From 5e6d38bccf1e2da6f284a3449f12f2e13f5f7441 Mon Sep 17 00:00:00 2001
From: mdelitroz <maxime.delitroz@idiap.ch>
Date: Wed, 19 Jul 2023 13:39:26 +0200
Subject: [PATCH] updated tests for Montgomery dataset
---
tests/test_mc.py | 137 +++++++++++++++++++++++++++++++++--------------
1 file changed, 98 insertions(+), 39 deletions(-)
diff --git a/tests/test_mc.py b/tests/test_mc.py
index 1b2aa4fd..87de46ea 100644
--- a/tests/test_mc.py
+++ b/tests/test_mc.py
@@ -4,131 +4,190 @@
"""Tests for Montgomery dataset."""
+import importlib
+
import pytest
def test_protocol_consistency():
- from ptbench.data.montgomery import dataset
# Default protocol
- subset = dataset.subsets("default")
+ datamodule = importlib.import_module(
+ "ptbench.data.montgomery.default"
+ ).datamodule
+ subset = datamodule.dataset_split.subsets
+
assert len(subset) == 3
assert "train" in subset
assert len(subset["train"]) == 88
for s in subset["train"]:
- assert s.key.startswith("CXR_png/MCUCXR_0")
+ assert s[0].startswith("CXR_png/MCUCXR_0")
assert "validation" in subset
assert len(subset["validation"]) == 22
for s in subset["validation"]:
- assert s.key.startswith("CXR_png/MCUCXR_0")
+ assert s[0].startswith("CXR_png/MCUCXR_0")
assert "test" in subset
assert len(subset["test"]) == 28
for s in subset["test"]:
- assert s.key.startswith("CXR_png/MCUCXR_0")
+ assert s[0].startswith("CXR_png/MCUCXR_0")
# Check labels
for s in subset["train"]:
- assert s.label in [0.0, 1.0]
+ assert s[1] in [0.0, 1.0]
for s in subset["validation"]:
- assert s.label in [0.0, 1.0]
+ assert s[1] in [0.0, 1.0]
for s in subset["test"]:
- assert s.label in [0.0, 1.0]
+ assert s[1] in [0.0, 1.0]
# Cross-validation fold 0-7
for f in range(8):
- subset = dataset.subsets("fold_" + str(f))
+ datamodule = importlib.import_module(
+ f"ptbench.data.montgomery.fold_{str(f)}"
+ ).datamodule
+ subset = datamodule.database_split.subsets
+
assert len(subset) == 3
assert "train" in subset
assert len(subset["train"]) == 99
for s in subset["train"]:
- assert s.key.startswith("CXR_png/MCUCXR_0")
+ assert s[0].startswith("CXR_png/MCUCXR_0")
assert "validation" in subset
assert len(subset["validation"]) == 25
for s in subset["validation"]:
- assert s.key.startswith("CXR_png/MCUCXR_0")
+ assert s[0].startswith("CXR_png/MCUCXR_0")
assert "test" in subset
assert len(subset["test"]) == 14
for s in subset["test"]:
- assert s.key.startswith("CXR_png/MCUCXR_0")
+ assert s[0].startswith("CXR_png/MCUCXR_0")
# Check labels
for s in subset["train"]:
- assert s.label in [0.0, 1.0]
+ assert s[1] in [0.0, 1.0]
for s in subset["validation"]:
- assert s.label in [0.0, 1.0]
+ assert s[1] in [0.0, 1.0]
for s in subset["test"]:
- assert s.label in [0.0, 1.0]
+ assert s[1] in [0.0, 1.0]
# Cross-validation fold 8-9
for f in range(8, 10):
- subset = dataset.subsets("fold_" + str(f))
+ datamodule = importlib.import_module(
+ f"ptbench.data.montgomery.fold_{str(f)}"
+ ).datamodule
+ subset = datamodule.database_split.subsets
+
assert len(subset) == 3
assert "train" in subset
assert len(subset["train"]) == 100
for s in subset["train"]:
- assert s.key.startswith("CXR_png/MCUCXR_0")
+ assert s[0].startswith("CXR_png/MCUCXR_0")
assert "validation" in subset
assert len(subset["validation"]) == 25
for s in subset["validation"]:
- assert s.key.startswith("CXR_png/MCUCXR_0")
+ assert s[0].startswith("CXR_png/MCUCXR_0")
assert "test" in subset
assert len(subset["test"]) == 13
for s in subset["test"]:
- assert s.key.startswith("CXR_png/MCUCXR_0")
+ assert s[0].startswith("CXR_png/MCUCXR_0")
# Check labels
for s in subset["train"]:
- assert s.label in [0.0, 1.0]
+ assert s[1] in [0.0, 1.0]
for s in subset["validation"]:
- assert s.label in [0.0, 1.0]
+ assert s[1] in [0.0, 1.0]
for s in subset["test"]:
- assert s.label in [0.0, 1.0]
+ assert s[1] in [0.0, 1.0]
@pytest.mark.skip_if_rc_var_not_set("datadir.montgomery")
def test_loading():
- from ptbench.data.montgomery import dataset
+ import torch
+ import torchvision.transforms
+
+ from ptbench.data.datamodule import _DelayedLoadingDataset
def _check_sample(s):
- data = s.data
- assert isinstance(data, dict)
- assert len(data) == 2
-
- assert "data" in data
- assert data["data"].size in (
- (4020, 4892), # portrait
- (4892, 4020), # landscape
- (512, 512), # test database @ CI
+ data = s[0]
+ metadata = s[1]
+
+ assert isinstance(data, torch.Tensor)
+
+ assert data.size in (
+ (1, 4020, 4892), # portrait
+ (1, 4892, 4020), # landscape
+ (1, 512, 512), # test database @ CI
)
- assert data["data"].mode == "L" # Check colors
+ assert (
+ torchvision.transforms.ToPILImage()(data).mode == "L"
+ ) # Check colors
- assert "label" in data
- assert data["label"] in [0, 1] # Check labels
+ assert "label" in metadata
+ assert metadata["label"] in [0, 1] # Check labels
limit = 30 # use this to limit testing to first images only, else None
- subset = dataset.subsets("default")
- for s in subset["train"][:limit]:
+ datamodule = importlib.import_module(
+ "ptbench.data.montgomery.default"
+ ).datamodule
+ subset = datamodule.database_split.subsetss
+ raw_data_loader = datamodule.raw_data_loader
+
+ # Need to use private function so we can limit the number of samples to use
+ dataset = _DelayedLoadingDataset(
+ subset["train"][:limit],
+ raw_data_loader
+ )
+
+ for s in dataset:
_check_sample(s)
@pytest.mark.skip_if_rc_var_not_set("datadir.montgomery")
def test_check():
- from ptbench.data.montgomery import dataset
+ from ptbench.data.split import check_database_split_loading
+
+ limit = 30 # use this to limit testing to first images only, else 0
+
+ # Default protocol
+ datamodule = importlib.import_module(
+ "ptbench.data.montgomery.default"
+ ).datamodule
+ database_split = datamodule.database_split
+ raw_data_loader = datamodule.raw_data_loader
+
+ assert (
+ check_database_split_loading(
+ database_split, raw_data_loader, limit=limit
+ )
+ == 0
+ )
+
+ # Folds
+ for f in range(10):
+ datamodule = importlib.import_module(
+ f"ptbench.data.montgomery.fold_{f}"
+ ).datamodule
+ database_split = datamodule.database_split
+ raw_data_loader = datamodule.raw_data_loader
+
+ assert (
+ check_database_split_loading(
+ database_split, raw_data_loader, limit=limit
+ )
+ == 0
+ )
- assert dataset.check() == 0
--
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