Update app.py

app.py

@@ -1,4 +1,3 @@
-import cv2
 import tensorflow as tf
 import gradio as gr
 
@@ -22,9 +21,7 @@ loaded_model2.load_weights("wrinkl.h5")
 
 def classifier(Imgarr):
     l = []
-    #img1 = cv2.imread(Imgarr)
-    img = cv2.resize(Imgarr,(50,50))
-    img = img.reshape(-1, 50, 50, 3)
+    img = Imgarr.reshape(-1, 50, 50, 3)
     result = loaded_model.predict(img)
     result = result[0]
     if result[0] >= result[1]:
@@ -45,10 +42,11 @@ def classifier(Imgarr):
         l.append("no wrinkles on face")
     else:
         l.append("wrinkles on face")
-    return l
+
+    return "The Predictions are " + str(l)
 
 interface = gr.Interface(classifier,gr.inputs.Image(shape=(50,50)),outputs = "text",
-                          description="Classifier of images of daisy plants, dandelion, roses, sunflowers, and tulips",
-                          title="Flower Image Classifier",
-                          examples=[['42.jpg'],['56.jpg']])
+                          description="Classifier of Aging Signs of Images",
+                          title="Aging Signs Classifier",
+                          examples=[['42.jpg'],['56.jpg'],['64.jpg']])
 interface.launch()