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Configuration error
Configuration error
File size: 4,013 Bytes
3dbd7d4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 | import sqlite3
import pandas as pd
from config import DB_PATH
def get_conn():
return sqlite3.connect(DB_PATH, check_same_thread=False)
def init_db():
conn = get_conn()
cur = conn.cursor()
cur.execute("""
CREATE TABLE IF NOT EXISTS analysis_results (
id INTEGER PRIMARY KEY AUTOINCREMENT,
timestamp TEXT NOT NULL,
file_name TEXT NOT NULL,
file_type TEXT NOT NULL,
label TEXT NOT NULL,
score REAL NOT NULL,
saved_to TEXT NOT NULL,
source TEXT DEFAULT ''
)
""")
conn.commit()
conn.close()
def insert_result(timestamp, file_name, file_type, label, score, saved_to, source=""):
conn = get_conn()
cur = conn.cursor()
cur.execute("""
INSERT INTO analysis_results
(timestamp, file_name, file_type, label, score, saved_to, source)
VALUES (?, ?, ?, ?, ?, ?, ?)
""", (
str(timestamp),
str(file_name),
str(file_type),
str(label),
float(score),
str(saved_to),
str(source)
))
conn.commit()
conn.close()
def read_results_df():
conn = get_conn()
try:
df = pd.read_sql_query("""
SELECT
timestamp,
file_name,
file_type,
label,
score,
saved_to,
source
FROM analysis_results
ORDER BY id DESC
""", conn)
return df
except Exception:
return pd.DataFrame(columns=[
"timestamp",
"file_name",
"file_type",
"label",
"score",
"saved_to",
"source"
])
finally:
conn.close()
def delete_all_results():
conn = get_conn()
cur = conn.cursor()
cur.execute("DELETE FROM analysis_results")
conn.commit()
conn.close()
def export_results_csv(csv_path="results_export.csv"):
df = read_results_df()
df.to_csv(csv_path, index=False, encoding="utf-8-sig")
return csv_path
def get_stats():
conn = get_conn()
cur = conn.cursor()
stats = {
"total": 0,
"fake_count": 0,
"real_count": 0,
"image_count": 0,
"audio_count": 0,
"video_count": 0,
"avg_score": 0.0
}
try:
cur.execute("SELECT COUNT(*) FROM analysis_results")
stats["total"] = cur.fetchone()[0] or 0
cur.execute("""
SELECT COUNT(*)
FROM analysis_results
WHERE lower(label) LIKE '%fake%'
OR lower(label) LIKE '%deepfake%'
OR lower(label) LIKE '%synthetic%'
OR lower(label) LIKE '%suspicious%'
""")
stats["fake_count"] = cur.fetchone()[0] or 0
stats["real_count"] = stats["total"] - stats["fake_count"]
cur.execute("""
SELECT COUNT(*)
FROM analysis_results
WHERE lower(file_type) = 'image'
""")
stats["image_count"] = cur.fetchone()[0] or 0
cur.execute("""
SELECT COUNT(*)
FROM analysis_results
WHERE lower(file_type) = 'audio'
""")
stats["audio_count"] = cur.fetchone()[0] or 0
cur.execute("""
SELECT COUNT(*)
FROM analysis_results
WHERE lower(file_type) = 'video'
""")
stats["video_count"] = cur.fetchone()[0] or 0
cur.execute("""
SELECT AVG(score)
FROM analysis_results
""")
avg_score = cur.fetchone()[0]
stats["avg_score"] = round(float(avg_score), 4) if avg_score is not None else 0.0
return stats
except Exception:
return stats
finally:
conn.close() |