logger

inference.py

@@ -121,20 +121,20 @@ def _load_hf_models() -> None:
                     model="prithivMLmods/Deepfake-Detection-Exp-02-21",
                     device=hf_device,
                 )
-                logger.info("HF model 1 loaded.")
+                logger.debug("HF model 1 loaded.")
             except Exception as exc:
                 logger.warning(f"HF model 1 failed to load: {exc}")
                 _model_hf1 = False
 
         if _model_hf2 is None:
             try:
-                logger.info("Loading HF model 2: Deep-Fake-Detector-v2-Model ...")
+                logger.debug("Loading HF model 2: Deep-Fake-Detector-v2-Model ...")
                 _model_hf2 = hf_pipeline(
                     "image-classification",
                     model="prithivMLmods/Deep-Fake-Detector-v2-Model",
                     device=hf_device,
                 )
-                logger.info("HF model 2 loaded.")
+                logger.debug("HF model 2 loaded.")
             except Exception as exc:
                 logger.warning(f"HF model 2 failed to load: {exc}")
                 _model_hf2 = False
@@ -244,9 +244,8 @@ def predict_with_confidence(image_source) -> tuple:
     cnn_confidence_pct = cnn_conf * 100
     final_confidence   = (vote_confidence * 0.6) + (cnn_confidence_pct * 0.4)
 
-    logger.info(
+    logger.debug(
         f"CNN={cnn_label}({cnn_conf:.2f}) "
-        f"HF1={hf1_label} HF2={hf2_label} "
         f"Votes ai={ai_votes} real={real_votes}/{total_weight} "
         f"→ {final_label} ({final_confidence:.1f}%)"
     )