Skip to content

solved training images issue #110

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 2 commits into from
Mar 25, 2025
Merged

solved training images issue #110

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
cbd0fa5
solved issue
miri-2000 Mar 24, 2025
97b74e2
updated test
miri-2000 Mar 25, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
20 changes: 17 additions & 3 deletions bin/crop_hdf5.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -122,10 +122,12 @@ def IlastikPrepOME(
full_h5 = h5py.File(pathlib.Path(os.path.join(output, h5_name)), "r")
im_nuc = full_h5[str(im_stem)][:, :, :, nuclei_index]
im = full_h5[str(im_stem)][:, :, :, :]
# Track previous crops as (h_up, h_down, w_lt, w_rt) tuples
previous_crops = []
indices = {}
count = 0
count = 1
thresh = filters.threshold_otsu(im_nuc[:, :, :])
while count < crop_amount:
while count < crop_amount+1:
# Get random height value that falls within crop range of the edges
extension_h = crop_size[0] // 2
h = random.randint(extension_h, im_nuc.shape[1] - extension_h)
Expand All @@ -134,6 +136,16 @@ def IlastikPrepOME(
extension_w = crop_size[1] // 2
w = random.randint(extension_w, im_nuc.shape[2] - extension_w)
w_lt, w_rt = w - extension_w, w + extension_w
# Check if the new crop overlaps with any previous crop
overlap = False
for prev_crop in previous_crops:
prev_h_up, prev_h_down, prev_w_lt, prev_w_rt = prev_crop
if not (h_down <= prev_h_up or h_up >= prev_h_down or w_rt <= prev_w_lt or w_lt >= prev_w_rt):
overlap = True
break
# If overlap, try again. Otherwise, save the crop and continue
if overlap:
continue
# Crop the image with these coordinates expanding from center
crop = im_nuc[:, h_up:h_down, w_lt:w_rt]
crop_name = pathlib.Path(os.path.join(output, (im_stem + "_crop" + str(count) + ".hdf5")))
Expand All @@ -147,7 +159,9 @@ def IlastikPrepOME(
h5_crop.close()
print("Finished exporting " + crop_name.stem + ".hdf5")
# Add one to the counter
count = count + 1
count += 1
# Add the current crop coordinates to the list of previous crops
previous_crops.append((h_up, h_down, w_lt, w_rt))
# Add the indices to a table to store the cropped indices
indices.update({crop_name.stem: [(h_up, h_down), (w_lt, w_rt)]})
# Export the indices to a text file to track the cropped regions
Expand Down
2 changes: 1 addition & 1 deletion bin/crop_tiff.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@

# Create a function to create crops from a tiff image and a dictionary of crop coordinates
def create_crops(tiff_image, crop_dict):
for index, (crop_name, crop) in enumerate(crop_dict.items()):
for index, (crop_name, crop) in enumerate(crop_dict.items(), start=1):
crop_image = tiff_image[:, crop[0][0] : crop[0][1], crop[1][0] : crop[1][1]]
basename = os.path.basename(args.input)
basename = os.path.splitext(basename)[0]
Expand Down
8 changes: 4 additions & 4 deletions tests/main.nf.test.snap
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -362,11 +362,11 @@
"pipeline_info/nf_core_molkart_software_mqc_versions.yml",
"training_subset",
"training_subset/hdf5",
"training_subset/hdf5/nuc_only_nuclear_gridfilled_clahe_crop0.hdf5",
"training_subset/hdf5/nuc_only_nuclear_gridfilled_clahe_crop1.hdf5",
"training_subset/hdf5/nuc_only_nuclear_gridfilled_clahe_crop2.hdf5",
"training_subset/tiff",
"training_subset/tiff/nuc_only_nuclear_gridfilled_clahe_crop0.tiff",
"training_subset/tiff/nuc_only_nuclear_gridfilled_clahe_crop1.tiff"
"training_subset/tiff/nuc_only_nuclear_gridfilled_clahe_crop1.tiff",
"training_subset/tiff/nuc_only_nuclear_gridfilled_clahe_crop2.tiff"
],
[
"nuc_only_nuclear_gridfilled.tiff:md5,123763d54f05b2274690b3b84f9690b1",
Expand All @@ -379,6 +379,6 @@
"nf-test": "0.9.2",
"nextflow": "24.10.5"
},
"timestamp": "2025-03-05T17:00:52.037627778"
"timestamp": "2025-03-25T10:00:57.349249698"
}
}