Upload Gradio.py

Gradio.py

@@ -9,21 +9,21 @@ model_directory = '/Users/keremoktay/Desktop/Gradio/'
 
 # Load the decision tree and KNN models
 dt_models = {
-    "2": pickle.load(open(model_directory + 'dt2.pkl', 'rb')),
-    "3": pickle.load(open(model_directory + 'dt3.pkl', 'rb')),
-    "5": pickle.load(open(model_directory + 'dt5.pkl', 'rb'))
+    "2": pickle.load(open('dt2.pkl', 'rb')),
+    "3": pickle.load(open('dt3.pkl', 'rb')),
+    "5": pickle.load(open('dt5.pkl', 'rb'))
 }
 knn_models = {
-    "1": pickle.load(open(model_directory + 'knn1.pkl', 'rb')),
-    "3": pickle.load(open(model_directory + 'knn3.pkl', 'rb')),
-    "5": pickle.load(open(model_directory + 'knn5.pkl', 'rb'))
+    "1": pickle.load(open('knn1.pkl', 'rb')),
+    "3": pickle.load(open('knn3.pkl', 'rb')),
+    "5": pickle.load(open('knn5.pkl', 'rb'))
 }
 
 # Load the neural network models
 nn_models = {
-    "1": load_model(model_directory + 'cnn_1layer.h5'),
-    "2": load_model(model_directory + 'cnn_2layer.h5'),
-    "3": load_model(model_directory + 'cnn_3layer.h5')
+    "1": load_model('cnn_1layer.h5'),
+    "2": load_model('cnn_2layer.h5'),
+    "3": load_model('cnn_3layer.h5')
 }
 
 def preprocess_image_for_ml(image_path):