diff --git a/bob/ip/binseg/configs/datasets/drivestarechasedb1hrf1024.py b/bob/ip/binseg/configs/datasets/drivestarechasedb1hrf1024.py
new file mode 100644
index 0000000000000000000000000000000000000000..74628abe77801ef572cd3ad2ff379e9af9287506
--- /dev/null
+++ b/bob/ip/binseg/configs/datasets/drivestarechasedb1hrf1024.py
@@ -0,0 +1,10 @@
+from bob.ip.binseg.configs.datasets.drive1024 import dataset as drive
+from bob.ip.binseg.configs.datasets.stare1024 import dataset as stare
+from bob.ip.binseg.configs.datasets.hrf1024 import dataset as hrf
+from bob.ip.binseg.configs.datasets.chasedb11024 import dataset as chase
+import torch
+
+#### Config ####
+
+# PyTorch dataset
+dataset = torch.utils.data.ConcatDataset([drive,stare,hrf,chase])
diff --git a/bob/ip/binseg/configs/datasets/drivestarechasedb1hrf1024ssliostar.py b/bob/ip/binseg/configs/datasets/drivestarechasedb1hrf1024ssliostar.py
new file mode 100644
index 0000000000000000000000000000000000000000..4dbd23d2cf52f40e4b03c38bb603f4139900a1c1
--- /dev/null
+++ b/bob/ip/binseg/configs/datasets/drivestarechasedb1hrf1024ssliostar.py
@@ -0,0 +1,34 @@
+from bob.ip.binseg.configs.datasets.drive1024 import dataset as drive
+from bob.ip.binseg.configs.datasets.stare1024 import dataset as stare
+from bob.ip.binseg.configs.datasets.hrf1024 import dataset as hrf
+from bob.ip.binseg.configs.datasets.chasedb11024 import dataset as chasedb
+from bob.db.iostar import Database as IOSTAR
+from bob.ip.binseg.data.transforms import *
+import torch
+from bob.ip.binseg.data.binsegdataset import BinSegDataset, SSLBinSegDataset, UnLabeledBinSegDataset
+
+
+#### Config ####
+
+# PyTorch dataset
+labeled_dataset = torch.utils.data.ConcatDataset([drive,stare,hrf,chasedb])
+
+#### Unlabeled CHASE TRAIN ####
+unlabeled_transforms = Compose([
+ Crop(0,18,960,960)
+ ,RandomHFlip()
+ ,RandomVFlip()
+ ,RandomRotation()
+ ,ColorJitter()
+ ,ToTensor()
+ ])
+
+# bob.db.dataset init
+iostarbobdb = IOSTAR(protocol='default_vessel')
+
+# PyTorch dataset
+unlabeled_dataset = UnLabeledBinSegDataset(iostarbobdb, split='train', transform=unlabeled_transforms)
+
+# SSL Dataset
+
+dataset = SSLBinSegDataset(labeled_dataset, unlabeled_dataset)
\ No newline at end of file
diff --git a/bob/ip/binseg/configs/datasets/drivestarechasedb1iostar1168sslhrf.py b/bob/ip/binseg/configs/datasets/drivestarechasedb1iostar1168sslhrf.py
new file mode 100644
index 0000000000000000000000000000000000000000..376aae1482ac3c8bd6911ae61e83f498bb5ad6c6
--- /dev/null
+++ b/bob/ip/binseg/configs/datasets/drivestarechasedb1iostar1168sslhrf.py
@@ -0,0 +1,35 @@
+from bob.ip.binseg.configs.datasets.drive1168 import dataset as drive
+from bob.ip.binseg.configs.datasets.stare1168 import dataset as stare
+from bob.ip.binseg.configs.datasets.chasedb11168 import dataset as chasedb
+from bob.ip.binseg.configs.datasets.iostarvessel1168 import dataset as iostar
+from bob.db.hrf import Database as HRF
+from bob.ip.binseg.data.transforms import *
+import torch
+from bob.ip.binseg.data.binsegdataset import BinSegDataset, SSLBinSegDataset, UnLabeledBinSegDataset
+
+
+#### Config ####
+
+# PyTorch dataset
+labeled_dataset = torch.utils.data.ConcatDataset([drive,stare,iostar,chasedb])
+
+#### Unlabeled CHASE TRAIN ####
+unlabeled_transforms = Compose([
+ Crop(0,108,2336,3296)
+ ,Resize((1168))
+ ,RandomHFlip()
+ ,RandomVFlip()
+ ,RandomRotation()
+ ,ColorJitter()
+ ,ToTensor()
+ ])
+
+# bob.db.dataset init
+hrfbobdb = HRF(protocol='default')
+
+# PyTorch dataset
+unlabeled_dataset = UnLabeledBinSegDataset(hrfbobdb, split='train', transform=unlabeled_transforms)
+
+# SSL Dataset
+
+dataset = SSLBinSegDataset(labeled_dataset, unlabeled_dataset)
\ No newline at end of file
diff --git a/bob/ip/binseg/configs/datasets/hrf1024.py b/bob/ip/binseg/configs/datasets/hrf1024.py
new file mode 100644
index 0000000000000000000000000000000000000000..48168445f5689b95a1f55ffda0633d2acdbb619a
--- /dev/null
+++ b/bob/ip/binseg/configs/datasets/hrf1024.py
@@ -0,0 +1,24 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+from bob.db.hrf import Database as HRF
+from bob.ip.binseg.data.transforms import *
+from bob.ip.binseg.data.binsegdataset import BinSegDataset
+
+#### Config ####
+
+transforms = Compose([
+ Pad((0,584,0,584))
+ ,Resize((1024))
+ ,RandomRotation()
+ ,RandomHFlip()
+ ,RandomVFlip()
+ ,ColorJitter()
+ ,ToTensor()
+ ])
+
+# bob.db.dataset init
+bobdb = HRF(protocol = 'default')
+
+# PyTorch dataset
+dataset = BinSegDataset(bobdb, split='train', transform=transforms)
diff --git a/bob/ip/binseg/script/binseg.py b/bob/ip/binseg/script/binseg.py
index 6af9d438a317a280d1b2c3e0c5fbe65fbd50068d..5b01d03960693f7c9cffe2f0207f3758c799605e 100644
--- a/bob/ip/binseg/script/binseg.py
+++ b/bob/ip/binseg/script/binseg.py
@@ -309,12 +309,17 @@ def testcheckpoints(model
'-o',
required=True,
)
+@click.option(
+ '--title',
+ '-t',
+ required=False,
+ )
@verbosity_option(cls=ResourceOption)
-def compare(output_path_list, output_path, **kwargs):
+def compare(output_path_list, output_path, title, **kwargs):
""" Compares multiple metrics files that are stored in the format mymodel/results/Metrics.csv """
logger.debug("Output paths: {}".format(output_path_list))
logger.info('Plotting precision vs recall curves for {}'.format(output_path_list))
- fig = plot_overview(output_path_list)
+ fig = plot_overview(output_path_list,title)
if not os.path.exists(output_path): os.makedirs(output_path)
fig_filename = os.path.join(output_path, 'precision_recall_comparison.pdf')
logger.info('saving {}'.format(fig_filename))
diff --git a/bob/ip/binseg/utils/plot.py b/bob/ip/binseg/utils/plot.py
index bedb7625a0fbdb98b6e72538bd0e9f81ed313d6e..db6269377054f5084e0fe84b8fb14c30733ba9a1 100644
--- a/bob/ip/binseg/utils/plot.py
+++ b/bob/ip/binseg/utils/plot.py
@@ -158,7 +158,7 @@ def read_metricscsv(file):
return np.array(precision), np.array(recall)
-def plot_overview(outputfolders):
+def plot_overview(outputfolders,title):
"""
Plots comparison chart of all trained models
@@ -166,6 +166,8 @@ def plot_overview(outputfolders):
----------
outputfolder : list
list containing output paths of all evaluated models (e.g. ``['DRIVE/model1', 'DRIVE/model2']``)
+ title : str
+ title of plot
Returns
-------
matplotlib.figure.Figure
@@ -181,15 +183,16 @@ def plot_overview(outputfolders):
precisions.append(pr)
recalls.append(re)
modelname = folder.split('/')[-1]
+ datasetname = folder.split('/')[-2]
# parameters
summary_path = os.path.join(folder,'results/ModelSummary.txt')
with open (summary_path, "r") as outfile:
rows = outfile.readlines()
lastrow = rows[-1]
parameter = int(lastrow.split()[1].replace(',',''))
- name = '[P={:.2f}M] {}'.format(parameter/100**3, modelname)
+ name = '[P={:.2f}M] {} {}'.format(parameter/100**3, modelname, datasetname)
names.append(name)
- title = folder.split('/')[-2]
+ #title = folder.split('/')[-4]
fig = precision_recall_f1iso(precisions,recalls,names,title)
return fig
@@ -286,4 +289,4 @@ def overlay(dataset, output_path):
# save to disk
overlayed_path = os.path.join(output_path,'overlayed')
if not os.path.exists(overlayed_path): os.makedirs(overlayed_path)
- overlayed.save(os.path.join(overlayed_path,name))
\ No newline at end of file
+ overlayed.save(os.path.join(overlayed_path,name))