From d740d32560d0502ca81568901e3ff567db10b061 Mon Sep 17 00:00:00 2001
From: atashne <atashnezhad1@gmail.com>
Date: Thu, 22 Jun 2023 16:03:13 -0500
Subject: [PATCH] edit test

---
 tests/test_run.py | 77 +++++++++++++++--------------------------------
 1 file changed, 24 insertions(+), 53 deletions(-)

diff --git a/tests/test_run.py b/tests/test_run.py
index 71ffd53..b5a8e4e 100644
--- a/tests/test_run.py
+++ b/tests/test_run.py
@@ -9,86 +9,57 @@
 main_dir = current_dir.parent
 # Add the main directory to the Python path
 sys.path.append(str(main_dir))
-# skip this test TODO: fix this test later
-import pytest
 
+import pytest
 from neural_network_model.bit_vision import BitVision
 from neural_network_model.process_data import Preprocessing
 
 
-@pytest.mark.skip(reason="no way of currently testing this")
+# @pytest.mark.skip(reason="no way of currently testing this")
 def test_run():
-    # check if a dir name test_resources exists if not create one
-    if not os.path.exists(Path(__file__).parent / "test_resources"):
-        os.mkdir(Path(__file__).parent / "test_resources")
-
     # download the images
-    obj = Preprocessing(
-        dataset_address=Path(__file__).parent / "test_resources" / "dataset"
-    )
+    obj = Preprocessing(dataset_address=Path(__file__).parent / "dataset")
     obj.download_images(limit=10)
     print(obj.image_dict)
     obj.augment_data(
         number_of_images_tobe_gen=10,
-        augment_data_address=Path(__file__).parent
-        / "test_resources"
-        / "augmented_dataset",
+        augment_data_address=Path(__file__).parent / "augmented_dataset"
     )
     obj.train_test_split(
-        augmented_data_address=Path(__file__).parent
-        / "test_resources"
-        / "augmented_dataset",
-        train_test_val_split_dir_address=Path(__file__).parent
-        / "test_resources"
-        / "dataset_train_test_val",
+        augmented_data_address=Path(__file__).parent / "augmented_dataset",
+        train_test_val_split_dir_address=Path(__file__).parent / "dataset_train_test_val"
     )
 
-    obj = BitVision(
-        train_test_val_dir=Path(__file__).parent
-        / "test_resources"
-        / "dataset_train_test_val"
-    )
+    obj = BitVision(train_test_val_dir=Path(__file__).parent / "dataset_train_test_val")
     print(obj.categories)
     print(obj.data_details)
     obj.plot_image_category()
     obj.compile_model()
-
+    #
     model_name = "model_epoch_{epoch:02d}_loss_{loss:.2f}_acc_{accuracy:.2f}_val_acc_{val_accuracy:.2f}_.h5"
     obj.train_model(
-        model_save_address=Path(__file__).parent / "test_resources" / "deep_model",
-        model_name=model_name,
-        epochs=10,
-    )
-    obj.plot_history(
-        fig_folder_address=Path(__file__).parent / "test_resources" / "figures"
+        epochs=8,
+        model_save_address=Path(__file__).parent / "deep_model",
+        model_name=model_name
     )
+    obj.plot_history(fig_folder_address=Path(__file__).parent / "figures")
+
+    best_model = obj.return_best_model_name(directory="deep_model")
 
     obj.predict(
-        fig_save_address=Path(__file__).parent / "test_resources" / "figures",
-        model_path=Path(__file__).parent / "test_resources" / "deep_model" / model_name,
-        test_folder_address=Path(__file__).parent
-        / "test_resources"
-        / "dataset_train_test_val"
-        / "test",
+        fig_save_address=Path(__file__).parent / "figures",
+        model_path=Path(__file__).parent / "deep_model" / best_model,
+        test_folder_address=Path(__file__).parent / "dataset_train_test_val" / "test"
     )
 
     # find list of images in the Path(__file__).parent / "dataset_train_test_val" / "test" / "pdc_bit"
-    directory_path = (
-        Path(__file__).parent
-        / "test_resources"
-        / "dataset_train_test_val"
-        / "test"
-        / "pdc_bit"
-    )
+    directory_path = Path(__file__).parent / "dataset_train_test_val" / "test" / "pdc_bit"
     list_of_images = [str(x) for x in directory_path.glob("*.jpeg")]
+
     obj.grad_cam_viz(
-        model_path=Path(__file__).parent / "test_resources" / "deep_model" / model_name,
-        fig_to_save_address=Path(__file__).parent / "test_resources" / "figures",
-        img_to_be_applied_path=Path(__file__).parent
-        / "test_resources"
-        / "dataset_train_test_val"
-        / "test"
-        / "pdc_bit"
-        / list_of_images[0],
-        output_gradcam_fig_name="gradcam.png",
+        model_path=Path(__file__).parent / "deep_model" / best_model,
+        fig_to_save_address=Path(__file__).parent / "figures",
+        img_to_be_applied_path=Path(__file__).parent / "dataset_train_test_val" / "test" / "pdc_bit" / list_of_images[
+            0],
+        output_gradcam_fig_name="gradcam.png"
     )