Move off of old demodata

tests/test_spatial_verification.py

@@ -131,7 +131,7 @@ def get_dummy_test_vars():
     return chip1, chip2, kpts1, kpts2, fm
 
 
-def get_dummy_test_vars1(fname1='easy1.png', fname2='easy2.png'):
+def get_dummy_test_vars1(fname1='tsukuba_r', fname2='tsukuba_l'):
     import utool as ut
     from vtool_ibeis import image as gtool
     from vtool_ibeis import features as feattool

vtool_ibeis/coverage_grid.py

@@ -34,7 +34,7 @@ def make_grid_coverage_mask(kpts, chipsize, weights, pxl_per_bin=4,
         >>> from vtool_ibeis.coverage_grid import *  # NOQA
         >>> import vtool_ibeis as vt
         >>> # build test data
-        >>> kpts, chipsize, weights = coverage_kpts.testdata_coverage('easy1.png')
+        >>> kpts, chipsize, weights = coverage_kpts.testdata_coverage('tsukuba_l')
         >>> pxl_per_bin = 4
         >>> grid_steps = 2
         >>> # execute function
@@ -323,7 +323,7 @@ def gridsearch_coverage_grid_mask():
     """
     import plottool_ibeis as pt
     cfgdict_list, cfglbl_list = get_coverage_grid_gridsearch_configs()
-    kpts, chipsize, weights = coverage_kpts.testdata_coverage('easy1.png')
+    kpts, chipsize, weights = coverage_kpts.testdata_coverage('astro')
     gridmask_list = [
         255 *  make_grid_coverage_mask(kpts, chipsize, weights, **cfgdict)
         for cfgdict in ub.ProgIter(cfgdict_list, desc='coverage grid')

vtool_ibeis/coverage_kpts.py

@@ -434,7 +434,8 @@ def gridsearch_kpts_coverage_mask():
     """
     import plottool_ibeis as pt
     cfgdict_list, cfglbl_list = get_coverage_kpts_gridsearch_configs()
-    kpts, chipsize, weights = testdata_coverage('easy1.png')
+    # kpts, chipsize, weights = testdata_coverage('easy1.png')
+    kpts, chipsize, weights = testdata_coverage('astro')
     imgmask_list = [
         255 *  make_kpts_coverage_mask(kpts, chipsize, weights,
                                        return_patch=False, **cfgdict)
@@ -459,18 +460,18 @@ def testdata_coverage(fname=None):
     # build test data
     kpts, vecs = vt.demodata.get_testdata_kpts(fname, with_vecs=True)
     # HACK IN DISTINCTIVENESS
-    if fname is not None:
-        from ibeis.algo.hots import distinctiveness_normalizer
-        cachedir = ub.ensure_app_cache_dir('ibeis', 'distinctiveness_model')
-        species = 'zebra_plains'
-        dstcnvs_normer = distinctiveness_normalizer.DistinctivnessNormalizer(species, cachedir=cachedir)
-        dstcnvs_normer.load(cachedir)
-        weights = dstcnvs_normer.get_distinctiveness(vecs)
-    else:
-        kpts = np.vstack((kpts, [0, 0, 1, 1, 1, 0]))
-        kpts = np.vstack((kpts, [0.01, 10, 1, 1, 1, 0]))
-        kpts = np.vstack((kpts, [0.94, 11.5, 1, 1, 1, 0]))
-        weights = np.ones(len(kpts))
+    # if fname is not None:
+    #     from ibeis.algo.hots import distinctiveness_normalizer
+    #     cachedir = ub.ensure_app_cache_dir('ibeis', 'distinctiveness_model')
+    #     species = 'zebra_plains'
+    #     dstcnvs_normer = distinctiveness_normalizer.DistinctivnessNormalizer(species, cachedir=cachedir)
+    #     dstcnvs_normer.load(cachedir)
+    #     weights = dstcnvs_normer.get_distinctiveness(vecs)
+    # else:
+    kpts = np.vstack((kpts, [0, 0, 1, 1, 1, 0]))
+    kpts = np.vstack((kpts, [0.01, 10, 1, 1, 1, 0]))
+    kpts = np.vstack((kpts, [0.94, 11.5, 1, 1, 1, 0]))
+    weights = np.ones(len(kpts))
     chipsize = tuple(vt.iceil(vt.get_kpts_image_extent(kpts)[2:4]).tolist())
     return kpts, chipsize, weights
 

vtool_ibeis/demodata.py

@@ -633,7 +633,7 @@ def get_testdata_kpts(fname=None, with_vecs=False):
         return kpts
 
 
-def testdata_ratio_matches(fname1='easy1.png', fname2='easy2.png', **kwargs):
+def testdata_ratio_matches(fname1='tsukuba_r', fname2='tsukuba_l', **kwargs):
     r"""
     Runs simple ratio-test matching between two images.
     Technically this is not demodata data.
@@ -659,8 +659,8 @@ def testdata_ratio_matches(fname1='easy1.png', fname2='easy2.png', **kwargs):
         >>> # xdoctest: +REQUIRES(module:pyhesaff)
         >>> from vtool_ibeis.demodata import *  # NOQA
         >>> import vtool_ibeis as vt
-        >>> fname1 = ut.get_argval('--fname1', type_=str, default='easy1.png')
-        >>> fname2 = ut.get_argval('--fname2', type_=str, default='easy2.png')
+        >>> fname1 = ut.get_argval('--fname1', type_=str, default='tsukuba_l')
+        >>> fname2 = ut.get_argval('--fname2', type_=str, default='tsukuba_r')
         >>> default_dict = vt.get_extract_features_default_params()
         >>> default_dict['ratio_thresh'] = .625
         >>> kwargs = ut.argparse_dict(default_dict)

vtool_ibeis/inspect_matches.py

@@ -69,8 +69,8 @@ class MatchInspector(INSPECT_BASE):
         >>> import vtool_ibeis as vt
         >>> gt.ensure_qapp()
         >>> ut.qtensure()
-        >>> annot1 = lazy_test_annot('easy1.png')
-        >>> annot2 = lazy_test_annot('easy2.png')
+        >>> annot1 = lazy_test_annot('tsukuba_r')
+        >>> annot2 = lazy_test_annot('tsukuba_l')
         >>> match = vt.PairwiseMatch(annot1, annot2)
         >>> self = MatchInspector(match=match)
         >>> self.show()

vtool_ibeis/matching.py

@@ -107,8 +107,8 @@ def demodata_match(cfgdict={}, apply=True, use_cache=True, recompute=False):
         enabled=use_cache
     )
     match = cacher.tryload()
-    annot1 = lazy_test_annot('easy1.png')
-    annot2 = lazy_test_annot('easy2.png')
+    annot1 = lazy_test_annot('tsukuba_l')
+    annot2 = lazy_test_annot('tsukuba_r')
     if match is None or recompute:
         match = vt.PairwiseMatch(annot1, annot2)
         if apply:
@@ -141,8 +141,10 @@ class PairwiseMatch(ub.NiceRepr):
         >>> # xdoctest: +REQUIRES(module:pyhesaff)
         >>> from vtool_ibeis.matching import *  # NOQA
         >>> import vtool_ibeis as vt
-        >>> imgR = vt.imread(ut.grab_test_imgpath('easy1.png'))
-        >>> imgL = vt.imread(ut.grab_test_imgpath('easy2.png'))
+        >>> #imgR = vt.imread(ut.grab_test_imgpath('easy1.png'))
+        >>> #imgL = vt.imread(ut.grab_test_imgpath('easy2.png'))
+        >>> imgR = vt.imread(ut.grab_test_imgpath('tsukuba_r'))
+        >>> imgL = vt.imread(ut.grab_test_imgpath('tsukuba_l'))
         >>> annot1 = {'rchip': imgR}
         >>> annot2 = {'rchip': imgL}
         >>> match = vt.PairwiseMatch(annot1, annot2)
@@ -162,8 +164,8 @@ class PairwiseMatch(ub.NiceRepr):
         >>> match.ishow()
         >>> from vtool_ibeis.matching import *  # NOQA
         >>> import vtool_ibeis as vt
-        >>> imgR = vt.imread(ut.grab_test_imgpath('easy1.png'))
-        >>> imgL = vt.imread(ut.grab_test_imgpath('easy2.png'))
+        >>> imgR = vt.imread(ut.grab_test_imgpath('tsukuba_r'))
+        >>> imgL = vt.imread(ut.grab_test_imgpath('tsukuba_l'))
         >>> annot1 = {'rchip': imgR}
         >>> annot2 = {'rchip': imgL}
         >>> match = vt.PairwiseMatch(annot1, annot2)
@@ -1449,7 +1451,7 @@ def ensure_metadata_feats(annot, cfgdict={}):
         >>> # ENABLE_DOCTEST
         >>> # xdoctest: +REQUIRES(module:pyhesaff)
         >>> from vtool_ibeis.matching import *  # NOQA
-        >>> rchip_fpath = ut.grab_test_imgpath('easy1.png')
+        >>> rchip_fpath = ut.grab_test_imgpath('astro')
         >>> annot = ut.LazyDict({'rchip_fpath': rchip_fpath})
         >>> cfgdict = {}
         >>> ensure_metadata_feats(annot, cfgdict)

vtool_ibeis/nearest_neighbors.py

@@ -109,8 +109,10 @@ def test_cv2_flann():
     from vtool_ibeis import demodata
     import plottool_ibeis as pt
     import vtool_ibeis as vt
-    img1 = vt.imread(ut.grab_test_imgpath('easy1.png'))
-    img2 = vt.imread(ut.grab_test_imgpath('easy2.png'))
+    # img1 = vt.imread(ut.grab_test_imgpath('easy1.png'))
+    # img2 = vt.imread(ut.grab_test_imgpath('easy2.png'))
+    img1 = vt.imread(ut.grab_test_imgpath('tsukuba_l'))
+    img2 = vt.imread(ut.grab_test_imgpath('tsukuba_r'))
 
     stereo = cv2.StereoBM_create(numDisparities=16, blockSize=15)
     disparity = stereo.compute(img1, img2)

vtool_ibeis/segmentation.py

@@ -85,7 +85,7 @@ def demo_grabcut(bgr_img):
         >>> import utool as ut
         >>> import plottool_ibeis as pt
         >>> import vtool_ibeis as vt
-        >>> img_fpath = ut.grab_test_imgpath('easy1.png')
+        >>> img_fpath = ut.grab_test_imgpath('astro')
         >>> bgr_img = vt.imread(img_fpath)
         >>> # execute function
         >>> print(bgr_img.shape)

vtool_ibeis/spatial_verification.py

@@ -374,8 +374,8 @@ def testdata_matching_affine_inliers():
     ori_thresh = 1.57
     xy_thresh_sqrd = dlen_sqrd2 * xy_thresh
     featkw = ut.argparse_dict(vt.get_extract_features_default_params())
-    fname1 = ut.get_argval('--fname1', type_=str, default='easy1.png')
-    fname2 = ut.get_argval('--fname2', type_=str, default='easy2.png')
+    fname1 = ut.get_argval('--fname1', type_=str, default='tsukuba_l')
+    fname2 = ut.get_argval('--fname2', type_=str, default='tsukuba_r')
     (kpts1, kpts2, fm, fs, rchip1, rchip2) = demodata.testdata_ratio_matches(fname1, fname2, **featkw)
     aff_inliers, aff_errors, Aff = get_best_affine_inliers_(
         kpts1, kpts2, fm, fs, xy_thresh_sqrd, scale_thresh, ori_thresh)