commit

app.py

@@ -1,7 +1,6 @@
 import tensorflow as tf
 from tensorflow.keras.models import load_model
 import streamlit as st
-import cv2
 from PIL import Image
 import numpy as np
 
@@ -10,11 +9,12 @@ model = load_model('model.h5')
 
 def run():
     upload = st.file_uploader("Please upload an image", type=["jpg", "png"])
-    img =  cv2.imread('test.png')
-    image_fromarray = Image.fromarray(img, 'RGB')
-    resize_image = image_fromarray.resize((32, 32))
-    X_inf = np.array(resize_image)
-    X_inf = X_inf/255
+    img =  Image.open(upload)
+    resize_image = img.resize((32, 32))
+    X = np.array(resize_image)
+    X = X/255
+    X_inf = np.expand_dims(X, axis=0)
+    X_inf.shape
 
     inf_pred = model.predict(X_inf)
     inf_class =np.argmax(inf_pred,axis=1)

requirements.txt

@@ -1,4 +1,3 @@
 streamlit
 tensorflow
-cv2
 numpy