8f05a7c188
- Update ASR, face, OCR, pose processors - Add release pre-flight check script - Add synonym generation, chunk processing scripts - Add face recognition, stamp search utilities
133 lines
3.6 KiB
Python
133 lines
3.6 KiB
Python
#!/opt/homebrew/bin/python3.11
|
|
"""
|
|
Comprehensive Age & Gender Updater.
|
|
Scans all persons in DB, finds a representative frame, and updates demographics using InsightFace.
|
|
"""
|
|
|
|
import os
|
|
import cv2
|
|
import psycopg2
|
|
import insightface
|
|
import numpy as np
|
|
|
|
# Configuration
|
|
DB_CONFIG = {"host": "localhost", "user": "accusys", "dbname": "momentry"}
|
|
BASE_VIDEO_DIR = "output"
|
|
|
|
|
|
def get_face_app():
|
|
print("Loading InsightFace model (buffalo_l)...")
|
|
app = insightface.app.FaceAnalysis(
|
|
name="buffalo_l", providers=["CPUExecutionProvider"]
|
|
)
|
|
app.prepare(ctx_id=0, det_size=(640, 640))
|
|
return app
|
|
|
|
|
|
def get_video_path(video_uuid):
|
|
"""Locate video file."""
|
|
path = f"{BASE_VIDEO_DIR}/{video_uuid}/{video_uuid}.mp4"
|
|
if os.path.exists(path):
|
|
return path
|
|
return None
|
|
|
|
|
|
def update_db(conn, person_id, age, gender):
|
|
"""Update demographics in DB."""
|
|
cur = conn.cursor()
|
|
cur.execute(
|
|
"""
|
|
UPDATE person_identities
|
|
SET age = %s, gender = %s
|
|
WHERE person_id = %s
|
|
""",
|
|
(age, gender, person_id),
|
|
)
|
|
conn.commit()
|
|
|
|
|
|
def process_person(app, conn, person_id, video_uuid, timestamp):
|
|
"""Extract frame and analyze face."""
|
|
video_path = get_video_path(video_uuid)
|
|
if not video_path:
|
|
return
|
|
|
|
# OpenCV seek (approximate)
|
|
cap = cv2.VideoCapture(video_path)
|
|
if not cap.isOpened():
|
|
return
|
|
|
|
# Try seeking by msec
|
|
cap.set(cv2.CAP_PROP_POS_MSEC, timestamp * 1000)
|
|
ret, frame = cap.read()
|
|
|
|
# If seeking failed or frame is bad, try frame number estimation (assuming 30fps as fallback, though inaccurate)
|
|
# But for this script, we just try a few times around the timestamp
|
|
attempts = 0
|
|
while not ret and attempts < 3:
|
|
ret, frame = cap.read()
|
|
attempts += 1
|
|
|
|
cap.release()
|
|
|
|
if not ret or frame is None:
|
|
print(f" - Failed to get frame for {person_id}")
|
|
return
|
|
|
|
# Analyze
|
|
faces = app.get(frame)
|
|
if faces:
|
|
# Take the first (usually largest/clearest) face
|
|
face = faces[0]
|
|
age = int(face.age) if hasattr(face, "age") else None
|
|
gender_val = face.gender if hasattr(face, "gender") else None
|
|
|
|
# gender is often 0 or 1 in insightface, map it
|
|
gender = "female" if gender_val == 0 else ("male" if gender_val == 1 else None)
|
|
|
|
if age and gender:
|
|
print(f" -> Detected: Age {age}, Gender {gender}")
|
|
update_db(conn, person_id, age, gender)
|
|
else:
|
|
print(f" -> Face found but attributes missing.")
|
|
else:
|
|
print(f" -> No face detected in frame.")
|
|
|
|
|
|
def main():
|
|
print("=== Starting Full Demographics Scan ===")
|
|
|
|
conn = psycopg2.connect(**DB_CONFIG)
|
|
cur = conn.cursor()
|
|
|
|
# Get all persons missing age/gender
|
|
# We group by person_id and video_uuid to handle multiple videos if necessary
|
|
cur.execute("""
|
|
SELECT person_id, video_uuid, MIN(first_appearance_time) as min_time
|
|
FROM person_identities
|
|
WHERE age IS NULL OR gender IS NULL
|
|
GROUP BY person_id, video_uuid
|
|
""")
|
|
rows = cur.fetchall()
|
|
|
|
if not rows:
|
|
print("All persons already have demographics data!")
|
|
return
|
|
|
|
print(f"Found {len(rows)} persons to process.")
|
|
|
|
app = get_face_app()
|
|
|
|
for i, (person_id, video_uuid, min_time) in enumerate(rows):
|
|
print(
|
|
f"[{i + 1}/{len(rows)}] Processing: {person_id} (Video: {video_uuid}, Time: {min_time:.1f}s)"
|
|
)
|
|
process_person(app, conn, person_id, video_uuid, min_time)
|
|
|
|
print("=== Done ===")
|
|
conn.close()
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|