add script to save image patches

applications/contrastive_phenotyping/figures/save_patches.py

@@ -0,0 +1,53 @@
+
+# %% script to save 128 by 128 image patches from napari viewer
+
+import napari
+import numpy as np
+from pathlib import Path
+import sys
+
+sys.path.append("/hpc/mydata/soorya.pradeep/scratch/viscy_infection_phenotyping/VisCy")
+# from viscy.data.triplet import TripletDataModule
+from viscy.representation.evaluation import dataset_of_tracks
+
+
+# %% input parameters
+
+data_path = Path(
+    "/hpc/projects/intracellular_dashboard/viral-sensor/2024_02_04_A549_DENV_ZIKV_timelapse/8-train-test-split/registered_test.zarr"
+)
+tracks_path = Path(
+    "/hpc/projects/intracellular_dashboard/viral-sensor/2024_02_04_A549_DENV_ZIKV_timelapse/8-train-test-split/track_test.zarr"
+)
+
+fov_name = '/B/4/8'
+track_id = 12
+source_channel = ["Phase3D", "RFP"]
+
+# %% load dataset
+
+prediction_dataset = dataset_of_tracks(
+    data_path,
+    tracks_path,
+    [fov_name],
+    [track_id],
+    source_channel=source_channel,
+)
+whole = np.stack([p["anchor"] for p in prediction_dataset])
+phase = whole[:, 0]
+fluor = whole[:, 1]
+
+# use the following if you want to visualize a specific phase slice with max projected fluor
+# phase = whole[:, 0, 3]   # 3 is the slice number
+# fluor = np.max(whole[:, 1], axis=1)
+
+# load image
+v = napari.Viewer()
+v.add_image(phase)
+v.add_image(fluor)
+
+# %% save patches as png images
+
+# use sliders on napari to get the deisred contrast and make other adjustments
+# then use save screenshot if saving the image patch manually
+# you can add code to automate the process if desired