From 0985d669882ef75915fba6912dd30f2979edca54 Mon Sep 17 00:00:00 2001
From: Laurent Guerard <laurent.guerard@unibas.ch>
Date: Wed, 8 Jan 2025 14:41:24 +0100
Subject: [PATCH] Add option to do batch
---
1_identify_fibers.py | 176 ++++++++++++++++++++++++++++++++-----------
1 file changed, 134 insertions(+), 42 deletions(-)
diff --git a/1_identify_fibers.py b/1_identify_fibers.py
index 6c3dc3e..9a9b104 100755
--- a/1_identify_fibers.py
+++ b/1_identify_fibers.py
@@ -677,34 +677,42 @@ imp_result = run_tm(membrane, 1, cellpose_dir.getPath(), PretrainedModel.CYTO2,
IJ.saveAs(imp_result, "Tiff", output_dir + "/" + raw_image_title + "_all_fibers_binary")
sys.exit()
+ file_list = pathtools.listdir_matching(
+ src_dir.getPath(), filename_filter, fullpath=True
+ )
-# modify rois
+ out_dir_info = pathtools.parse_path(output_dir)
rm.hide()
raw.hide()
-enlarge_all_rois( enlarge, rm, raw_image_calibration.pixelWidth )
-renumber_rois(rm)
-save_all_rois( rm, output_dir + "/" + raw_image_title + "_all_fiber_rois.zip" )
-# check for positive fibers
-if fiber_channel > 0:
- if min_fiber_intensity == 0:
- min_fiber_intensity = get_threshold_from_method(raw, fiber_channel, "Mean")[0]
- IJ.log( "automatic intensity threshold detection: True" )
+ for index, file in enumerate(file_list):
+ # open image using Bio-Formats
+ file_info = pathtools.parse_path(file)
+ misc.progressbar(index + 1, len(file_list), 1, "Opening : ")
+ raw = bf.import_image(file_info["full"])[0]
- IJ.log( "fiber intensity threshold: " + str(min_fiber_intensity) )
- change_all_roi_color(rm, "blue")
- positive_fibers = select_positive_fibers( raw, fiber_channel, rm, min_fiber_intensity )
- change_subset_roi_color(rm, positive_fibers, "magenta")
- save_selected_rois( rm, positive_fibers, output_dir + "/" + raw_image_title + "_mhc_positive_fiber_rois.zip")
+ # get image info
+ raw_image_calibration = raw.getCalibration()
+ raw_image_title = fix_BF_czi_imagetitle(raw)
+ print("raw image title: ", str(raw_image_title))
-# measure size & shape, save
-IJ.run("Set Measurements...", "area perimeter shape feret's redirect=None decimal=4")
-IJ.run("Clear Results", "")
-measure_in_all_rois( raw, membrane_channel, rm )
+ # take care of paths and directories
+ output_dir = os.path.join(
+ out_dir_info["full"], str(raw_image_title), "1_identify_fibers"
+ )
+ print("output_dir: ", str(output_dir))
-rt = ResultsTable.getResultsTable("Results")
+ if not os.path.exists(str(output_dir)):
+ os.makedirs(str(output_dir))
-print rt.size()
+ # update the log for the user
+ misc.timed_log("Now working on " + str(raw_image_title))
+ if raw_image_calibration.scaled() is False:
+ IJ.log(
+ "Your image is not spatially calibrated! Size measurements are only possible in [px]."
+ )
+ # Only print it once since we'll use the same settings everytime
+ if index == 0:
IJ.log(" -- settings used -- ")
IJ.log("area = " + str(minAr) + "-" + str(maxAr))
IJ.log("perimeter = " + str(minPer) + "-" + str(maxPer))
@@ -714,25 +722,109 @@ print rt.size()
IJ.log("MHC positive fiber channel = " + str(fiber_channel))
# IJ.log("sub-tiling = " + str(tiling_factor))
IJ.log(" -- settings used -- ")
-print "saved the all_fibers_results.csv"
-# dress up the original image, save a overlay-png, present original to the user
-rm.show()
-raw.show()
-show_all_rois_on_image( rm, raw )
-raw.setDisplayMode(IJ.COMPOSITE)
-enhance_contrast( raw )
-IJ.run("From ROI Manager", "") # ROIs -> overlays so they show up in the saved png
-qc_duplicate = raw.duplicate()
-IJ.saveAs(qc_duplicate, "PNG", output_dir + "/" + raw_image_title + "_all_fibers")
-qc_duplicate.close()
-wm.toFront( raw.getWindow() )
-IJ.run("Remove Overlay", "")
-raw.setDisplayMode(IJ.GRAYSCALE)
-show_all_rois_on_image( rm, raw )
-total_execution_time_min = (time.time() - execution_start_time) / 60.0
-IJ.log("total time in minutes: " + str(total_execution_time_min))
-IJ.log( "~~ all done ~~" )
-IJ.selectWindow("Log")
-IJ.saveAs("Text", str(output_dir + "/" + raw_image_title + "_all_fibers_Log"))
-if close_raw == True:
- raw.close()
\ No newline at end of file
+
+ # image (pre)processing and segmentation (-> ROIs)# imp, firstC, lastC, firstZ,
+ # lastZ, firstT, lastT
+ membrane = Duplicator().run(raw, membrane_channel, membrane_channel, 1, 1, 1, 1)
+ imp_bgd_corrected = do_background_correction(membrane)
+ IJ.run("Conversions...", "scale")
+ IJ.run(imp_bgd_corrected, "16-bit", "")
+
+ imp_result = run_tm(
+ imp_bgd_corrected,
+ 1,
+ cellpose_dir.getPath(),
+ PretrainedModel.CYTO2,
+ 30.0,
+ area_thresh=[minAr, maxAr],
+ circularity_thresh=[minCir, maxCir],
+ perimeter_thresh=[minPer, maxPer],
+ )
+ IJ.saveAs(
+ imp_result,
+ "Tiff",
+ os.path.join(output_dir, raw_image_title + "_all_fibers_binary"),
+ )
+
+ command.run(Labels2CompositeRois, True, "rm", rm, "imp", imp_result).get()
+
+ enlarge_all_rois(enlarge_radius, rm, raw_image_calibration.pixelWidth)
+ renumber_rois(rm)
+ save_all_rois(
+ rm, os.path.join(output_dir, raw_image_title + "_all_fiber_rois.zip")
+ )
+
+ # check for positive fibers
+ if fiber_channel > 0:
+ if min_fiber_intensity == 0:
+ min_fiber_intensity = get_threshold_from_method(
+ raw, fiber_channel, "Mean"
+ )[0]
+ IJ.log("automatic intensity threshold detection: True")
+
+ IJ.log("fiber intensity threshold: " + str(min_fiber_intensity))
+ change_all_roi_color(rm, "blue")
+ positive_fibers = select_positive_fibers(
+ raw, fiber_channel, rm, min_fiber_intensity
+ )
+ change_subset_roi_color(rm, positive_fibers, "magenta")
+ save_selected_rois(
+ rm,
+ positive_fibers,
+ os.path.join(
+ output_dir, raw_image_title + "_mhc_positive_fiber_rois.zip"
+ ),
+ )
+
+ # measure size & shape, save
+ IJ.run(
+ "Set Measurements...",
+ "area perimeter shape feret's redirect=None decimal=4",
+ )
+ IJ.run("Clear Results", "")
+ measure_in_all_rois(raw, membrane_channel, rm)
+
+ rt = ResultsTable.getResultsTable("Results")
+
+ # print(rt.size())
+
+ if fiber_channel > 0:
+ # print(rt.size())
+ preset_results_column(rt, "MHC Positive Fibers (magenta)", "NO")
+ # print(rt.size())
+ add_results(rt, "MHC Positive Fibers (magenta)", positive_fibers, "YES")
+ # print(rt.size())
+
+ rt.save(os.path.join(output_dir, raw_image_title + "_all_fibers_results.csv"))
+ # print("saved the all_fibers_results.csv")
+ # dress up the original image, save a overlay-png, present original to the user
+ rm.show()
+ raw.show()
+ show_all_rois_on_image(rm, raw)
+ raw.setDisplayMode(IJ.COMPOSITE)
+ enhance_contrast(raw)
+ IJ.run(
+ "From ROI Manager", ""
+ ) # ROIs -> overlays so they show up in the saved png
+ qc_duplicate = raw.duplicate()
+ IJ.saveAs(
+ qc_duplicate, "PNG", output_dir + "/" + raw_image_title + "_all_fibers"
+ )
+ qc_duplicate.close()
+ wm.toFront(raw.getWindow())
+ IJ.run("Remove Overlay", "")
+ raw.setDisplayMode(IJ.GRAYSCALE)
+ show_all_rois_on_image(rm, raw)
+
+ IJ.selectWindow("Log")
+ IJ.saveAs("Text", str(output_dir + "/" + raw_image_title + "_all_fibers_Log"))
+ membrane.close()
+ imp_bgd_corrected.close()
+ imp_result.close()
+
+ if close_raw == True:
+ raw.close()
+
+ total_execution_time_min = (time.time() - execution_start_time) / 60.0
+ IJ.log("total time in minutes: " + str(total_execution_time_min))
+ IJ.log("~~ all done ~~")
--
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