keras prediction functions now works both with model path and model object

cccaaannn · cccaaannn · commit 8f429e0216ac · 2020-05-27T18:22:22.000+03:00
diff --git a/README.md b/README.md
@@ -48,7 +48,6 @@ from  imagepreprocessing.utilities import create_confusion_matrix, train_test_sp
 
 images_path = "deep_learning/test_images/food2"
 save_path = "food"
-model_path = "deep_learning/saved_models/alexnet.h5"
 
 # Create training data split the data
 x, y, x_val, y_val = create_training_data_keras(images_path, save_path = save_path, validation_split=0.2, percent_to_use=0.5)
@@ -63,7 +62,7 @@ x, y, test_x, test_y =  train_test_split(x,y,save_path = save_path)
 class_names = ["apple", "melon", "orange"]
 
 # make prediction
-predictions = make_prediction_from_array_keras(test_x, model_path, print_output=False)
+predictions = make_prediction_from_array_keras(test_x, model, print_output=False)
 
 # create confusion matrix
 create_confusion_matrix(predictions, test_y, class_names=class_names, one_hot=True)
diff --git a/imagepreprocessing/keras_functions.py b/imagepreprocessing/keras_functions.py
@@ -265,13 +265,13 @@ def create_training_data_keras(source_path, save_path = None, image_size = (224,
         return x, y
 
 
-def make_prediction_from_directory_keras(images_path, keras_model_path, image_size = (224,224), print_output=True, model_summary=True, show_images=False, grayscale = False, files_to_exclude = [".DS_Store",""]):
+def make_prediction_from_directory_keras(images_path, keras_model, image_size = (224,224), print_output=True, model_summary=True, show_images=False, grayscale = False, files_to_exclude = [".DS_Store",""]):
     """
     Reads test data from directory resizes it and makes prediction with using a keras model
 
     # Arguments:
         images_path: source path of the test images see input format
-        keras_model_path: path of the keras model 
+        keras_model: a keras model object or path of the model 
         img_size (224): size of the images for resizing
         print_output (True): prints output
         model_summary (True): shows keras model summary 
@@ -323,8 +323,11 @@ def make_prediction_from_directory_keras(images_path, keras_model_path, image_si
         if exclude in images: 
             images.remove(exclude)
 
-    # load model
-    model = keras.models.load_model(keras_model_path)
+    # prepare model
+    if(isinstance(keras_model, keras.Model)):
+        model = keras_model
+    else:
+        model = keras.models.load_model(keras_model)
 
     # get all images
     for image in images:
@@ -367,13 +370,13 @@ def make_prediction_from_directory_keras(images_path, keras_model_path, image_si
     return predictions
 
 
-def make_prediction_from_array_keras(test_x, keras_model_path, print_output=True, model_summary=True, show_images=False):
+def make_prediction_from_array_keras(test_x, keras_model, print_output=True, model_summary=True, show_images=False):
     """
     makes prediction with using a keras model
 
     # Arguments:
         test_x: numpy array of images
-        keras_model_path: path of the keras model
+        keras_model: a keras model object or path of the model
         print_output (True): prints output
         model_summary (True): shows keras model summary 
         show_images (False): shows the predicted image
@@ -392,8 +395,11 @@ def make_prediction_from_array_keras(test_x, keras_model_path, print_output=True
     import keras
     import cv2
 
-    # load model
-    model = keras.models.load_model(keras_model_path)
+    # prepare model
+    if(isinstance(keras_model, keras.Model)):
+        model = keras_model
+    else:
+        model = keras.models.load_model(keras_model)
 
     # show model summary
     if(model_summary):
diff --git a/setup.py b/setup.py
@@ -5,7 +5,7 @@
 
 setuptools.setup(
     name="imagepreprocessing",
-    version="1.4.1",
+    version="1.5.0",
     author="Can Kurt",
     author_email="can.kurt.aa@gmail.com",
     description="image preprocessing",
