new script for ep05

episodes/scripts/predict.py

@@ -0,0 +1,24 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Thu Jun 15 16:27:34 2023
+
+@author: jc140298
+"""
+
+from tensorflow.keras.utils import load_img
+from tensorflow.keras.utils import img_to_array
+
+# load a new image and prepare it to match cifar10 dataset
+new_img_pil = load_img("01_Jabiru_TGS.JPG", target_size=(32,32)) # Image format
+new_img_arr = img_to_array(new_img_pil) # convert to array for analysis
+new_img_reshape = new_img_arr.reshape(1, 32, 32, 3) # reshape into single sample
+new_img_float =  new_img_reshape.astype('float64') / 255.0 # normalize
+
+# predict the classname
+result = model.predict(new_img_float) # make prediction
+print(result) # probability for each class
+print(class_names[result.argmax()]) # class with highest probability
+
+
+# test set
+y_pred = model.predict(test_images)