Label and Predict

This notebook uses the napari-easy-augment-batch-dl widget to explore and label the data. If we have a model trained we can also predict using that model.

import os
import numpy as np
import napari
from napari_easy_augment_batch_dl import easy_augment_batch_dl

try:
    from napari_easy_augment_batch_dl.frameworks.cellpose_instance_framework import CellPoseInstanceFramework
except:
    print('CellPoseInstanceFramework not loaded')

viewer = napari.Viewer()

batch_dl = easy_augment_batch_dl.NapariEasyAugmentBatchDL(viewer, label_only = False)

viewer.window.add_dock_widget(
    batch_dl
)

data_path = r'../../data'
parent_path = os.path.join(data_path, 'ladybugs_series')
model_path = os.path.join(parent_path, 'models')

model_name = 'cellpose_ladybugs_scale2'
#mod = models.Cellpose(gpu=True, model_type="cyto3")
model_type = "CellPose Instance Model"
batch_dl.load_image_directory(parent_path)


if model_name is not None:

    # set the drop down to the CellPoseInstanceFramework
    batch_dl.network_architecture_drop_down.setCurrentText(CellPoseInstanceFramework.descriptor)
    
    # get the cellpose widget
    widget = batch_dl.deep_learning_widgets[CellPoseInstanceFramework.descriptor]

    # load model
    widget.load_model_from_path(os.path.join(model_path, model_name))

   # get the framework object
    framework = batch_dl.deep_learning_project.frameworks[CellPoseInstanceFramework.descriptor]

    # set the parameters for the cellpose framework
    framework.prob_thresh = -1
    framework.flow_thresh = 0.4
    framework.chan_segment = 0 
    framework.chan2 = 1

    # sync parameters on the widget after this we should see the widget in Napari synced with the parameters we set on the framework
    widget.sync_with_framework()

VIT checkpoint loaded successfully
found framework is  MobileSAMFramework
found framework is  YoloSAMFramework
found framework is  RandomForestFramework
found framework is  PytorchSemanticFramework
found framework is  CellPoseInstanceFramework
creating new log file
2025-02-13 18:54:19,541 [INFO] WRITING LOG OUTPUT TO C:\Users\bnort\.cellpose\run.log
2025-02-13 18:54:19,542 [INFO] 
cellpose version: 	3.1.0 
platform:       	win32 
python version: 	3.10.14 
torch version:  	2.2.2+cu118
Zarr store already up-to-date.
Zarr store already up-to-date.
2025-02-13 18:54:22,297 [INFO] ** TORCH CUDA version installed and working. **
2025-02-13 18:54:22,298 [INFO] >>>> using GPU (CUDA)
2025-02-13 18:54:22,420 [INFO] >>>> loading model ../../data\ladybugs_series\models\cellpose_ladybugs_scale2
2025-02-13 18:54:22,620 [INFO] >>>> model diam_mean =  30.000 (ROIs rescaled to this size during training)
2025-02-13 18:54:22,622 [INFO] >>>> model diam_labels =  181.358 (mean diameter of training ROIs)
'QCheckBox' object has no attribute 'setValue'