Merge branch 'cy/layer-inference' of https://github.com/AdaptiveMotorControlLab/CellSeg3d into cy/layer-inference

Author: C-Achard

napari_cellseg3d/model_workers.py

@@ -233,6 +233,10 @@ def __init__(
         self.window_infer_size = window_infer_size
         self.keep_on_cpu = keep_on_cpu
         self.stats_to_csv = stats_csv
+        ############################################
+        ############################################
+        self.layer = layer
+        self.images_filepaths = images_filepaths
 
         ############################################
         ############################################
@@ -360,8 +364,10 @@ def load_layer(self):
         dims_check = volume.shape
         self.log("\nChecking dimensions...")
         pad = utils.get_padding_dim(dims_check)
+
         # print(volume.shape)
         # print(volume.dtype)
+
         load_transforms = Compose(
             [
                 ToTensor(),
@@ -532,11 +538,14 @@ def inference_on_list(self, inf_data, i, model, post_process_transforms):
 
     def stats_csv(self, instance_labels):
         if self.stats_to_csv:
+
             # try:
+
             data_dict = volume_stats(
                 instance_labels
             )  # TODO test with area mesh function
             return data_dict
+
         # except ValueError as e:
         #     self.log(f"Error occurred during stats computing : {e}")
         #     return None
@@ -679,6 +688,7 @@ def inference(self):
         if self.model_dict["name"] == "SegResNet":
             model = self.model_dict["class"].get_net()(
                 input_image_size=[
+
                     dims,
                     dims,
                     dims,

napari_cellseg3d/plugin_model_inference.py

@@ -219,10 +219,12 @@ def __init__(self, viewer: "napari.viewer.Viewer"):
             "Image size on which the SegResNet has been trained (default : 128)"
         )
 
+
         thresh_desc = (
             "Thresholding : all values in the image below the chosen probability"
             " threshold will be set to 0, and all others to 1."
         )
+
         self.thresholding_checkbox.setToolTip(thresh_desc)
         self.thresholding_count.setToolTip(thresh_desc)
         self.window_infer_box.setToolTip(
@@ -634,6 +636,7 @@ def start(self, on_layer=False):
 
             self.worker.set_download_log(self.log)
 
+
             yield_connect_show_res = lambda data: self.on_yield(
                 data,
                 widget=self,