SecureMLAPI / main.py
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feat: integrate ppnet inference backend
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from pathlib import Path
from PIL import Image
from model_service import get_model_config, get_model_service
IMAGE_PATH = Path("person.jpg")
# IMAGE_PATH = Path("no_person.jpg")
def main():
if not IMAGE_PATH.exists():
raise SystemExit(f"Image not found: {IMAGE_PATH}")
service = get_model_service()
config = get_model_config()
print(f"[INFO] device={service.device}")
print(f"[INFO] model_name={config.name}")
print(f"[INFO] model_backend={config.backend}")
print(f"[INFO] model_path={config.model_path}")
print(f"[INFO] image={IMAGE_PATH}")
img = Image.open(IMAGE_PATH).convert("RGB")
result = service.predict_image(img)
print("\n========== RESULT ==========")
print(f"Prediction: {result['label']}")
print(f"P(no_person) = {result['probabilities']['no_person']:.4f}")
print(f"P(person) = {result['probabilities']['person']:.4f}")
print("============================")
if __name__ == "__main__":
main()