Create app.py

app.py

@@ -0,0 +1,25 @@
+import gradio as gr
+import tensorflow as tf
+import cv2
+
+title = "Covid 19 Prediction App using X-ray Images"
+
+head = (
+  "<center>"
+  "Upload an X-ray image to check for covid19. The app is for research purposes and not clinically authorized"
+  "</center>"
+)
+
+
+cnn = tf.keras.models.load_model("cnn_model.h5")
+
+def predict_input_image(img):
+    img = img.reshape(1, 500, 500, 1)
+    prediction = cnn.predict(img).tolist()[0]
+    class_names = ["Covid"]
+    return {class_names[i]: 1-prediction[i] for i in range(1)}
+
+image = gr.inputs.Image(shape=(500, 500), image_mode='L', invert_colors=False, source="upload")
+label = gr.outputs.Label()
+iface = gr.Interface(fn=predict_input_image, inputs=image, outputs=label,title=title, description=head)
+iface.launch()