Update app.py

app.py

@@ -53,25 +53,14 @@ def preprocess(img: np.ndarray) -> np.ndarray:
 def predict(img: np.ndarray):
     x = preprocess(img)
     raw = float(model.predict(x, verbose=0)[0, 0])
-
-    # DEBUG: print raw score to logs
     print("Raw model output:", raw, flush=True)
 
-    # OPTION A (current assumption): model outputs P(MLBT)
-    prob_mlbt_A = raw
-    prob_mmat_A = 1.0 - raw
-
-    # OPTION B (flipped): model outputs P(MMAT)
-    prob_mmat_B = raw
-    prob_mlbt_B = 1.0 - raw
-
-    # For now, return both sets so you can see what's going on
-    return {
-        "MLBT (assume raw=P(MLBT))": prob_mlbt_A,
-        "MMAT (assume raw=P(MLBT))": prob_mmat_A,
-        "MLBT (assume raw=P(MMAT))": prob_mlbt_B,
-        "MMAT (assume raw=P(MMAT))": prob_mmat_B,
-    }
+    # raw ≈ P(MMAT)
+    prob_mmat = raw
+    prob_mlbt = 1.0 - prob_mmat
+
+    return {"MLBT": prob_mlbt, "MMAT": prob_mmat}
+