https://huggingface.co/spaces/Saad123/minima

app.py

@@ -2,6 +2,7 @@ import gradio as gr
 import numpy as np
 import tensorflow as tf
 import tensorflow_hub as hub
+import time
 
 loaded_model = tf.keras.models.load_model(
        ('CatDogmodel.h5'),
@@ -9,16 +10,20 @@ loaded_model = tf.keras.models.load_model(
 )
 
 def model(image):
+    
     im_scaled = image/255
     im_reshape = np.reshape(im_scaled,[1,224,224,3])
+    start = time.time()
     pred = loaded_model.predict(im_reshape)
+    end=time.time()
+    t = start-end
     cat_pred = pred
     dog_pred = 1-pred
     pred_label = np.argmax(pred)
     if (pred_label == 0):
-        return f"The Image is of a Dog."
+        return "The Image is of a Dog."+"Accuracy:" +dog_pred[0]+"Time:"+t
     if (pred_label == 1):
-        return "The Image is of a Cat."
+        return "The Image is of a Cat."+"Accuracy:" +cat_pred[1]+"Time"+t
 
 image = gr.inputs.Image(shape=(224,224))
 background='body{background-image:url("https://d2gg9evh47fn9z.cloudfront.net/800px_COLOURBOX35440124.jpg");}'

requirements.txt

@@ -5,3 +5,4 @@ tensorflow_hub==0.12.0
 matplotlib==3.5.1
 opencv_python==4.6.0.66
 Pillow==9.2.0
+time