From 1c136bc1810b6eed0dc4694eb9240319f063fd6d Mon Sep 17 00:00:00 2001
From: Andre Anjos <andre.dos.anjos@gmail.com>
Date: Wed, 13 May 2020 18:02:53 +0200
Subject: [PATCH] [test.test_config] Fix config tests after db remodelling
---
bob/ip/binseg/test/test_config.py | 190 +++++++++++++++---------------
1 file changed, 98 insertions(+), 92 deletions(-)
diff --git a/bob/ip/binseg/test/test_config.py b/bob/ip/binseg/test/test_config.py
index 52e3a2b3..2d6cc499 100644
--- a/bob/ip/binseg/test/test_config.py
+++ b/bob/ip/binseg/test/test_config.py
@@ -34,8 +34,9 @@ def test_drive():
from ..configs.datasets.drive.default import dataset
- nose.tools.eq_(len(dataset), 3)
+ nose.tools.eq_(len(dataset), 4)
_check_subset(dataset["__train__"], 20)
+ _check_subset(dataset["__valid__"], 20)
_check_subset(dataset["train"], 20)
_check_subset(dataset["test"], 20)
@@ -53,7 +54,7 @@ def test_drive():
def test_drive_mtest():
from ..configs.datasets.drive.mtest import dataset
- nose.tools.eq_(len(dataset), 6)
+ nose.tools.eq_(len(dataset), 10)
from ..configs.datasets.drive.default import dataset as baseline
nose.tools.eq_(dataset["train"], baseline["train"])
@@ -80,25 +81,24 @@ def test_drive_mtest():
def test_drive_covd():
from ..configs.datasets.drive.covd import dataset
- nose.tools.eq_(len(dataset), 3)
+ nose.tools.eq_(len(dataset), 4)
from ..configs.datasets.drive.default import dataset as baseline
- nose.tools.eq_(dataset["train"], baseline["train"])
+ nose.tools.eq_(dataset["train"], dataset["__valid__"])
nose.tools.eq_(dataset["test"], baseline["test"])
- # this is the only different set from the baseline
- nose.tools.eq_(len(dataset["__train__"]), 53)
-
- for sample in dataset["__train__"]:
- assert 3 <= len(sample) <= 4
- assert isinstance(sample[0], str)
- nose.tools.eq_(sample[1].shape, (3, 544, 544)) #planes, height, width
- nose.tools.eq_(sample[1].dtype, torch.float32)
- nose.tools.eq_(sample[2].shape, (1, 544, 544)) #planes, height, width
- nose.tools.eq_(sample[2].dtype, torch.float32)
- if len(sample) == 4:
- nose.tools.eq_(sample[3].shape, (1, 544, 544)) #planes, height, width
- nose.tools.eq_(sample[3].dtype, torch.float32)
+ for key in ("__train__", "train"):
+ nose.tools.eq_(len(dataset[key]), 123)
+ for sample in dataset["__train__"]:
+ assert 3 <= len(sample) <= 4
+ assert isinstance(sample[0], str)
+ nose.tools.eq_(sample[1].shape, (3, 544, 544)) #planes, height, width
+ nose.tools.eq_(sample[1].dtype, torch.float32)
+ nose.tools.eq_(sample[2].shape, (1, 544, 544)) #planes, height, width
+ nose.tools.eq_(sample[2].dtype, torch.float32)
+ if len(sample) == 4:
+ nose.tools.eq_(sample[3].shape, (1, 544, 544))
+ nose.tools.eq_(sample[3].dtype, torch.float32)
@rc_variable_set("bob.ip.binseg.drive.datadir")
@@ -109,15 +109,16 @@ def test_drive_covd():
def test_drive_ssl():
from ..configs.datasets.drive.ssl import dataset
- nose.tools.eq_(len(dataset), 3)
-
- from ..configs.datasets.drive.default import dataset as baseline
- nose.tools.eq_(dataset["train"], baseline["train"])
- nose.tools.eq_(dataset["test"], baseline["test"])
+ nose.tools.eq_(len(dataset), 4)
- # this is the only different set from the baseline
- nose.tools.eq_(len(dataset["__train__"]), 53)
+ from ..configs.datasets.drive.covd import dataset as covd
+ nose.tools.eq_(dataset["train"], covd["train"])
+ nose.tools.eq_(dataset["train"], dataset["__valid__"])
+ nose.tools.eq_(dataset["test"], covd["test"])
+ nose.tools.eq_(dataset["__valid__"], covd["__valid__"])
+ # these are the only different from the baseline
+ nose.tools.eq_(len(dataset["__train__"]), 123)
for sample in dataset["__train__"]:
assert 5 <= len(sample) <= 6
assert isinstance(sample[0], str)
@@ -172,7 +173,7 @@ def test_stare():
for protocol in "ah", "vk":
dataset = _maker(protocol, stare_dataset)
- nose.tools.eq_(len(dataset), 3)
+ nose.tools.eq_(len(dataset), 4)
_check_subset(dataset["__train__"], 10)
_check_subset(dataset["train"], 10)
_check_subset(dataset["test"], 10)
@@ -186,7 +187,7 @@ def test_stare():
def test_stare_mtest():
from ..configs.datasets.stare.mtest import dataset
- nose.tools.eq_(len(dataset), 6)
+ nose.tools.eq_(len(dataset), 10)
from ..configs.datasets.stare.ah import dataset as baseline
nose.tools.eq_(dataset["train"], baseline["train"])
@@ -213,24 +214,25 @@ def test_stare_mtest():
def test_stare_covd():
from ..configs.datasets.stare.covd import dataset
- nose.tools.eq_(len(dataset), 3)
+ nose.tools.eq_(len(dataset), 4)
from ..configs.datasets.stare.ah import dataset as baseline
- nose.tools.eq_(dataset["train"], baseline["train"])
+ nose.tools.eq_(dataset["train"], dataset["__valid__"])
nose.tools.eq_(dataset["test"], baseline["test"])
- # this is the only different set from the baseline
- nose.tools.eq_(len(dataset["__train__"]), 63)
- for sample in dataset["__train__"]:
- assert 3 <= len(sample) <= 4
- assert isinstance(sample[0], str)
- nose.tools.eq_(sample[1].shape, (3, 608, 704)) #planes, height, width
- nose.tools.eq_(sample[1].dtype, torch.float32)
- nose.tools.eq_(sample[2].shape, (1, 608, 704)) #planes, height, width
- nose.tools.eq_(sample[2].dtype, torch.float32)
- if len(sample) == 4:
- nose.tools.eq_(sample[3].shape, (1, 608, 704)) #planes, height, width
- nose.tools.eq_(sample[3].dtype, torch.float32)
+ # these are the only different sets from the baseline
+ for key in ("__train__", "train"):
+ nose.tools.eq_(len(dataset[key]), 143)
+ for sample in dataset[key]:
+ assert 3 <= len(sample) <= 4
+ assert isinstance(sample[0], str)
+ nose.tools.eq_(sample[1].shape, (3, 608, 704)) #planes, height, width
+ nose.tools.eq_(sample[1].dtype, torch.float32)
+ nose.tools.eq_(sample[2].shape, (1, 608, 704)) #planes, height, width
+ nose.tools.eq_(sample[2].dtype, torch.float32)
+ if len(sample) == 4:
+ nose.tools.eq_(sample[3].shape, (1, 608, 704))
+ nose.tools.eq_(sample[3].dtype, torch.float32)
@rc_variable_set("bob.ip.binseg.chasedb1.datadir")
@@ -249,8 +251,9 @@ def test_chasedb1():
for m in ("first_annotator", "second_annotator"):
d = importlib.import_module(f"...configs.datasets.chasedb1.{m}",
package=__name__).dataset
- nose.tools.eq_(len(d), 3)
+ nose.tools.eq_(len(d), 4)
_check_subset(d["__train__"], 8)
+ _check_subset(d["__valid__"], 8)
_check_subset(d["train"], 8)
_check_subset(d["test"], 20)
@@ -263,7 +266,7 @@ def test_chasedb1():
def test_chasedb1_mtest():
from ..configs.datasets.chasedb1.mtest import dataset
- nose.tools.eq_(len(dataset), 6)
+ nose.tools.eq_(len(dataset), 10)
from ..configs.datasets.chasedb1.first_annotator import dataset as baseline
nose.tools.eq_(dataset["train"], baseline["train"])
@@ -290,24 +293,25 @@ def test_chasedb1_mtest():
def test_chasedb1_covd():
from ..configs.datasets.chasedb1.covd import dataset
- nose.tools.eq_(len(dataset), 3)
+ nose.tools.eq_(len(dataset), 4)
from ..configs.datasets.chasedb1.first_annotator import dataset as baseline
- nose.tools.eq_(dataset["train"], baseline["train"])
+ nose.tools.eq_(dataset["train"], dataset["__valid__"])
nose.tools.eq_(dataset["test"], baseline["test"])
- # this is the only different set from the baseline
- nose.tools.eq_(len(dataset["__train__"]), 65)
- for sample in dataset["__train__"]:
- assert 3 <= len(sample) <= 4
- assert isinstance(sample[0], str)
- nose.tools.eq_(sample[1].shape, (3, 960, 960)) #planes, height, width
- nose.tools.eq_(sample[1].dtype, torch.float32)
- nose.tools.eq_(sample[2].shape, (1, 960, 960)) #planes, height, width
- nose.tools.eq_(sample[2].dtype, torch.float32)
- if len(sample) == 4:
- nose.tools.eq_(sample[3].shape, (1, 960, 960)) #planes, height, width
- nose.tools.eq_(sample[3].dtype, torch.float32)
+ # these are the only different sets from the baseline
+ for key in ("__train__", "train"):
+ nose.tools.eq_(len(dataset[key]), 135)
+ for sample in dataset[key]:
+ assert 3 <= len(sample) <= 4
+ assert isinstance(sample[0], str)
+ nose.tools.eq_(sample[1].shape, (3, 960, 960)) #planes, height, width
+ nose.tools.eq_(sample[1].dtype, torch.float32)
+ nose.tools.eq_(sample[2].shape, (1, 960, 960)) #planes, height, width
+ nose.tools.eq_(sample[2].dtype, torch.float32)
+ if len(sample) == 4:
+ nose.tools.eq_(sample[3].shape, (1, 960, 960))
+ nose.tools.eq_(sample[3].dtype, torch.float32)
@rc_variable_set("bob.ip.binseg.hrf.datadir")
@@ -326,7 +330,7 @@ def test_hrf():
nose.tools.eq_(s[3].dtype, torch.float32)
from ..configs.datasets.hrf.default import dataset
- nose.tools.eq_(len(dataset), 3)
+ nose.tools.eq_(len(dataset), 4)
_check_subset(dataset["__train__"], 15)
_check_subset(dataset["train"], 15)
_check_subset(dataset["test"], 30)
@@ -340,7 +344,7 @@ def test_hrf():
def test_hrf_mtest():
from ..configs.datasets.hrf.mtest import dataset
- nose.tools.eq_(len(dataset), 6)
+ nose.tools.eq_(len(dataset), 10)
from ..configs.datasets.hrf.default import dataset as baseline
nose.tools.eq_(dataset["train"], baseline["train"])
@@ -367,24 +371,25 @@ def test_hrf_mtest():
def test_hrf_covd():
from ..configs.datasets.hrf.covd import dataset
- nose.tools.eq_(len(dataset), 3)
+ nose.tools.eq_(len(dataset), 4)
from ..configs.datasets.hrf.default import dataset as baseline
- nose.tools.eq_(dataset["train"], baseline["train"])
+ nose.tools.eq_(dataset["train"], dataset["__valid__"])
nose.tools.eq_(dataset["test"], baseline["test"])
- # this is the only different set from the baseline
- nose.tools.eq_(len(dataset["__train__"]), 58)
- for sample in dataset["__train__"]:
- assert 3 <= len(sample) <= 4
- assert isinstance(sample[0], str)
- nose.tools.eq_(sample[1].shape, (3, 1168, 1648)) #planes, height, width
- nose.tools.eq_(sample[1].dtype, torch.float32)
- nose.tools.eq_(sample[2].shape, (1, 1168, 1648)) #planes, height, width
- nose.tools.eq_(sample[2].dtype, torch.float32)
- if len(sample) == 4:
- nose.tools.eq_(sample[3].shape, (1, 1168, 1648))
- nose.tools.eq_(sample[3].dtype, torch.float32)
+ # these are the only different sets from the baseline
+ for key in ("__train__", "train"):
+ nose.tools.eq_(len(dataset[key]), 118)
+ for sample in dataset[key]:
+ assert 3 <= len(sample) <= 4
+ assert isinstance(sample[0], str)
+ nose.tools.eq_(sample[1].shape, (3, 1168, 1648))
+ nose.tools.eq_(sample[1].dtype, torch.float32)
+ nose.tools.eq_(sample[2].shape, (1, 1168, 1648))
+ nose.tools.eq_(sample[2].dtype, torch.float32)
+ if len(sample) == 4:
+ nose.tools.eq_(sample[3].shape, (1, 1168, 1648))
+ nose.tools.eq_(sample[3].dtype, torch.float32)
@rc_variable_set("bob.ip.binseg.iostar.datadir")
@@ -405,7 +410,7 @@ def test_iostar():
for m in ("vessel", "optic_disc"):
d = importlib.import_module(f"...configs.datasets.iostar.{m}",
package=__name__).dataset
- nose.tools.eq_(len(d), 3)
+ nose.tools.eq_(len(d), 4)
_check_subset(d["__train__"], 20)
_check_subset(d["train"], 20)
_check_subset(d["test"], 10)
@@ -419,7 +424,7 @@ def test_iostar():
def test_iostar_mtest():
from ..configs.datasets.iostar.vessel_mtest import dataset
- nose.tools.eq_(len(dataset), 6)
+ nose.tools.eq_(len(dataset), 10)
from ..configs.datasets.iostar.vessel import dataset as baseline
nose.tools.eq_(dataset["train"], baseline["train"])
@@ -446,24 +451,25 @@ def test_iostar_mtest():
def test_iostar_covd():
from ..configs.datasets.iostar.covd import dataset
- nose.tools.eq_(len(dataset), 3)
+ nose.tools.eq_(len(dataset), 4)
from ..configs.datasets.iostar.vessel import dataset as baseline
- nose.tools.eq_(dataset["train"], baseline["train"])
+ nose.tools.eq_(dataset["train"], dataset["__valid__"])
nose.tools.eq_(dataset["test"], baseline["test"])
- # this is the only different set from the baseline
- nose.tools.eq_(len(dataset["__train__"]), 53)
- for sample in dataset["__train__"]:
- assert 3 <= len(sample) <= 4
- assert isinstance(sample[0], str)
- nose.tools.eq_(sample[1].shape, (3, 1024, 1024)) #planes, height, width
- nose.tools.eq_(sample[1].dtype, torch.float32)
- nose.tools.eq_(sample[2].shape, (1, 1024, 1024)) #planes, height, width
- nose.tools.eq_(sample[2].dtype, torch.float32)
- if len(sample) == 4:
- nose.tools.eq_(sample[3].shape, (1, 1024, 1024))
- nose.tools.eq_(sample[3].dtype, torch.float32)
+ # these are the only different sets from the baseline
+ for key in ("__train__", "train"):
+ nose.tools.eq_(len(dataset[key]), 133)
+ for sample in dataset[key]:
+ assert 3 <= len(sample) <= 4
+ assert isinstance(sample[0], str)
+ nose.tools.eq_(sample[1].shape, (3, 1024, 1024))
+ nose.tools.eq_(sample[1].dtype, torch.float32)
+ nose.tools.eq_(sample[2].shape, (1, 1024, 1024))
+ nose.tools.eq_(sample[2].dtype, torch.float32)
+ if len(sample) == 4:
+ nose.tools.eq_(sample[3].shape, (1, 1024, 1024))
+ nose.tools.eq_(sample[3].dtype, torch.float32)
@rc_variable_set("bob.ip.binseg.refuge.datadir")
@@ -482,7 +488,7 @@ def test_refuge():
for m in ("disc", "cup"):
d = importlib.import_module(f"...configs.datasets.refuge.{m}",
package=__name__).dataset
- nose.tools.eq_(len(d), 4)
+ nose.tools.eq_(len(d), 5)
_check_subset(d["__train__"], 400)
_check_subset(d["train"], 400)
_check_subset(d["validation"], 400)
@@ -505,7 +511,7 @@ def test_drishtigs1():
for m in ("disc_all", "cup_all", "disc_any", "cup_any"):
d = importlib.import_module(f"...configs.datasets.drishtigs1.{m}",
package=__name__).dataset
- nose.tools.eq_(len(d), 3)
+ nose.tools.eq_(len(d), 4)
_check_subset(d["__train__"], 50)
_check_subset(d["train"], 50)
_check_subset(d["test"], 51)
@@ -527,7 +533,7 @@ def test_rimoner3():
for m in ("disc_exp1", "cup_exp1", "disc_exp2", "cup_exp2"):
d = importlib.import_module(f"...configs.datasets.rimoner3.{m}",
package=__name__).dataset
- nose.tools.eq_(len(d), 3)
+ nose.tools.eq_(len(d), 4)
_check_subset(d["__train__"], 99)
_check_subset(d["train"], 99)
_check_subset(d["test"], 60)
@@ -549,7 +555,7 @@ def test_drionsdb():
for m in ("expert1", "expert2"):
d = importlib.import_module(f"...configs.datasets.drionsdb.{m}",
package=__name__).dataset
- nose.tools.eq_(len(d), 3)
+ nose.tools.eq_(len(d), 4)
_check_subset(d["__train__"], 60)
_check_subset(d["train"], 60)
_check_subset(d["test"], 50)
--
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