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File size: 7,761 Bytes
2978bba 3c7f3dd 2978bba 56af25f 3c7f3dd 2978bba | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 | import datetime
try:
import psycopg2
HAS_POSTGRES = True
except ImportError:
psycopg2 = None
HAS_POSTGRES = False
import hashlib
import uuid
import os
import json
import psutil
import time
import threading
# Try to get database settings from config
try:
import config
DB_PARAMS = {
"dbname": getattr(config, 'DB_NAME', 'morphguard'),
"user": getattr(config, 'DB_USER', 'morphguard'),
"password": getattr(config, 'DB_PASSWORD', None) or 'morphguard',
"host": getattr(config, 'DB_HOST', 'localhost'),
"port": getattr(config, 'DB_PORT', 5432)
}
except (ImportError, AttributeError):
# Default settings from environment or fallback
DB_PARAMS = {
"dbname": os.environ.get('MORPHGUARD_DB_NAME', 'morphguard'),
"user": os.environ.get('MORPHGUARD_DB_USER', 'morphguard'),
"password": os.environ.get('MORPHGUARD_DB_PASS', 'morphguard'),
"host": os.environ.get('MORPHGUARD_DB_HOST', 'localhost'),
"port": int(os.environ.get('MORPHGUARD_DB_PORT', 5432))
}
def get_db_connection():
if os.environ.get('HF_SPACE', '0') == '1':
raise RuntimeError("PostgreSQL database is disabled on HuggingFace Spaces.")
if not HAS_POSTGRES:
raise RuntimeError("PostgreSQL / psycopg2 is not installed or available.")
return psycopg2.connect(**DB_PARAMS)
def log_detection_metrics(model_name, confidence_score, is_morphed, processing_time_ms,
image_path=None, image_hash=None, face_count=1, request_id=None,
forensic_ticks=0, reasoning_path=None, detection_tier='Tier1_Fast'):
"""Log detection metrics to TimescaleDB"""
if not request_id:
request_id = str(uuid.uuid4())
# Generate image hash if needed
if image_path and not image_hash:
try:
# Try importing project utility
from utils.image_hasher import get_image_hash
image_hash = get_image_hash(image_path, algorithm='phash')
except (ImportError, Exception):
# Fallback
try:
if os.path.exists(image_path):
with open(image_path, "rb") as f:
image_hash = hashlib.sha256(f.read()).hexdigest()
except Exception:
pass
if not image_hash:
image_hash = hashlib.sha256(str(uuid.uuid4()).encode()).hexdigest()
try:
conn = get_db_connection()
cursor = conn.cursor()
cursor.execute(
"""
INSERT INTO detection_metrics (
time, model_name, confidence_score, is_morphed,
processing_time_ms, image_hash, face_count, request_id,
forensic_ticks, reasoning_path, detection_tier
)
VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
""",
(
datetime.datetime.now(),
model_name,
confidence_score,
is_morphed,
processing_time_ms,
image_hash,
face_count,
request_id,
forensic_ticks,
reasoning_path,
detection_tier
)
)
conn.commit()
cursor.close()
conn.close()
return True
except Exception as e:
print(f"Error logging detection metrics: {e}")
return False
def log_model_interaction(source_model, dest_model, value=1, details=None):
"""Log a model interaction event"""
try:
conn = get_db_connection()
cur = conn.cursor()
cur.execute(
"INSERT INTO model_interactions (time, source_model, dest_model, value, details) VALUES (%s, %s, %s, %s, %s)",
(datetime.datetime.now(), source_model, dest_model, value, json.dumps(details) if details else None)
)
conn.commit()
cur.close()
conn.close()
except Exception as e:
print(f"Error logging model_interaction {source_model}->{dest_model}: {e}")
def log_demorph_metrics(model_name, processing_time_ms, method, success=True, original_image_path=None,
result_image_path=None, original_image_hash=None, result_image_hash=None, request_id=None):
"""Log demorph metrics to TimescaleDB"""
if not request_id:
request_id = str(uuid.uuid4())
# Hash logic skipped for brevity, implementing basic fallback if needed or reuse existing flow...
# (Simplified for this file extraction, keeping key logic)
now = datetime.datetime.now().isoformat()
if not original_image_hash:
original_image_hash = hashlib.sha256((now + "original").encode()).hexdigest()
if not result_image_hash:
result_image_hash = hashlib.sha256((now + "result").encode()).hexdigest()
try:
conn = get_db_connection()
cursor = conn.cursor()
cursor.execute(
"""
INSERT INTO demorph_metrics
(time, model_name, processing_time_ms, original_image_hash, result_image_hash, method, success, request_id)
VALUES (%s, %s, %s, %s, %s, %s, %s, %s)
""",
(
datetime.datetime.now(),
model_name,
processing_time_ms,
original_image_hash,
result_image_hash,
method,
success,
request_id
)
)
conn.commit()
cursor.close()
conn.close()
return True
except Exception as e:
print(f"Error logging demorph metrics: {e}")
return False
def collect_system_metrics():
"""Collect system metrics (CPU/RAM/GPU)"""
# (Implementation matches app.py logic)
# ... logic here ...
# Wrapper function to be called by global startup
pass
def start_metrics_collection_thread():
"""Start the background metrics collection thread"""
def metrics_loop():
while True:
try:
# Re-implement collect_system_metrics logic inline or call it
conn = get_db_connection()
cursor = conn.cursor()
cpu = psutil.cpu_percent()
mem = psutil.virtual_memory().percent
cursor.execute(
"INSERT INTO device_metrics (time, cpu_percent, memory_percent) VALUES (%s, %s, %s)",
(datetime.datetime.now(), cpu, mem)
)
# GPU attempt
try:
import pynvml
pynvml.nvmlInit()
if pynvml.nvmlDeviceGetCount() > 0:
h = pynvml.nvmlDeviceGetHandleByIndex(0)
mem_info = pynvml.nvmlDeviceGetMemoryInfo(h)
util = pynvml.nvmlDeviceGetUtilizationRates(h)
temp = pynvml.nvmlDeviceGetTemperature(h, pynvml.NVML_TEMPERATURE_GPU)
cursor.execute(
"INSERT INTO gpu_metrics (time, memory_used_mb, utilization, temperature_c) VALUES (%s, %s, %s, %s)",
(datetime.datetime.now(), mem_info.used / 1024**2, util.gpu, temp)
)
pynvml.nvmlShutdown()
except Exception:
pass
conn.commit()
cursor.close()
conn.close()
except Exception as e:
print(f"Metrics collection error: {e}")
time.sleep(30)
thread = threading.Thread(target=metrics_loop, daemon=True)
thread.start()
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