grad cam retet

neural_network_model/transfer_learning.py

@@ -1139,11 +1139,11 @@ def predict_image_patch_classes(self, **kwargs):
  # transfer_model.plot_classes_number()
  # transfer_model.analyze_image_names()
  # transfer_model.plot_data_images(num_rows=3, num_cols=3, cmap="jet")
- # transfer_model.train_model(
- #  epochs=1,
- #  model_save_path=(Path(__file__).parent / ".." / "deep_model").resolve(),
- #  model_name="tf_model_core_1.h5",
- # )
+ transfer_model.train_model(
+ epochs=1,
+ model_save_path=(Path(__file__).parent / ".." / "deep_model").resolve(),
+ model_name="tf_model_core_1.h5",
+ )
  # transfer_model.plot_metrics_results()
  # transfer_model.results()
  # one can pass the model address to the predict_test method
@@ -1153,27 +1153,21 @@ def predict_image_patch_classes(self, **kwargs):
  # "MildDemented": "Mild",
  # "VeryMildDemented": "Very Mild",
  # }
- # transfer_model.predict_test(
- # model_path=(
- # Path(__file__).parent / ".." / "deep_model" / "tf_model_core_1.h5"
- # ).resolve(),
- # rotation=90,
- # y_axis_label_size=12,
- # x_axis_label_size=12,
- # title_size=14,
- # fig_title="Original Confusion Matrix",
- # conf_matx_font_size=12,
- # # custom_titles=custom_titles,
- # cmap="winter",
- # normalize="true",
- # )
- transfer_model.grad_cam_viz(
- num_rows=3,
- num_cols=2,
- model_path=Path(__file__).parent / ".." / "deep_model" / "tf_model_core_1.h5",
- test_dataset_address=Path(__file__).parent / ".." / "dataset_core" / "patch_images",
- save_path=Path(__file__).parent / ".." / "figures" / "grad_cam.png",
+ transfer_model.predict_test(
+ model_path=(
+ Path(__file__).parent / ".." / "deep_model" / "tf_model_core_1.h5"
+ ).resolve(),
+ rotation=90,
+ y_axis_label_size=12,
+ x_axis_label_size=12,
+ title_size=14,
+ fig_title="Original Confusion Matrix",
+ conf_matx_font_size=12,
+ # custom_titles=custom_titles,
+ cmap="winter",
+ normalize="true",
  )
+ transfer_model.grad_cam_viz(num_rows=3, num_cols=2)
 
  # transfer_model.predict_one_image(
  # img_path=str(