Skip to content

Commit

Permalink
ensure that the brain mask and void image are treated differently
Browse files Browse the repository at this point in the history
  • Loading branch information
@sarthakpati
sarthakpati committed Dec 19, 2024
1 parent ca49b4c commit 1c4afd7
Showing 1 changed file with 49 additions and 34 deletions.
83 changes: 49 additions & 34 deletions GANDLF/cli/generate_metrics.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -302,21 +302,22 @@ def __percentile_clip(
reference_tensor = (
input_tensor if reference_tensor is None else reference_tensor
)
v_min, v_max = np.percentile(
reference_tensor, [p_min, p_max]
) # get p_min percentile and p_max percentile

# get p_min percentile and p_max percentile
v_min, v_max = np.percentile(reference_tensor, [p_min, p_max])
# set lower bound to be 0 if strictlyPositive is enabled
v_min = max(v_min, 0.0) if strictlyPositive else v_min
output_tensor = np.clip(
input_tensor, v_min, v_max
) # clip values to percentiles from reference_tensor
output_tensor = (output_tensor - v_min) / (
v_max - v_min
) # normalizes values to [0;1]
# clip values to percentiles from reference_tensor
output_tensor = np.clip(input_tensor, v_min, v_max)
# normalizes values to [0;1]
output_tensor = (output_tensor - v_min) / (v_max - v_min)
return output_tensor

input_df = __update_header_location_case_insensitive(input_df, "Mask", False)
# these are additional columns that could be present for synthesis tasks
for column_to_make_case_insensitive in ["Mask", "VoidImage"]:
input_df = __update_header_location_case_insensitive(
input_df, column_to_make_case_insensitive, False
)

for _, row in tqdm(input_df.iterrows(), total=input_df.shape[0]):
current_subject_id = row["SubjectID"]
overall_stats_dict[current_subject_id] = {}
Expand All @@ -332,16 +333,26 @@ def __percentile_clip(
)
).byte()

void_image_present = True if "VoidImage" in row else False
void_image = (
__fix_2d_tensor(torchio.ScalarImage(row["VoidImage"]).data)
if "VoidImage" in row
else torch.from_numpy(
np.ones(target_image.numpy().shape, dtype=np.uint8)
)
)

# Get Infill region (we really are only interested in the infill region)
output_infill = (pred_image * mask).float()
gt_image_infill = (target_image * mask).float()

# Normalize to [0;1] based on GT (otherwise MSE will depend on the image intensity range)
normalize = parameters.get("normalize", True)
if normalize:
# use all the tissue that is not masked for normalization
reference_tensor = (
target_image * ~mask
) # use all the tissue that is not masked for normalization
target_image * ~mask if not void_image_present else void_image
)
gt_image_infill = __percentile_clip(
gt_image_infill,
reference_tensor=reference_tensor,
Expand All @@ -357,9 +368,9 @@ def __percentile_clip(
strictlyPositive=True,
)

overall_stats_dict[current_subject_id][
"ssim"
] = structural_similarity_index(output_infill, gt_image_infill, mask).item()
overall_stats_dict[current_subject_id]["ssim"] = (
structural_similarity_index(output_infill, gt_image_infill, mask).item()
)

# ncc metrics
compute_ncc = parameters.get("compute_ncc", True)
Expand All @@ -386,6 +397,10 @@ def __percentile_clip(
output_infill, gt_image_infill
).item()

overall_stats_dict[current_subject_id]["rmse"] = mean_squared_error(

Check warning on line 400 in GANDLF/cli/generate_metrics.py

View workflow job for this annotation

GitHub Actions / Check Spelling 

`rmse` is not a recognized word. (unrecognized-spelling)
output_infill, gt_image_infill, squared=False
).item()

overall_stats_dict[current_subject_id]["msle"] = mean_squared_log_error(
output_infill, gt_image_infill
).item()
Expand All @@ -400,30 +415,30 @@ def __percentile_clip(
).item()

# same as above but with epsilon for robustness
overall_stats_dict[current_subject_id][
"psnr_eps"
] = peak_signal_noise_ratio(
output_infill, gt_image_infill, epsilon=sys.float_info.epsilon
).item()
overall_stats_dict[current_subject_id]["psnr_eps"] = (
peak_signal_noise_ratio(
output_infill, gt_image_infill, epsilon=sys.float_info.epsilon
).item()
)

# only use fix data range to [0;1] if the data was normalized before
if normalize:
# torchmetrics PSNR but with fixed data range of 0 to 1
overall_stats_dict[current_subject_id][
"psnr_01"
] = peak_signal_noise_ratio(
output_infill, gt_image_infill, data_range=(0, 1)
).item()
overall_stats_dict[current_subject_id]["psnr_01"] = (
peak_signal_noise_ratio(
output_infill, gt_image_infill, data_range=(0, 1)
).item()
)

# same as above but with epsilon for robustness
overall_stats_dict[current_subject_id][
"psnr_01_eps"
] = peak_signal_noise_ratio(
output_infill,
gt_image_infill,
data_range=(0, 1),
epsilon=sys.float_info.epsilon,
).item()
overall_stats_dict[current_subject_id]["psnr_01_eps"] = (
peak_signal_noise_ratio(
output_infill,
gt_image_infill,
data_range=(0, 1),
epsilon=sys.float_info.epsilon,
).item()
)

pprint(overall_stats_dict)
if outputfile is not None:
Expand Down

1 comment on commit 1c4afd7

@github-actions
Copy link

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

@check-spelling-bot Report

🔴 Please review

See the 📜action log or 📝 job summary for details.

Unrecognized words (1)

rmse

These words are not needed and should be removed adopy tiffslide Uploded

Some files were automatically ignored 🙈

These sample patterns would exclude them:

[^/]\.png$
^\Q.gitattributes\E$
^\Q.spelling/.spelling/expect.txt\E$
^\Q__init__.py\E$
^\QGANDLF/data/patch_miner/__init__.py\E$
^\QGANDLF/data/patch_miner/opm/__init__.py\E$
^\QGANDLF/grad_clipping/__init__.py\E$
^\QGANDLF/models/seg_modules/__init__.py\E$
^\QGANDLF/privacy/__init__.py\E$
^\Qtesting/__init__.py\E$
^\Qtutorials/classification_medmnist_notebook/tutorial.ipynb\E$
^samples/images_opm/
^tutorials/classification_medmnist_notebook/medmnist/

You should consider excluding directory paths (e.g. (?:^|/)vendor/), filenames (e.g. (?:^|/)yarn\.lock$), or file extensions (e.g. \.gz$)

You should consider adding them to:

.github/actions/spelling/excludes.txt

File matching is via Perl regular expressions.

To check these files, more of their words need to be in the dictionary than not. You can use patterns.txt to exclude portions, add items to the dictionary (e.g. by adding them to allow.txt), or fix typos.

To accept these unrecognized words as correct, update file exclusions, and remove the previously acknowledged and now absent words, you could run the following commands

... in a clone of the git@github.com:sarthakpati/GaNDLF.git repository
on the synthesis_metrics_debug branch (ℹ️ how do I use this?):

curl -s -S -L 'https://raw.githubusercontent.com/check-spelling/check-spelling/main/apply.pl' |
perl - 'https://github.com/sarthakpati/GaNDLF/actions/runs/12416093250/attempts/1'
Available 📚 dictionaries could cover words not in the 📘 dictionary
Dictionary Entries Covers Uniquely
cspell:java/src/java-terms.txt 920 2 2

Consider adding them (in .github/workflows/spellchecker.yml) in jobs:/spelling: for uses: check-spelling/check-spelling@main in its with:

      with:
        extra_dictionaries: |
          cspell:java/src/java-terms.txt

To stop checking additional dictionaries, add (in .github/workflows/spellchecker.yml) for uses: check-spelling/check-spelling@main in its with:

check_extra_dictionaries: ''
Warnings (3)

See the 📜action log or 📝 job summary for details.

⚠️ Warnings Count
⚠️ binary-file 19
⚠️ large-file 2
⚠️ noisy-file 2

See ⚠️ Event descriptions for more information.

Please sign in to comment.