Update app.py

app.py

@@ -25,21 +25,17 @@ This Space demonstrates model based on efficientnet base model.
 
 The model is trained using [anasmohammedtahir/covidqu](https://www.kaggle.com/datasets/anasmohammedtahir/covidqu) dataset
 """
+article="<p style='text-align: center'><a href='https://www.kaggle.com/datasets/anasmohammedtahir/covidqu' target='_blank'>COVID-QU-Ex Dataset</a></p>"
 examples = [
-    ['Xray Image','covid/covid_1038.png', 'Covid']
-    #["Covid Xray Image 2","covid/covid_1034.png"], 
-    #["Covid Xray Image 3","covid/cd.png"], 
-    #["Covid Xray Image 4","covid/covid_1021.png"], 
-    #["Covid Xray Image 5","covid/covid_1027.png"], 
-    #["Covid Xray Image 6","covid/covid_1042.png"], 
-    #["Covid Xray Image 7","covid/covid_1031.png"]
+    ['covid/covid_1038.png'], ['covid/covid_1034.png'], 
+    ['covid/cd.png'], ['covid/covid_1021.png'], 
+    ['covid/covid_1027.png'], ['covid/covid_1042.png'], 
+    ['covid/covid_1031.png']
 ]
-article="<p style='text-align: center'><a href='https://www.kaggle.com/datasets/anasmohammedtahir/covidqu' target='_blank'>COVID-QU-Ex Dataset</a></p>"
+
 interpretation="default"
-num_shap=5
 enable_queue=True
 
-
 gr.Interface(fn=predict_image, inputs=gr.Image(shape=(224,224)),
              outputs = gr.Label(num_top_classes=3),title=title,description=description,examples=examples, article=article, interpretation=interpretation,enable_queue=enable_queue).launch(share=False)