Update app.py

Added Html text

app.py

@@ -11,7 +11,15 @@ def predict_image(get_image):
    pred, idx, probs = learn.predict(get_image)
    return dict(zip(categories, map(float, probs)))
 
-title = "Detect COVID_19 Infection Xray Chest Images"
+title = "COVID_19 Infection Detectation App!"
+
+head = (
+  "<center>"
+  "<img src='covid/cd.png' width=400>"
+  "The robot was trained to classify chest xray image. To test it, Use the Example Images Provided or Upload your own xray images the space provided."
+  "</center>"
+)
+
 description = """
 This Space demonstrates model based on efficientnet base model. 
 
@@ -27,25 +35,11 @@ examples = [
     #["Covid Xray Image 7","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="shap"
+interpretation="default"
 num_shap=5
 enable_queue=True
 
 
-gr.Interface(fn=predict_image, 
-             inputs=[gr.Image(shape=(224,224)),
-                     gr.inputs.Textbox(
-                        label="Target Text",
-                        lines=1),
-                    gr.inputs.Image(
-                        label='Input Image'),
-                    gr.inputs.Textbox(
-                        label="Class Type")
-                    ],
-             outputs = gr.Label(num_top_classes=3),
-             title=title,description=description,
-             examples=examples, 
-             article=article, 
-             interpretation=interpretation,
-             enable_queue=enable_queue).launch(share=False)
+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)