Add preprocess_input for resnet50

app.py

@@ -1,5 +1,6 @@
 import gradio as gr
 import pathlib
+import tensorflow as tf
 
 current_dir = pathlib.Path(__file__).parent
 
@@ -68,6 +69,7 @@ def classify_image(inp):
   inp =resize(inp, (300, 300, 3))
   inp = inp.reshape((-1, 300, 300, 3))
   # inp = tf.keras.applications.mobilenet_v2.preprocess_input(inp)
+  inp = tf.keras.applications.resnet50.preprocess_input(inp)
   prediction = oc_resnet50_model2.predict(inp).flatten()
   confidences = {labels[i]: float(prediction[i]) for i in range(2)}
   return confidences