Create app.py

app.py

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+import gradio as gr
+from keras.models import load_model
+import cv2
+import numpy as np
+model = load_model('covid_trained_model.h5')
+def sigmoid_to_binary(output_value, threshold=0.705):
+    if output_value >= threshold:
+        return 1
+    else:
+        return 0
+def covid(img):
+    resized_image = cv2.resize(img, (224, 224))
+    reshaped_image = np.expand_dims(resized_image, axis=0)
+    pred = model.predict(reshaped_image)
+    binary = sigmoid_to_binary(pred[0,0])
+    if(binary == 0):
+        return "COVID POSITIVE +"
+    return "COVID NEGATIVE -"
+gr.Interface(fn=covid,inputs="image",outputs="text",title="Covid19 Detector by CHEST X-Ray",description="Please upload your CHEST X-RAY in below input field").launch()