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petercorke merged 1 commit into from
Oct 3, 2026
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test: remove bare except from point-feature and core-op tests #114

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221 changes: 97 additions & 124 deletions tests/test_image_point_features.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,7 @@
#!/usr/bin/env python

import os
import tempfile
import unittest

import numpy as np
Expand All @@ -15,118 +17,103 @@ def test_copy(self):
img = Image.Read("monalisa.png")
img_copy = img.copy()
self.assertEqual(img_copy.shape, img.shape)
nt.assert_array_equal(img_copy.A, img.A)
nt.assert_array_equal(img_copy.array, img.array)

def test_write_read_roundtrip(self):
"""Test writing and reading back an image"""
"""Test writing and reading back an image (PNG is lossless)"""
img = Image.Read("monalisa.png", dtype="uint8")

try:
# Write to file
import tempfile

with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as f:
fname = f.name

with tempfile.TemporaryDirectory() as tmpdir:
fname = os.path.join(tmpdir, "roundtrip.png")
img.write(fname)

# Read back
img_read = Image.Read(fname)
self.assertEqual(img_read.shape, img.shape)

# Clean up
import os

os.unlink(fname)
except Exception:
pass
self.assertEqual(img_read.shape, img.shape)
nt.assert_array_equal(img_read.array, img.array)

def test_colorspace_conversion_roundtrip(self):
"""Test colorspace conversions"""
img = Image.Read("flowers1.png")

# RGB to HSV and back
try:
hsv = img.colorspace("hsv", src="rgb")
self.assertEqual(hsv.nplanes, 3)
except:
pass
# RGB to HSV
hsv = img.colorspace("hsv", src="rgb")
self.assertEqual(hsv.nplanes, 3)
self.assertEqual(hsv.shape[:2], img.shape[:2])

# RGB to lab
try:
lab = img.colorspace("lab")
self.assertEqual(lab.nplanes, 3)
except:
pass
lab = img.colorspace("lab")
self.assertEqual(lab.nplanes, 3)
self.assertEqual(lab.shape[:2], img.shape[:2])

def test_cast_operations(self):
"""Test image type casting"""
# float to uint8
img_float = Image(np.random.rand(10, 10))
img_uint8 = img_float.array_as("uint8")
self.assertEqual(img_uint8.dtype, np.uint8)

try:
# Cast to uint8
img_uint8 = img_float.array_as("uint8")
self.assertEqual(img_uint8.dtype, np.uint8)
except:
pass

try:
# Cast to float
img_uint8 = Image(np.random.rand(10, 10) * 255, dtype="uint8")
img_float2 = img_uint8.array_as("float32")
self.assertTrue(np.issubdtype(img_float2.dtype, np.floating))
except:
pass
# uint8 to float
img_uint8 = Image(np.random.rand(10, 10) * 255, dtype="uint8")
img_float2 = img_uint8.array_as("float32")
self.assertEqual(img_float2.dtype, np.float32)

def test_matrix_conversion(self):
"""Test matrix/array conversion"""
img = Image(np.random.rand(10, 10, 3))

# To array
arr = img.A
arr = img.array
self.assertEqual(arr.shape, img.shape)

def test_concat(self):
"""Test image concatenation"""
def test_hstack(self):
"""Test horizontal concatenation"""
img1 = Image(np.random.rand(10, 10))
img2 = Image(np.random.rand(10, 10))

stacked = Image.Hstack([img1, img2], sep=0)
self.assertEqual(stacked.shape, (10, 20))
nt.assert_array_equal(stacked.array[:, :10], img1.array)
nt.assert_array_equal(stacked.array[:, 10:], img2.array)

# a separator adds columns between the images
stacked = Image.Hstack([img1, img2], sep=2)
self.assertEqual(stacked.shape, (10, 22))

def test_vstack(self):
"""Test vertical concatenation"""
img1 = Image(np.random.rand(10, 10))
img2 = Image(np.random.rand(10, 10))

try:
# Horizontal concatenation
concat_h = img1.concat(img2, "h")
self.assertEqual(concat_h.shape[0], img1.shape[0])
self.assertEqual(concat_h.shape[1], img1.shape[1] + img2.shape[1])
except:
pass

try:
# Vertical concatenation
concat_v = img1.concat(img2, "v")
self.assertEqual(concat_v.shape[0], img1.shape[0] + img2.shape[0])
self.assertEqual(concat_v.shape[1], img1.shape[1])
except:
pass
stacked = Image.Vstack([img1, img2], sep=0)
self.assertEqual(stacked.shape, (20, 10))
nt.assert_array_equal(stacked.array[:10, :], img1.array)
nt.assert_array_equal(stacked.array[10:, :], img2.array)

# a separator adds rows between the images
stacked = Image.Vstack([img1, img2], sep=2)
self.assertEqual(stacked.shape, (22, 10))

def test_interp2d(self):
"""Test 2D interpolation"""
"""Test 2D interpolation: sampling at integer pixel coordinates must
reproduce the image values"""
img = Image.Read("monalisa.png", mono=True, dtype="float32")

try:
# Interpolate at specific points
interp = img.interp2d(np.array([100, 200]), np.array([150, 250]))
self.assertIsNotNone(interp)
except:
pass
# U, V are (Ho, Wo) coordinate arrays for the output image
U, V = np.meshgrid(np.arange(100, 110), np.arange(150, 160))
interp = img.interp2d(U, V)

self.assertEqual(interp.shape, (10, 10))
nt.assert_allclose(interp.array, img.array[150:160, 100:110], rtol=1e-5)

def test_get_pixel(self):
"""Test getting pixel values"""
img = Image(np.random.rand(10, 10))
"""Test getting pixel values; the arguments are (u, v), i.e. (column,
row), the opposite order to NumPy indexing"""
img = Image(np.random.rand(10, 12))
self.assertEqual(img.pixel(5, 3), img.array[3, 5])

try:
val = img.getpixel(5, 5)
self.assertIsNotNone(val)
except:
pass
# color image: result is a vector over planes
img3 = Image(np.random.rand(10, 12, 3))
nt.assert_array_equal(img3.pixel(5, 3), img3.array[3, 5, :])


class TestImagePointFeatures(unittest.TestCase):
Expand All @@ -135,31 +122,26 @@ def test_sift(self):
"""Test SIFT feature detection"""
img = Image.Read("monalisa.png", mono=True)

try:
sift = img.SIFT()
self.assertGreater(len(sift), 0)
except:
pass
sift = img.SIFT()
self.assertGreater(len(sift), 0)

@unittest.skip(
"Image.SURF() is not implemented, and SURF is non-free in pip OpenCV "
"builds; see https://github.com/petercorke/machinevision-toolbox-python/issues/113"
)
def test_surf(self):
"""Test SURF feature detection"""
img = Image.Read("flowers1.png", mono=True)

try:
surf = img.SURF()
self.assertGreater(len(surf), 0)
except:
pass
surf = img.SURF()
self.assertGreater(len(surf), 0)

def test_orb(self):
"""Test ORB feature detection"""
img = Image.Read("monalisa.png", mono=True)

try:
orb = img.ORB()
self.assertGreater(len(orb), 0)
except:
pass
orb = img.ORB()
self.assertGreater(len(orb), 0)

def test_match_orb_auto_metric(self):
"""match() must auto-select hamming distance for binary (ORB)
Expand Down Expand Up @@ -187,15 +169,12 @@ def test_match_orb_auto_metric(self):
m_sift_l2 = sift1.match(sift2, metric="L2")
self.assertEqual(len(m_sift_auto), len(m_sift_l2))

def test_corners(self):
"""Test corner detection"""
def test_harris(self):
"""Test Harris corner detection"""
img = Image.Read("monalisa.png", mono=True)

try:
corners = img.corners()
self.assertGreater(len(corners), 0)
except:
pass
corners = img.Harris()
self.assertGreater(len(corners), 0)

def test_draw2(self):
"""draw2() with a named color and a colorized (colororder-bearing)
Expand All @@ -212,21 +191,16 @@ def test_draw2(self):
def test_features_list_operations(self):
"""Test feature list operations"""
img = Image.Read("monalisa.png", mono=True)
sift = img.SIFT()
self.assertGreater(len(sift), 5)

try:
sift = img.SIFT()

# Test slicing
if len(sift) > 5:
slice_sift = sift[:5]
self.assertEqual(len(slice_sift), 5)
# Test slicing
slice_sift = sift[:5]
self.assertEqual(len(slice_sift), 5)

# Test indexing
if len(sift) > 0:
first_feature = sift[0]
self.assertIsNotNone(first_feature)
except:
pass
# Test indexing
first_feature = sift[0]
self.assertEqual(len(first_feature), 1)

def test_gridify_scalar_nbins(self):
"""gridify() with a scalar nbins must not raise (regression: numpy
Expand Down Expand Up @@ -266,20 +240,19 @@ def test_akaze(self):
def test_feature_properties(self):
"""Test feature properties"""
img = Image.Read("monalisa.png", mono=True)

try:
sift = img.SIFT()

if len(sift) > 0:
# Get properties
uv = sift.uv
self.assertIsNotNone(uv)

# Get strength
strength = sift.strength
self.assertIsNotNone(strength)
except:
pass
sift = img.SIFT()
n = len(sift)
self.assertGreater(n, 0)

# coordinates: u, v are per-feature lists, p is a 2xN array
self.assertEqual(len(sift.u), n)
self.assertEqual(len(sift.v), n)
self.assertEqual(sift.p.shape, (2, n))
nt.assert_array_equal(sift.p[0, :], sift.u)
nt.assert_array_equal(sift.p[1, :], sift.v)

# strength
self.assertEqual(len(sift.strength), n)


if __name__ == "__main__":
Expand Down
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