deepface

STANAANDREY

May 31st, 2025 (edited)

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from deepface import DeepFace
import os
os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0'
def main():
# Assuming img1_path and img2_path are defined elsewhere
# and point to image files
print('matching...')
# result = DeepFace.verify(
# img1_path="bieber.jpeg",
# img2_path="bieber.jpg",
# model_name="ArcFace",
# detector_backend="retinaface"
# )
results = DeepFace.find(img_path="menight.jpeg", db_path="imgs/", model_name="ArcFace",
detector_backend="mtcnn",
distance_metric="euclidean",
#enforce_detection=False,
)
df = results[0] if isinstance(results, list) else results
print(len(df))
if len(df) == 0:
exit()
# Get the row with the smallest distance
best_match = df.iloc[df['distance'].idxmin()]
# Get the file path (identity)
identity_path = best_match['identity']
distance = best_match['distance']
print(f"Best match: {identity_path} with distance {distance}")
if __name__ == '__main__':
main()

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