Merge branch 'MarvinTeichmann-unittest'

Author: lucasb-eyer

.gitignore

@@ -5,3 +5,54 @@ build
 
 pydensecrf/eigen.cpp
 pydensecrf/densecrf.cpp
+
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+env/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+.hypothesis/
+

MANIFEST.in

@@ -0,0 +1,5 @@
+include pydensecrf/eigen.pxd
+include pydensecrf/eigen.pyx
+include pydensecrf/densecrf.pxd
+include pydensecrf/densecrf.pyx
+recursive-include pydensecrf/densecrf *

README.md

@@ -16,7 +16,9 @@ and provide a link to this repository as a footnote or a citation.
 Installation
 ============
 
-You can install this using `pip` by executing:
+The package is on PyPI, so simply run `pip install pydensecrf` to install it.
+
+If you want the newest and freshest version, you can install it by executing:
 
 ```
 pip install git+https://github.com/lucasb-eyer/pydensecrf.git
@@ -101,10 +103,14 @@ d.addPairwiseGaussian(sxy=3, compat=3)
 d.addPairwiseBilateral(sxy=80, srgb=13, rgbim=im, compat=10)
 ```
 
+### Non-RGB bilateral
+
 An important caveat is that `addPairwiseBilateral` only works for RGB images, i.e. three channels.
 If your data is of different type than this simple but common case, you'll need to compute your
 own pairwise energy using `utils.create_pairwise_bilateral`; see the [generic non-2D case](https://github.com/lucasb-eyer/pydensecrf#generic-non-2d) for details.
 
+A good [example of working with Non-RGB data](https://github.com/lucasb-eyer/pydensecrf/blob/master/examples/Non%20RGB%20Example.ipynb) is provided as a notebook in the examples folder.
+
 ### Compatibilities
 
 The `compat` argument can be any of the following:
@@ -145,6 +151,7 @@ According to the paper, `w(2)` was set to 1 and `w(1)` was cross-validated, but
 Looking through Philip's code (included in [pydensecrf/densecrf](https://github.com/lucasb-eyer/pydensecrf/tree/master/pydensecrf/densecrf)),
 I couldn't find such explicit weights, and my guess is they are thus hard-coded to 1.
 If anyone knows otherwise, please open an issue or, better yet, a pull-request.
+Update: user @waldol1 has an idea in [this issue](https://github.com/lucasb-eyer/pydensecrf/issues/37). Feel free to try it out!
 
 Inference
 ---------
@@ -230,3 +237,24 @@ Common Problems
 ---------------------------------
 
 If while importing pydensecrf you get an error about some undefined symbols (for example `.../pydensecrf/densecrf.so: undefined symbol: _ZTINSt8ios_base7failureB5cxx11E`), you most likely are inadvertently mixing different compilers or toolchains. Try to see what's going on using tools like `ldd`. If you're using Anaconda, [running `conda install libgcc` might be a solution](https://github.com/lucasb-eyer/pydensecrf/issues/28).
+
+Maintaining
+===========
+
+These are instructions for maintainers about how to release new versions. (Mainly instructions for myself.)
+
+```
+# Go increment the version in setup.py
+> python setup.py build_ext
+> python setup.py sdist
+> twine upload dist/pydensecrf-VERSION_NUM.tar.gz
+```
+
+And that's it. At some point, it would be cool to automate this on [TravisCI](https://docs.travis-ci.com/user/deployment/pypi/), but not worth it yet.
+At that point, looking into [creating "manylinux" wheels](https://github.com/pypa/python-manylinux-demo) might be nice, too.
+
+Testing
+=======
+
+Thanks to @MarvinTeichmann we now have proper tests, install the package and run `py.test`.
+Maybe there's a better way to run them, but both of us don't know :smile:

pydensecrf/densecrf.pxd

@@ -86,6 +86,8 @@ cdef extern from "densecrf/include/densecrf.h":
 
 cdef class DenseCRF:
     cdef c_DenseCRF *_this
+    cdef int _nlabel
+    cdef int _nvar
 
 
 cdef class DenseCRF2D(DenseCRF):

pydensecrf/densecrf.pyx

@@ -59,19 +59,30 @@ cdef class DenseCRF:
         else:
             self._this = NULL
 
+        self._nvar = nvar
+        self._nlabel = nlabels
+
     def __dealloc__(self):
         # Because destructors are virtual, this is enough to delete any object
         # of child classes too.
         if self._this:
             del self._this
 
     def addPairwiseEnergy(self, float[:,::1] features not None, compat, KernelType kernel=DIAG_KERNEL, NormalizationType normalization=NORMALIZE_SYMMETRIC):
+        if features.shape[1] != self._nvar:
+            raise ValueError("Bad shape for pairwise energy (Need (?, {}), got {})".format(self._nvar, (features.shape[0], features.shape[1])))
+
         self._this.addPairwiseEnergy(eigen.c_matrixXf(features), _labelcomp(compat), kernel, normalization)
 
     def setUnary(self, Unary u):
         self._this.setUnaryEnergy(u.move())
 
     def setUnaryEnergy(self, float[:,::1] u not None, float[:,::1] f = None):
+        if u.shape[0] != self._nlabel or u.shape[1] != self._nvar:
+            raise ValueError("Bad shape for unary energy (Need {}, got {})".format((self._nlabel, self._nvar), (u.shape[0], u.shape[1])))
+        # TODO: I don't remember the exact shape `f` should have, so I'm not putting an assertion here.
+        #       If you get hit by a wrong shape of `f`, please open an issue with the necessary info!
+
         if f is None:
             self._this.setUnaryEnergy(eigen.c_matrixXf(u))
         else:
@@ -102,6 +113,10 @@ cdef class DenseCRF2D(DenseCRF):
         self._w = w
         self._h = h
 
+        # Also set these for the superclass
+        self._nvar = w*h
+        self._nlabel = nlabels
+
     def addPairwiseGaussian(self, sxy, compat, KernelType kernel=DIAG_KERNEL, NormalizationType normalization=NORMALIZE_SYMMETRIC):
         if isinstance(sxy, Number):
             sxy = (sxy, sxy)

pydensecrf/test.py

@@ -0,0 +1,99 @@
+import numpy as np
+import pydensecrf.densecrf as dcrf
+import pydensecrf.utils as utils
+
+import pytest
+
+
+def _get_simple_unary():
+    unary1 = np.zeros((10, 10), dtype=np.float32)
+    unary1[:, [0, -1]] = unary1[[0, -1], :] = 1
+
+    unary2 = np.zeros((10, 10), dtype=np.float32)
+    unary2[4:7, 4:7] = 1
+
+    unary = np.vstack([unary1.flat, unary2.flat])
+    unary = (unary + 1) / (np.sum(unary, axis=0) + 2)
+
+    return unary
+
+
+def _get_simple_img():
+
+    img = np.zeros((10, 10, 3), dtype=np.uint8)
+    img[2:8, 2:8, :] = 255
+
+    return img
+
+
+def test_call_dcrf2d():
+
+    d = dcrf.DenseCRF2D(10, 10, 2)
+
+    unary = _get_simple_unary()
+    img = _get_simple_img()
+
+    d.setUnaryEnergy(-np.log(unary))
+    # d.setUnaryEnergy(PyConstUnary(-np.log(Up)))
+
+    d.addPairwiseBilateral(sxy=2, srgb=2, rgbim=img, compat=3)
+    # d.addPairwiseBilateral(2, 2, img, 3)
+    np.argmax(d.inference(10), axis=0).reshape(10, 10)
+
+
+def test_call_dcrf():
+
+    d = dcrf.DenseCRF(100, 2)
+
+    unary = _get_simple_unary()
+    img = _get_simple_img()
+
+    d.setUnaryEnergy(-np.log(unary))
+    # d.setUnaryEnergy(PyConstUnary(-np.log(Up)))
+
+    feats = utils.create_pairwise_bilateral(sdims=(2, 2), schan=2,
+                                            img=img, chdim=2)
+
+    d.addPairwiseEnergy(feats, compat=3)
+    # d.addPairwiseBilateral(2, 2, img, 3)
+    np.argmax(d.inference(10), axis=0).reshape(10, 10)
+
+
+def test_call_dcrf_eq_dcrf2d():
+
+    d = dcrf.DenseCRF(100, 2)
+    d2 = dcrf.DenseCRF2D(10, 10, 2)
+
+    unary = _get_simple_unary()
+    img = _get_simple_img()
+
+    d.setUnaryEnergy(-np.log(unary))
+    d2.setUnaryEnergy(-np.log(unary))
+
+    feats = utils.create_pairwise_bilateral(sdims=(2, 2), schan=2,
+                                            img=img, chdim=2)
+
+    d.addPairwiseEnergy(feats, compat=3)
+
+    d2.addPairwiseBilateral(sxy=2, srgb=2, rgbim=img, compat=3)
+    # d.addPairwiseBilateral(2, 2, img, 3)
+    res1 = np.argmax(d.inference(10), axis=0).reshape(10, 10)
+    res2 = np.argmax(d2.inference(10), axis=0).reshape(10, 10)
+
+    assert(np.all(res1 == res2))
+
+
+def test_compact_wrong():
+
+    # Tests whether expection is indeed raised
+    ##########################################
+
+    # Via e-mail: crash when non-float32 compat
+    d = dcrf.DenseCRF2D(10, 10, 2)
+    d.setUnaryEnergy(np.ones((2, 10 * 10), dtype=np.float32))
+    compat = np.array([1.0, 2.0])
+
+    with pytest.raises(ValueError):
+        d.addPairwiseBilateral(sxy=(3, 3), srgb=(3, 3, 3), rgbim=np.zeros(
+            (10, 10, 3), np.uint8), compat=compat)
+        d.inference(2)

pydensecrf/test_eigen.py

@@ -0,0 +1,41 @@
+import numpy as np
+import pydensecrf.eigen as e
+
+import pytest
+
+
+def test_vector_conversion():
+    np_vector = np.random.randn(3).astype(np.float32)
+    c_vector = e.vectorXf(np_vector)
+    assert np.all(np.array(c_vector) == np_vector)
+
+
+def test_matrix_conversion():
+    np_matrix = np.random.randn(3, 3).astype(np.float32)
+    assert(np_matrix.ndim == 2)
+    c_matrix = e.matrixXf(np_matrix)
+    assert np.all(np.array(c_matrix) == np_matrix)
+
+
+def test_wrong_dims():
+    np_matrix = np.random.randn(3, 3, 3).astype(np.float32)
+    assert(np_matrix.ndim == 3)
+    # c_matrix only supports ndim == 2
+    with pytest.raises(ValueError):
+        # Check whether a Value Error is raised
+        e.matrixXf(np_matrix)
+
+
+def test_wrong_type():
+    np_matrix = np.random.randn(3, 3).astype(np.float64)
+    # c_matrix requies type np.float32
+    with pytest.raises(ValueError):
+        # Check whether a Value Error is raised
+        e.matrixXf(np_matrix)
+
+
+def test_none_type():
+    np_matrix = None
+    with pytest.raises(TypeError):
+        # Check whether a Value Error is raised
+        e.matrixXf(np_matrix)