Add

app.py

@@ -165,7 +165,8 @@ def predict():
 
             with torch.no_grad():
                 out = model(tensor)
-                probs = torch.exp(out).cpu().numpy()[0]
+                probs = torch.softmax(out, dim=1).cpu().numpy()[0]
+                #probs = torch.exp(out).cpu().numpy()[0]
 
         elif framework == "tensorflow":
             model = load_tensorflow()
@@ -182,9 +183,10 @@ def predict():
         pred_idx = int(np.argmax(probs))
         return jsonify({
             "class": CLASSES[pred_idx],
-            "confidence": float(probs[pred_idx]),
+            #"confidence": float(probs[pred_idx]),
+            "confidence": float(probs[pred_idx] * 100),
             "probabilities": {
-                c: float(p) for c, p in zip(CLASSES, probs)
+                c: float(p * 100) for c, p in zip(CLASSES, probs)
             },
         })