Update utils/predict.py

utils/predict.py

@@ -68,9 +68,9 @@ def predict_batch(image_path):
 
             prob_list = slice_pred[i].numpy().flatten().tolist()
             sorted_prob = np.argsort(slice_pred[i])[::-1].flatten()
-            prob_scores = {"image": "image "+ str(j), "first": f"probability of {class_vocab[sorted_prob[0]]} is {round(prob_list[sorted_prob[0]] * 100,2)} %", 
-            "second": f"probability of {class_vocab[sorted_prob[1]]} is {round(prob_list[sorted_prob[1]] * 100,2)} %", 
-            "third": f"probability of {class_vocab[sorted_prob[2]]} is {round(prob_list[sorted_prob[2]] * 100,2)} %"}
+            prob_scores = {"image": "image "+ str(j), "first": f"predicted {class_vocab[sorted_prob[0]]} with {round(prob_list[sorted_prob[0]] * 100,2)}% confidence", 
+            "second": f"predicted {class_vocab[sorted_prob[1]]} is {round(prob_list[sorted_prob[1]] * 100,2)}% confidence", 
+            "third": f"predicted {class_vocab[sorted_prob[2]]} is {round(prob_list[sorted_prob[2]] * 100,2)}% confidence"}
             predictions_df = predictions_df.append(prob_scores,ignore_index=True)
             
             plt.title(f"image {j} : {class_vocab[output]}")