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fix: recursively look for h5 files to generate slide encodings #171

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fix: recursively look for h5 files to generate slide encodings #171

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20 changes: 13 additions & 7 deletions src/stamp/encoding/encoder/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -62,22 +62,25 @@ def encode_slides_(
if self.precision == torch.float16:
self.model.half()

h5_files = sorted(f for f in os.listdir(feat_dir) if f.endswith(".h5"))
for tile_feats_filename in (progress := tqdm(h5_files)):
h5_path = os.path.join(feat_dir, tile_feats_filename)
slide_name: str = Path(tile_feats_filename).stem
# Recursively collect all .h5 files in feat_dir
h5_files = [p for p in feat_dir.glob("**/*.h5")]
for h5_path in (progress := tqdm(h5_files)):
slide_name: str = h5_path.stem
progress.set_description(slide_name)

# skip patient in case feature file already exists
output_path = (encode_dir / slide_name).with_suffix(".h5")
# Maintain the relative folder structure in the output directory
relative_path = h5_path.relative_to(feat_dir)
output_path = (encode_dir / relative_path).with_suffix(".h5")

# Skip processing if the output file already exists
if output_path.exists():
_logger.info(
f"skipping {str(slide_name)} because {output_path} already exists"
)
continue

try:
feats, coords = self._validate_and_read_features(h5_path)
feats, coords = self._validate_and_read_features(str(h5_path))
except ValueError as e:
tqdm.write(s=str(e))
continue
Expand Down Expand Up @@ -200,6 +203,9 @@ def _read_h5(
def _save_features_(
self, output_path: Path, feats: np.ndarray, feat_type: str
) -> None:
# Ensure the parent directory exists before creating the temporary file
output_path.parent.mkdir(parents=True, exist_ok=True)

with (
NamedTemporaryFile(dir=output_path.parent, delete=False) as tmp_h5_file,
h5py.File(tmp_h5_file, "w") as f,
Expand Down
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