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Model loading utilities for fingerprint analysis models
"""
import os
import pickle
import joblib
from pathlib import Path
import warnings
warnings.filterwarnings('ignore')
# Import TensorFlow
import tensorflow as tf
# Configure paths
BASE_DIR = Path(__file__).parent.parent
MODELS_DIR = BASE_DIR / "models"
# Model paths
BLOOD_GROUP_MODEL_PATH = os.environ.get(
"BLOOD_GROUP_MODEL_PATH",
str(MODELS_DIR / "blood_group.h5")
)
GENDER_MODEL_PATH = os.environ.get(
"GENDER_MODEL_PATH",
str(MODELS_DIR / "gender_model.keras")
)
# Global variables to cache loaded models
_blood_group_model = None
_gender_model = None
def load_blood_group_model():
"""Load the blood group prediction model"""
global _blood_group_model
if _blood_group_model is not None:
return _blood_group_model
try:
if BLOOD_GROUP_MODEL_PATH.endswith(('.h5', '.keras')):
try:
_blood_group_model = tf.keras.models.load_model(BLOOD_GROUP_MODEL_PATH)
except Exception as e:
# Fallback: load without compile
print(f"⚠️ Trying compile=False...")
_blood_group_model = tf.keras.models.load_model(BLOOD_GROUP_MODEL_PATH, compile=False)
_blood_group_model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])
elif BLOOD_GROUP_MODEL_PATH.endswith('.pkl'):
with open(BLOOD_GROUP_MODEL_PATH, 'rb') as f:
_blood_group_model = pickle.load(f)
elif BLOOD_GROUP_MODEL_PATH.endswith('.joblib'):
_blood_group_model = joblib.load(BLOOD_GROUP_MODEL_PATH)
else:
raise ValueError(f"Unsupported format: {BLOOD_GROUP_MODEL_PATH}")
print(f"✓ Blood group model loaded")
return _blood_group_model
except Exception as e:
raise Exception(f"Error loading blood group model: {str(e)}")
def load_gender_model():
"""Load the gender classification model"""
global _gender_model
if _gender_model is not None:
return _gender_model
try:
if GENDER_MODEL_PATH.endswith(('.h5', '.keras')):
try:
_gender_model = tf.keras.models.load_model(GENDER_MODEL_PATH)
except Exception as e:
# Fallback: load without compile
print(f"⚠️ Trying compile=False...")
_gender_model = tf.keras.models.load_model(GENDER_MODEL_PATH, compile=False)
_gender_model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])
elif GENDER_MODEL_PATH.endswith('.pkl'):
with open(GENDER_MODEL_PATH, 'rb') as f:
_gender_model = pickle.load(f)
elif GENDER_MODEL_PATH.endswith('.joblib'):
_gender_model = joblib.load(GENDER_MODEL_PATH)
else:
raise ValueError(f"Unsupported format: {GENDER_MODEL_PATH}")
print(f"✓ Gender model loaded")
return _gender_model
except Exception as e:
raise Exception(f"Error loading gender model: {str(e)}")
def set_model_paths(blood_group_path, gender_path):
"""Update model paths at runtime"""
global BLOOD_GROUP_MODEL_PATH, GENDER_MODEL_PATH
global _blood_group_model, _gender_model
BLOOD_GROUP_MODEL_PATH = blood_group_path
GENDER_MODEL_PATH = gender_path
# Clear cached models
_blood_group_model = None
_gender_model = None
print(f"Model paths updated successfully")
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