Improve interactive launch

src/napari_easy_augment_batch_dl/interactive_launch.py

@@ -1,18 +1,46 @@
+# note have to import napari first and show the viewer
+# otherwise on Linux I get an error if I show the viewer after
+# importing Cellpose
 import napari
 viewer = napari.Viewer()
 
 import os
 from napari_easy_augment_batch_dl import easy_augment_batch_dl
-from napari_easy_augment_batch_dl.deep_learning_project import DLModel
 
-batch_dl = easy_augment_batch_dl.NapariEasyAugmentBatchDL(viewer)
+# import the frameworks you want to use.  As part of the import the framework wil be registered
+# if it calls the BaseFramework.register_framework() method
+try:
+    from napari_easy_augment_batch_dl.frameworks.pytorch_semantic_framework import PytorchSemanticFramework
+except:
+    print('PytorchSemanticFramework not loaded')
+try:
+    from napari_easy_augment_batch_dl.frameworks.cellpose_instance_framework import CellPoseInstanceFramework
+except:
+    print('CellPoseInstanceFramework not loaded')
+try:
+    from napari_easy_augment_batch_dl.frameworks.stardist_instance_framework import StardistInstanceFramework
+except:
+    print('StardistInstanceFramework not loaded')
+
+# create the napari-easy-augment-batch-dl widget, we pass import_all_frameworks=False because
+# we already imported the frameworks we want to use
+batch_dl = easy_augment_batch_dl.NapariEasyAugmentBatchDL(viewer, import_all_frameworks=False)
 
 viewer.window.add_dock_widget(
     batch_dl
 )
 
+# here we list directories for image sets we have been experimenting with
+# need to point the parent_path to a directory with the 2D image set we want to work with
+
 #test_dataset = "Roots" # "DAPI Cellpse"
-test_dataset = "None"
+#test_dataset = "None"
+test_dataset = "particles"
+#test_dataset = "grains_cellpose"
+#test_dataset = "DAPI Cellpose"
+#test_dataset = "Bees"
+#test_dataset = "grains_semantic"
+#test_dataset = "custom"
 
 #parent_path = os.path.join(r'D:\images\tnia-python-images\imagesc\2024_08_21_spheroids\yolo_omero_dataset\subset1')
 
@@ -22,40 +50,67 @@
     parent_path =r'D:\images\tnia-python-images\imagesc\2024_08_19_Dapi_CJ'
 elif test_dataset == "Bees":
     parent_path =r'C:\Users\bnort\work\ImageJ2022\tnia\gpu-image-analysis-deep-learning\data\ab_bees'
+    parent_path = r'/home/bnorthan/images/tnia-python-images/imagesc/2024_08_27_bees_sparse/'
 elif test_dataset == "Ladybugs":
     parent_path = r"C:\Users\bnort\work\ImageJ2022\tnia\gpu-image-analysis-deep-learning\data\aa_lady_bugs_fresh"
     parent_path = r'D:\images\tnia-python-images\imagesc\2024_10_03_cellpose_ladybugs'
 elif test_dataset == "Vesicles":
     parent_path =r'D:\images\tnia-python-images\tg\2024-09-26-vesicles'
 elif test_dataset == "multi_uclear":
     parent_path = r'D:\images\tnia-python-images\imagesc\2024_10_07_cellpose_multi_nuclear'
+elif test_dataset == "spindle":
+    parent_path = r'D:\images\tnia-python-images\imagesc\2024_10_09_spindle_shaped_cells'
+elif test_dataset == "thin_section":
+    parent_path =r'D:\images\tnia-python-images\\imagesc\\2024_10_17_thin_section'
+elif test_dataset == "ladybugs":
+    data_path = r'C:\Users\bnort\work\ImageJ2022\tnia\notebooks-and-napari-widgets-for-dl\data'
+    parent_path = os.path.join(data_path, 'ladybugs1')
+elif test_dataset == "particles":
+    parent_path = r'/home/bnorthan/besttestset/images/Semantic_Sparse/'
+elif test_dataset == "grains_cellpose":
+    parent_path = r'/home/bnorthan/images/tnia-python-images/imagesc/2024_12_19_sem_grain_size_revisit2'
+elif test_dataset == "grains_semantic":
+    parent_path = r'/home/bnorthan/images/tnia-python-images/imagesc/2024_12_19_sem_grain_size_revisit/'
+elif test_dataset == "particles2":
+    parent_path = r'/home/bnorthan/besttestset/images/training14/'
+else:
+    parent_path = r'/home/bnorthan/images/tnia-python-images/imagesc/2024_12_19_sem_grain_size_revisit3'
 
-parent_path = r'D:\images\tnia-python-images\imagesc\2024_10_09_spindle_shaped_cells'
-parent_path =r'D:\images\tnia-python-images\\imagesc\\2024_10_17_thin_section'
-
-data_path = r'C:\Users\bnort\work\ImageJ2022\tnia\notebooks-and-napari-widgets-for-dl\data'
-parent_path = os.path.join(data_path, 'ladybugs1')
+model_path = os.path.join(parent_path, r'models')
 
 batch_dl.load_image_directory(parent_path)
 
 # load the model that goes with the test
 try:
 
     if test_dataset == "Roots":
-        model_path = os.path.join(parent_path, r'models')
-        model_name =  'model1' # None
-        batch_dl.deep_learning_project.set_pretrained_model(os.path.join(model_path, model_name), DLModel.UNET)
-        batch_dl.network_architecture_drop_down.setCurrentText(DLModel.UNET)
+        model_name =  None #'model1' 
+        batch_dl.network_architecture_drop_down.setCurrentText(PytorchSemanticFramework.descriptor)
     elif test_dataset == "DAPI Cellpose":
-        model_path = os.path.join(parent_path, r'models\models\cellpose_testing')
-        batch_dl.deep_learning_project.set_pretrained_model(model_path, DLModel.CELLPOSE)
-        batch_dl.network_architecture_drop_down.setCurrentText(DLModel.CELLPOSE)
+        model_name = os.path.join(parent_path, r'models\models\cellpose_testing')
+        batch_dl.network_architecture_drop_down.setCurrentText(CellPoseInstanceFramework.descriptor)
+        widget = batch_dl.deep_learning_widgets[CellPoseInstanceFramework.descriptor]
+        widget.load_model_from_path(model_name)
     elif test_dataset == "Bees":
-        model_path = os.path.join(parent_path, r'models')
-        model_name = os.path.join(model_path, 'beetestmodel')
-        #batch_dl.deep_learning_project.set_pretrained_model(model_name, DLModel.STARDIST)
-        batch_dl.set_pretrained_model(model_name, "Stardist Model")
-        batch_dl.network_architecture_drop_down.setCurrentText(DLModel.STARDIST)
+        model_name = os.path.join(model_path, 'model1')
+        batch_dl.network_architecture_drop_down.setCurrentText(StardistInstanceFramework.descriptor)
+        widget = batch_dl.dSeep_learning_widgets[StardistInstanceFramework.descriptor]
+        widget.load_model_from_path(model_name)
+    elif test_dataset == "particles":
+        model_name = 'ok.pth'
+        widget = batch_dl.deep_learning_widgets[PytorchSemanticFramework.descriptor]
+        widget.load_model_from_path(os.path.join(model_path, model_name))
+    elif test_dataset == "grains cellpose":
+        model_name = "cellpose_20241219_090937"
+        batch_dl.network_architecture_drop_down.setCurrentText(CellPoseInstanceFramework.descriptor)
+        widget = batch_dl.deep_learning_widgets[CellPoseInstanceFramework.descriptor]
+        widget.load_model_from_path(os.path.join(model_path, model_name))
+    elif test_dataset == 'grains_semantic':
+        model_name = 'semantic_20250130_200224.pth'
+        batch_dl.network_architecture_drop_down.setCurrentText(PytorchSemanticFramework.descriptor)
+        widget = batch_dl.deep_learning_widgets[PytorchSemanticFramework.descriptor]
+        widget.load_model_from_path(os.path.join(model_path, model_name))
+
 except Exception as e:
     print('Exception occurred when loading model ', e)