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Add setting the objective magnification when patching #287

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29 changes: 23 additions & 6 deletions create_patches_fp.py
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Original file line number Diff line number Diff line change
Expand Up @@ -37,12 +37,12 @@ def patching(WSI_object, **kwargs):
start_time = time.time()

# Patch
file_path = WSI_object.process_contours(**kwargs)
file_path, attr_dict = WSI_object.process_contours(**kwargs)


### Stop Patch Timer
patch_time_elapsed = time.time() - start_time
return file_path, patch_time_elapsed
return file_path, patch_time_elapsed, attr_dict


def seg_and_patch(source, save_dir, patch_save_dir, mask_save_dir, stitch_save_dir,
Expand All @@ -52,7 +52,8 @@ def seg_and_patch(source, save_dir, patch_save_dir, mask_save_dir, stitch_save_d
filter_params = {'a_t':100, 'a_h': 16, 'max_n_holes':8},
vis_params = {'vis_level': -1, 'line_thickness': 500},
patch_params = {'use_padding': True, 'contour_fn': 'four_pt'},
patch_level = 0,
magnification = None,
patch_level = 0, custom_downsample = 1,
use_default_params = False,
seg = False, save_mask = True,
stitch= False,
Expand Down Expand Up @@ -195,9 +196,23 @@ def seg_and_patch(source, save_dir, patch_save_dir, mask_save_dir, stitch_save_d

patch_time_elapsed = -1 # Default time
if patch:
current_patch_params.update({'patch_level': patch_level, 'patch_size': patch_size, 'step_size': step_size,
if magnification:
if WSI_object.max_objective_magnification is None:
df.loc[idx, 'status'] = 'WSI do not has the attribute of objective magnification.'
print('WSI do not has the attribute of objective magnification.')
continue
patch_level, custom_downsample = WSI_object.getPatchLevel(magnification)
if isinstance(patch_level, dict):
df.loc[idx, 'status'] = patch_level['error']
print(patch_level['error'])
continue
current_patch_params.update({'patch_level': patch_level, 'patch_size': patch_size,
'step_size': step_size, 'custom_downsample': custom_downsample,
'save_path': patch_save_dir})
file_path, patch_time_elapsed = patching(WSI_object = WSI_object, **current_patch_params,)
file_path, patch_time_elapsed, attr_dict = patching(WSI_object = WSI_object, **current_patch_params)
print(attr_dict)
for key in ['patch_level', 'target_patch_size', 'target_step_size','patch_size', 'step_size', 'custom_downsample']:
df.loc[i, key] = attr_dict[key]

stitch_time_elapsed = -1
if stitch:
Expand Down Expand Up @@ -242,6 +257,8 @@ def seg_and_patch(source, save_dir, patch_save_dir, mask_save_dir, stitch_save_d
help='directory to save processed data')
parser.add_argument('--preset', default=None, type=str,
help='predefined profile of default segmentation and filter parameters (.csv)')
parser.add_argument('--magnification', type=int, default=None,
help='objective magnification at which to patch. When it is not None, the patch_level does not work.')
parser.add_argument('--patch_level', type=int, default=0,
help='downsample level at which to patch')
parser.add_argument('--process_list', type = str, default=None,
Expand Down Expand Up @@ -306,6 +323,6 @@ def seg_and_patch(source, save_dir, patch_save_dir, mask_save_dir, stitch_save_d
seg_times, patch_times = seg_and_patch(**directories, **parameters,
patch_size = args.patch_size, step_size=args.step_size,
seg = args.seg, use_default_params=False, save_mask = True,
stitch= args.stitch,
stitch= args.stitch, magnification = args.magnification,
patch_level=args.patch_level, patch = args.patch,
process_list = process_list, auto_skip=args.no_auto_skip)
5 changes: 4 additions & 1 deletion dataset_modules/dataset_h5.py
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Original file line number Diff line number Diff line change
Expand Up @@ -64,6 +64,8 @@ def __init__(self,
dset = f['coords']
self.patch_level = f['coords'].attrs['patch_level']
self.patch_size = f['coords'].attrs['patch_size']
self.target_patch_size = f['coords'].attrs['target_patch_size']
self.custom_downsample = f['coords'].attrs['custom_downsample']
self.length = len(dset)

self.summary()
Expand All @@ -84,7 +86,8 @@ def __getitem__(self, idx):
with h5py.File(self.file_path,'r') as hdf5_file:
coord = hdf5_file['coords'][idx]
img = self.wsi.read_region(coord, self.patch_level, (self.patch_size, self.patch_size)).convert('RGB')

if self.custom_downsample > 1:
img = img.resize((self.target_patch_size, self.target_patch_size))
img = self.roi_transforms(img)
return {'img': img, 'coord': coord}

Expand Down
49 changes: 47 additions & 2 deletions wsi_core/WholeSlideImage.py
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Original file line number Diff line number Diff line change
Expand Up @@ -32,13 +32,50 @@ def __init__(self, path):
self.wsi = openslide.open_slide(path)
self.level_downsamples = self._assertLevelDownsamples()
self.level_dim = self.wsi.level_dimensions
self.max_objective_magnification = self.getMaxObjectivteMagnification()

self.contours_tissue = None
self.contours_tumor = None
self.hdf5_file = None

def getOpenSlide(self):
return self.wsi

def getMaxObjectivteMagnification(self):
if 'aperio.AppMag' in self.wsi.properties:
return int(self.wsi.properties['aperio.AppMag'])
elif 'openslide.mpp-x' in self.wsi.properties:
if abs(float(self.wsi.properties['openslide.mpp-x'])-0.25) < 0.1:
return 40
elif abs(float(self.wsi.properties['openslide.mpp-x'])-0.5) < 0.1:
return 20
elif 'tiff.XResolution' in self.wsi.properties:
# um per pixel
mpp = 1.0/(float(self.wsi.properties['tiff.XResolution'])/10000)
if abs(mpp-0.25) < 0.1:
return 40
elif abs(mpp-0.5) < 0.1:
return 20
return None

def getPatchLevel(self,magnification):
if magnification > self.max_objective_magnification:
return {'error':'The specified magnification exceeds the maximum available magnification.'}, None
if self.max_objective_magnification % magnification != 0:
return {'error':'The specified magnification must be divisible by the maximum magnification.'}, None
scale = self.max_objective_magnification / magnification
patch_level, custom_downsample = None, None
for i, level_downsample in enumerate(self.level_downsamples):
downsample = int(level_downsample[0])
if downsample == scale:
patch_level = i
custom_downsample = 1
elif downsample>scale:
break
if not patch_level:
patch_level = 0
custom_downsample = scale
return patch_level, custom_downsample

def initXML(self, xml_path):
def _createContour(coord_list):
Expand Down Expand Up @@ -368,7 +405,9 @@ def _assertLevelDownsamples(self):

return level_downsamples

def process_contours(self, save_path, patch_level=0, patch_size=256, step_size=256, **kwargs):
def process_contours(self, save_path, patch_level=0, patch_size=256, step_size=256, custom_downsample=1, **kwargs):
target_patch_size, target_step_size = patch_size, step_size
patch_size, step_size = int(target_patch_size * custom_downsample), int(target_step_size * custom_downsample)
save_path_hdf5 = os.path.join(save_path, str(self.name) + '.h5')
print("Creating patches for: ", self.name, "...",)
elapsed = time.time()
Expand All @@ -381,14 +420,19 @@ def process_contours(self, save_path, patch_level=0, patch_size=256, step_size=2
print('Processing contour {}/{}'.format(idx, n_contours))

asset_dict, attr_dict = self.process_contour(cont, self.holes_tissue[idx], patch_level, save_path, patch_size, step_size, **kwargs)
attr_dict['coords'].update({
'target_patch_size': target_patch_size,
'target_step_size': target_step_size,
'custom_downsample': custom_downsample
})
if len(asset_dict) > 0:
if init:
save_hdf5(save_path_hdf5, asset_dict, attr_dict, mode='w')
init = False
else:
save_hdf5(save_path_hdf5, asset_dict, mode='a')

return self.hdf5_file
return self.hdf5_file, attr_dict['coords']


def process_contour(self, cont, contour_holes, patch_level, save_path, patch_size = 256, step_size = 256,
Expand Down Expand Up @@ -464,6 +508,7 @@ def process_contour(self, cont, contour_holes, patch_level, save_path, patch_siz
asset_dict = {'coords' : results}

attr = {'patch_size' : patch_size, # To be considered...
'step_size' : step_size,
'patch_level' : patch_level,
'downsample': self.level_downsamples[patch_level],
'downsampled_level_dim' : tuple(np.array(self.level_dim[patch_level])),
Expand Down