
# --- 콜백 함수 ---
def handle_nav_button(direction, total_files):
if direction == "prev" and st.session_state.eval_current_index > 0:
@@ -201,9 +242,11 @@ def handle_nav_button(direction, total_files):
elif direction == "next" and st.session_state.eval_current_index < total_files - 1:
st.session_state.eval_current_index += 1
def handle_selectbox_change():
st.session_state.eval_current_index = st.session_state.eval_selectbox_key
# --- 메인 UI 로직 ---
def main():
st.set_page_config(layout="wide", page_title="OCR 성능 평가 도구")
@@ -214,9 +257,11 @@ def main():
st.sidebar.header("세션 선택")
sessions = get_evaluable_sessions()
if not sessions:
st.info("평가 가능한 세션이 없습니다. 먼저 '정답셋 생성 도구'에서 정답셋을 생성해주세요.")
st.info(
"평가 가능한 세션이 없습니다. 먼저 '정답셋 생성 도구'에서 정답셋을 생성해주세요."
)
return
seed = st.sidebar.selectbox("평가할 세션을 선택하세요.", sessions)
@@ -228,14 +273,16 @@ def main():
matched_files = match_evaluation_files(seed)
if matched_files is None:
st.error(f"'{seed}'에 해당하는 세션을 찾을 수 없거나, 필요한 폴더(docs, groundtruth 등)가 없습니다.")
st.error(
f"'{seed}'에 해당하는 세션을 찾을 수 없거나, 필요한 폴더(docs, groundtruth 등)가 없습니다."
)
return
if not matched_files:
st.warning("해당 세션에 평가할 파일(정답셋이 생성된 파일)이 없습니다.")
return
sorted_basenames = sorted(list(matched_files.keys()))
if st.session_state.eval_current_index >= len(sorted_basenames):
st.session_state.eval_current_index = 0
@@ -255,7 +302,7 @@ def main():
st.sidebar.header("내보내기")
results_df = generate_all_results_df(matched_files)
if not results_df.empty:
csv = results_df.to_csv(index=False).encode('utf-8')
csv = results_df.to_csv(index=False).encode("utf-8")
st.sidebar.download_button(
label="전체 결과 CSV 다운로드",
data=csv,
@@ -265,9 +312,8 @@ def main():
else:
st.sidebar.write("다운로드할 결과가 없습니다.")
current_basename = sorted_basenames[st.session_state.eval_current_index]
nav_cols = st.columns([1, 5, 1])
nav_cols[0].button(
"◀ 이전",
@@ -303,5 +349,6 @@ def main():
with col2:
display_evaluation_for_file(files_to_evaluate)
if __name__ == "__main__":
main()