Update app.py

app.py

@@ -37,23 +37,23 @@ print("Model Vocabulary:", learn.dls.vocab)
 
 labels = learn.dls.vocab
 
-# def predict(img):
-#     img = PILImage.create(img)
-#     pred,pred_idx,probs = learn.predict(img)
-#     return {labels[i]: float(probs[i]) for i in range(len(labels))}
+def predict(img):
+    img = PILImage.create(img)
+    pred,pred_idx,probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
 
 
 
-def predict(img):
-    img = PILImage.create(img)
-    pred, pred_idx, probs = learn.predict(img)
-    results = {labels[i]: float(probs[i]) for i in range(len(labels))}
-    # Adjust results to highlight when 'Survived' meets the 75% threshold
-    if results['Survived'] <= 0.1:
-        results['Survived'] = 1.0  # Indicating high confidence of survival
-    else:
-        results['Survived'] = 0.0  # Indicating it did not meet the threshold
-    return results
+# def predict(img):
+#     img = PILImage.create(img)
+#     pred, pred_idx, probs = learn.predict(img)
+#     results = {labels[i]: float(probs[i]) for i in range(len(labels))}
+#     # Adjust results to highlight when 'Survived' meets the 75% threshold
+#     if results['Survived'] <= 0.1:
+#         results['Survived'] = 1.0  # Indicating high confidence of survival
+#     else:
+#         results['Survived'] = 0.0  # Indicating it did not meet the threshold
+#     return results
 
 
 # def predict(img):