Пример #1
0
 def show_normalizers(match, fnum=None, pnum=None, update=True):
     import plottool as pt
     from plottool import plot_helpers as ph
     # hack keys out of namespace
     keys = ['rchip', 'kpts']
     rchip1, kpts1 = ut.dict_take(match.annot1.__dict__, keys)
     rchip2, kpts2 = ut.dict_take(match.annot2.__dict__, keys)
     fs, fm = match.fs, match.fm_norm
     cmap = 'cool'
     draw_lines = True
     if fnum is None:
         fnum = pt.next_fnum()
     pt.figure(fnum=fnum, pnum=pnum)
     #doclf=True, docla=True)
     ax, xywh1, xywh2 = pt.show_chipmatch2(rchip1,
                                           rchip2,
                                           kpts1,
                                           kpts2,
                                           fm=fm,
                                           fs=fs,
                                           fnum=fnum,
                                           cmap=cmap,
                                           draw_lines=draw_lines)
     ph.set_plotdat(ax, 'viztype', 'matches')
     ph.set_plotdat(ax, 'key', match.key)
     title = match.key + '\n num=%d, sum=%.2f' % (len(fm), sum(fs))
     pt.set_title(title)
     if update:
         pt.update()
     return ax, xywh1, xywh2
Пример #2
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 def visualize_probs(normalizer, update=True, fnum=None, pnum=(1, 1, 1)):
     plot_postbayes_pdf(normalizer.score_domain, 1 - normalizer.p_tp_given_score,
                        normalizer.p_tp_given_score,
                        cfgstr=normalizer.get_cfgstr(), fnum=fnum, pnum=pnum)
     if update:
         import plottool as pt
         pt.update()
Пример #3
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    def show_normalizers(match, fnum=None, pnum=None, update=True):
        import plottool as pt
        from plottool import plot_helpers as ph

        # hack keys out of namespace
        keys = ["rchip", "kpts"]
        rchip1, kpts1 = ut.dict_take(match.annot1.__dict__, keys)
        rchip2, kpts2 = ut.dict_take(match.annot2.__dict__, keys)
        fs, fm = match.fs, match.fm_norm
        cmap = "cool"
        draw_lines = True
        if fnum is None:
            fnum = pt.next_fnum()
        pt.figure(fnum=fnum, pnum=pnum)
        # doclf=True, docla=True)
        ax, xywh1, xywh2 = pt.show_chipmatch2(
            rchip1, rchip2, kpts1, kpts2, fm=fm, fs=fs, fnum=fnum, cmap=cmap, draw_lines=draw_lines
        )
        ph.set_plotdat(ax, "viztype", "matches")
        ph.set_plotdat(ax, "key", match.key)
        title = match.key + "\n num=%d, sum=%.2f" % (len(fm), sum(fs))
        pt.set_title(title)
        if update:
            pt.update()
        return ax, xywh1, xywh2
Пример #4
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    def visualize(normalizer, update=True, verbose=True, fnum=None):
        """
        CommandLine:
            python -m ibeis.algo.hots.score_normalization --test-visualize --index 0
            --cmd

        Example:
            >>> # DISABLE_DOCTEST
            >>> import plottool as pt
            >>> from ibeis.algo.hots.score_normalization import *  # NOQA
            >>> #import ibeis
            >>> index = ut.get_argval('--index', type_=int, default=0)
            >>> normalizer = load_precomputed_normalizer(index, with_global=False)
            >>> normalizer.visualize()
            >>> six.exec_(pt.present(), globals(), locals())

        """
        import plottool as pt
        if verbose:
            print(normalizer.get_infostr())
        if normalizer.score_domain is None:
            return
        if fnum is None:
            fnum = pt.next_fnum()
        pt.figure(fnum=fnum, pnum=(2, 1, 1), doclf=True, docla=True)
        normalizer.visualize_probs(fnum=fnum, pnum=(2, 1, 1), update=False)
        normalizer.visualize_support(fnum=fnum, pnum=(2, 1, 2), update=False)
        if update:
            pt.update()
Пример #5
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 def show_selected(self, event):
     import plottool as pt
     print('show_selected')
     from ibeis.viz import viz_chip
     fnum = pt.ensure_fnum(None)
     print('fnum = %r' % (fnum,))
     pt.figure(fnum=fnum)
     viz_chip.show_many_chips(self.ibs, self.selected_aids)
     pt.update()
Пример #6
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 def show_selected(self, event):
     import plottool as pt
     print('show_selected')
     from ibeis.viz import viz_chip
     fnum = pt.ensure_fnum(None)
     print('fnum = %r' % (fnum, ))
     pt.figure(fnum=fnum)
     viz_chip.show_many_chips(self.ibs, self.selected_aids)
     pt.update()
Пример #7
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 def plot_weights(self, event=None):
     scalars = self.infr.get_scalars()
     import plottool as pt
     inter = pt.ExpandableInteraction(fnum=1)
     for px, (key, vals) in enumerate(scalars.items()):
         print(key + ' = ' + ut.get_stats_str(vals, use_nan=True))
         args = (np.arange(len(vals)), sorted(vals))
         kw = dict(title=key, y_label=key, marker='-o', equal_aspect=False)
         inter.append_partial(pt.plot2, *args, **kw)
     inter.start()
     inter.show_page()
     pt.update()
Пример #8
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 def __init__(self,
              ibs,
              gid,
              next_callback=None,
              prev_callback=None,
              rows_updated_callback=None,
              reset_window=True,
              dodraw=True,
              fnum=None):
     """
     TODO: rename to interact image annotations?
     """
     self.ibs = ibs
     self.gid = gid
     self.rows_updated_callback = rows_updated_callback
     img = ibs.get_images(self.gid)
     self.aid_list = ibs.get_image_aids(self.gid)
     bbox_list = ibs.get_annot_bboxes(self.aid_list)
     #verts_list    = ibs.get_annot_verts(self.aid_list)  # TODO
     theta_list = ibs.get_annot_thetas(self.aid_list)
     species_list = ibs.get_annot_species_texts(self.aid_list)
     #valid_species = ibs.get_all_species_texts()
     valid_species = [tup[1] for tup in ibs.get_working_species()]
     metadata_list = [ibs.get_annot_lazy_dict(aid) for aid in self.aid_list]
     for metadata in metadata_list:
         # eager eval on name
         metadata['name']
     if True:
         interact_annotations.rrr()
     self.interact_ANNOTATIONS = interact_annotations.ANNOTATIONInteraction(
         img,
         bbox_list=bbox_list,
         theta_list=theta_list,
         species_list=species_list,
         metadata_list=metadata_list,
         commit_callback=self.commit_callback,
         # TODO: get default species in a better way
         default_species=self.ibs.cfg.detect_cfg.species_text,
         next_callback=next_callback,
         prev_callback=prev_callback,
         fnum=fnum,
         valid_species=valid_species,
         #figure_to_use=None if reset_window else self.interact_ANNOTATIONS.fig,
     )
     if dodraw:
         pt.update()
Пример #9
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def test_sharpness():
    import ibeis
    defaltdb = 'seaturtles'
    a = ['default']
    ibs = ibeis.opendb(defaultdb=defaltdb)
    ibs, qaids, daids = ibeis.testdata_expanded_aids(ibs=ibs, a=a)
    from vtool import quality_classifier

    contrast_list = [quality_classifier.compute_average_contrast(chip) for chip in ibs.get_annot_chips(qaids)]
    sortx = ut.argsort(contrast_list)[::-1]
    sharpest_qaids = ut.take(qaids, sortx)

    aid = sharpest_qaids[0]
    ut.ensure_pylab_qt4()
    from ibeis import viz
    import plottool as pt
    for aid in ut.InteractiveIter(sharpest_qaids):
        viz.show_chip(ibs, aid, annot=False, nokpts=True)
        pt.update()
Пример #10
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 def __init__(self, ibs, gid, next_callback=None, prev_callback=None,
              rows_updated_callback=None, reset_window=True, dodraw=True,
              fnum=None):
     """
     TODO: rename to interact image annotations?
     """
     self.ibs = ibs
     self.gid = gid
     self.rows_updated_callback = rows_updated_callback
     img = ibs.get_images(self.gid)
     self.aid_list = ibs.get_image_aids(self.gid)
     bbox_list     = ibs.get_annot_bboxes(self.aid_list)
     #verts_list    = ibs.get_annot_verts(self.aid_list)  # TODO
     theta_list    = ibs.get_annot_thetas(self.aid_list)
     species_list  = ibs.get_annot_species_texts(self.aid_list)
     #valid_species = ibs.get_all_species_texts()
     valid_species = [tup[1] for tup in
                      ibs.get_working_species()]
     metadata_list = [ibs.get_annot_lazy_dict(aid) for aid in self.aid_list]
     for metadata in metadata_list:
         # eager eval on name
         metadata['name']
     if True:
         interact_annotations.rrr()
     self.interact_ANNOTATIONS = interact_annotations.ANNOTATIONInteraction(
         img,
         bbox_list=bbox_list,
         theta_list=theta_list,
         species_list=species_list,
         metadata_list=metadata_list,
         commit_callback=self.commit_callback,
         # TODO: get default species in a better way
         default_species=self.ibs.cfg.detect_cfg.species_text,
         next_callback=next_callback,
         prev_callback=prev_callback,
         fnum=fnum,
         valid_species=valid_species,
         #figure_to_use=None if reset_window else self.interact_ANNOTATIONS.fig,
     )
     if dodraw:
         pt.update()
Пример #11
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def test_sharpness():
    import ibeis
    defaltdb = 'seaturtles'
    a = ['default']
    ibs = ibeis.opendb(defaultdb=defaltdb)
    ibs, qaids, daids = ibeis.testdata_expanded_aids(ibs=ibs, a=a)
    from vtool import quality_classifier

    contrast_list = [
        quality_classifier.compute_average_contrast(chip)
        for chip in ibs.get_annot_chips(qaids)
    ]
    sortx = ut.argsort(contrast_list)[::-1]
    sharpest_qaids = ut.take(qaids, sortx)

    aid = sharpest_qaids[0]
    ut.ensure_pylab_qt4()
    from ibeis import viz
    import plottool as pt
    for aid in ut.InteractiveIter(sharpest_qaids):
        viz.show_chip(ibs, aid, annot=False, nokpts=True)
        pt.update()
Пример #12
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def view_training_data(ibs, **kwargs):
    """
    CommandLine:
        python -m ibeis_cnn.ibsplugin --test-view_training_data --db NNP_Master3

    Example:
        >>> # DISABLE_DOCTEST
        >>> from ibeis_cnn.ibsplugin import *  # NOQA
        >>> import ibeis
        >>> # build test data
        >>> ibs = ibeis.opendb(defaultdb='testdb1')
        >>> view_training_data(ibs)
    """
    data_fpath, labels_fpath, training_dpath = get_identify_training_fpaths(
        ibs, **kwargs)
    data = np.load(data_fpath, mmap_mode='r')
    #width = height = base_size * 2  # HACK FIXME
    #channels = 3
    #img_list = utils.convert_data_to_imglist(data, width, height, channels)
    import plottool as pt
    for img in ut.InteractiveIter(data, display_item=False):
        pt.imshow(img)
        pt.update()
Пример #13
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 def show_single_namematch():
     import plottool as pt
     ax = cm.show_single_namematch(qreq_, aid2, mode=0)
     ax = pt.gca()
     ax.figure.canvas.draw()
     pt.update()
Пример #14
0
def export_testset_for_chuck(ibs, min_num_annots):
    """
    Exports a set with some number of annotations that has good demo examples.
    multiple annotations per name and large time variation within names.

    Args:
        ibs (IBEISController):  ibeis controller object

    CommandLine:
        python -m ibeis.other.ibsfuncs --test-export_testset_for_chuck --dbdir /raid/work2/Turk/PZ_Master --min-num-annots 100
        python -m ibeis.other.ibsfuncs --test-export_testset_for_chuck --dbdir /raid/work2/Turk/PZ_Master --min-num-annots 500

        python -m ibeis.other.ibsfuncs --test-export_testset_for_chuck --dbdir /raid/work2/Turk/GZ_Master --min-num-annots 100
        python -m ibeis.other.ibsfuncs --test-export_testset_for_chuck --dbdir
        /raid/work2/Turk/GZ_Master --min-num-annots 500_DOCTEST


        python -m ibeis.other.ibsfuncs --test-export_testset_for_chuck --db GIR_Tanya --min-num-annots 100

    Example:
        >>> # DISABLE_DOCTEST
        >>> from ibeis.other.ibsfuncs import *  # NOQA
        >>> import ibeis
        >>> # build test data
        >>> #dbdir = ut.get_argval(('--dbdir',), type_=str, default='testdb1')
        >>> min_num_annots = ut.get_argval(('--min-num-annots',), type_=int, default=500)
        >>> #ibs = ibeis.opendb('testdb1')
        >>> #ibs = ibeis.opendb(dbdir='/raid/work2/Turk/PZ_Master')
        >>> ibs = ibeis.opendb()  # dbdir=dbdir)
        >>> #ibs = ibeis.opendb(dbdir='/raid/work2/Turk/GZ_Master')
        >>> print(ibs.get_dbinfo_str())
        >>> #ibs = ibeis.opendb('testdb1')
        >>> # execute function
        >>> result = export_testset_for_chuck(ibs, min_num_annots)
        >>> # verify results
        >>> print(result)

    min_num_annots = 500
    """
    import numpy as np

    min_num_annots_per_name = 3
    max_annot_per_image = 5
    #3

    #min_num_annots_per_name = 1
    #max_annot_per_image = 3000

    nid_list = ibs.get_valid_nids()
    aids_list = ibs.get_name_aids(nid_list)
    nAids_list = list(map(len, aids_list))
    nOther_aids_list = ibs.unflat_map(ibs.get_annot_num_contact_aids,
                                      aids_list)

    invalid_by_num_annots = [
        num < min_num_annots_per_name for num in nAids_list
    ]
    invalid_by_num_others = [
        any([num > max_annot_per_image for num in nums])
        for nums in nOther_aids_list
    ]
    invalid_list = ut.or_lists(invalid_by_num_annots, invalid_by_num_others)

    valid_nids = ut.filterfalse_items(nid_list, invalid_list)

    def get_name_time_variation(ibs, nid_list):
        aids_list = ibs.get_name_aids(nid_list)
        unixtimes_list = ibs.unflat_map(ibs.get_annot_image_unixtimes,
                                        aids_list)
        unixtimes_arrs = list(map(np.array, unixtimes_list))
        fixtimes_list = [arr[arr > 0] for arr in unixtimes_arrs]
        std_list = [
            np.std(arr) if len(arr) > 1 else 0 for arr in fixtimes_list
        ]
        return std_list

    std_list = get_name_time_variation(ibs, valid_nids)
    sorted_nids = ut.sortedby(valid_nids, std_list, reverse=True)

    # Find which names to include
    num_annot_cumsum = np.cumsum(ibs.get_name_num_annotations(sorted_nids))
    pos_list = np.where(num_annot_cumsum >= min_num_annots)[0]
    assert len(pos_list) > 0

    nid_list_chosen = sorted_nids[:pos_list[0] + 1]
    print('using names:')
    print(ibs.get_name_texts(nid_list_chosen))
    aids_list_chosen = ibs.get_name_aids(nid_list_chosen)
    aid_list_chosen = ut.flatten(aids_list_chosen)
    gid_list_chosen = ibs.get_annot_gids(aid_list_chosen)
    #ut.debug_duplicate_items(gid_list_chosen)

    # make sure not too many other annots are along for the ride
    other_aids = ibs.get_annot_contact_aids(aid_list_chosen)
    unexpected_aids = list(
        set(ut.flatten(other_aids)).difference(set(aid_list_chosen)))
    print('got %d unexpected_aids' % (len(unexpected_aids), ))

    from ibeis.dbio import export_subset

    def new_nonconflicting_dbpath(ibs):
        dpath, dbname = split(ibs.get_dbdir())
        base_fmtstr = dbname + '_demo' + str(min_num_annots) + '_export%d'
        new_dbpath = ut.get_nonconflicting_path(base_fmtstr, dpath)
        return new_dbpath

    #ut.embed()

    dbpath = new_nonconflicting_dbpath(ibs)
    ibs_dst = ibeis.opendb(dbdir=dbpath, allow_newdir=True)
    ibs_src = ibs
    gid_list = gid_list_chosen
    export_subset.merge_databases(ibs_src, ibs_dst, gid_list=gid_list)

    DEBUG_NAME = False
    if DEBUG_NAME:
        ibs.get_name_num_annotations(sorted_nids[0:10])
        import plottool as pt
        ibeis.viz.viz_name.show_name(ibs, sorted_nids[0])
        pt.update()
Пример #15
0
 def toggle_samefig(self):
     self.same_fig = not self.same_fig
     if self.mx is not None:
         self.select_ith_match(self.mx)
     pt.update()
Пример #16
0
def param_interaction():
    r"""
    CommandLine:
        python -m vtool.test_constrained_matching --test-param_interaction

    Notes:
        python -m vtool.test_constrained_matching --test-param_interaction
        setparam normalizer_mode=nearby
        setparam normalizer_mode=far
        setparam ratio_thresh=.625
        setparam ratio_thresh=.5

        setparam ratio_thresh2=.625
        normalizer_mode=plus

    Example:
        >>> # DISABLE_DOCTEST
        >>> from vtool.test_constrained_matching import *  # NOQA
        >>> # build test data
        >>> # execute function
        >>> testtup = param_interaction()
        >>> # verify results
        >>> result = str(testtup)
        >>> print(result)
    """
    import plottool as pt
    USE_IBEIS = False and ut.is_developer()
    if USE_IBEIS:
        from ibeis.algo.hots import devcases
        index = 2
        fpath1, fpath2, fpath3 = devcases.get_dev_test_fpaths(index)
        testtup1 = testdata_matcher(fpath1, fpath2)
        testtup2 = testdata_matcher(fpath1, fpath3)
    else:
        testtup1 = testdata_matcher('easy1.png', 'easy2.png')
        testtup2 = testdata_matcher('easy1.png', 'hard3.png')
    testtup_list = [testtup1, testtup2]
    simp_list = [SimpleMatcher(testtup) for testtup in testtup_list]
    varied_dict = dict([
        ('sver_xy_thresh', .1),
        ('ratio_thresh', .625),
        ('search_K', 7),
        ('ratio_thresh2', .625),
        ('sver_xy_thresh2', .01),
        ('normalizer_mode', ['nearby', 'far', 'plus'][1]),
        ('match_xy_thresh', .1),
    ])
    cfgdict_list = ut.all_dict_combinations(varied_dict)
    tried_configs = []

    # DEFINE CUSTOM INTRACTIONS
    custom_actions, valid_vizmodes, viz_index_, offset_fnum_ = make_custom_interactions(
        simp_list)
    # /DEFINE CUSTOM INTRACTIONS

    for cfgdict in ut.InteractiveIter(
            cfgdict_list,
            #default_action='reload',
            custom_actions=custom_actions,
            wraparound=True):
        for simp in simp_list:
            simp.run_matching(cfgdict=cfgdict)
        vizkey = valid_vizmodes[viz_index_[0]].replace('visualize_', '')
        print('vizkey = %r' % (vizkey, ))
        for fnum_, simp in enumerate(simp_list):
            fnum = fnum_ + offset_fnum_[0]
            simp.visualize(vizkey, fnum=fnum)
        tried_configs.append(cfgdict.copy())
        print('Current Config = ')
        print(ut.dict_str(cfgdict))
        pt.present()
        pt.update()
Пример #17
0
def test_mser():
    import cv2
    import vtool as vt
    import plottool as pt
    import numpy as np
    pt.qt4ensure()

    class Keypoints(ut.NiceRepr):
        """
        Convinence class for dealing with keypoints
        """
        def __init__(self, kparr, info=None):
            self.kparr = kparr
            if info is None:
                info = {}
            self.info = info

        def add_info(self, key, val):
            self.info[key] = val

        def __nice__(self):
            return ' ' + str(len(self.kparr))

        @property
        def scale(self):
            return vt.get_scales(self.kparr)

        @property
        def eccentricity(self):
            return vt.get_kpts_eccentricity(self.kparr)

        def compress(self, flags, inplace=False):
            subarr = self.kparr.compress(flags, axis=0)
            info = {
                key: ut.compress(val, flags)
                for key, val in self.info.items()
            }
            return Keypoints(subarr, info)

    img_fpath = ut.grab_test_imgpath(
        ut.get_argval('--fname', default='zebra.png'))
    imgBGR = vt.imread(img_fpath)
    imgGray = cv2.cvtColor(imgBGR, cv2.COLOR_BGR2GRAY)
    # http://docs.opencv.org/master/d3/d28/classcv_1_1MSER.html#gsc.tab=0
    # http://stackoverflow.com/questions/17647500/exact-meaning-of-the-parameters-given-to-initialize-mser-in-opencv-2-4-x
    factory = cv2.MSER_create
    img_area = np.product(np.array(vt.get_size(imgGray)))
    _max_area = (img_area // 10)
    _delta = 8
    _min_diversity = .5

    extractor = factory(_delta=_delta,
                        _max_area=_max_area,
                        _min_diversity=_min_diversity)
    # bboxes are x,y,w,h
    regions, bboxes = extractor.detectRegions(imgGray)
    # ellipse definition from [Fitzgibbon95]
    # http://www.bmva.org/bmvc/1995/bmvc-95-050.pdf p518
    # ell = [c_x, c_y, R_x, R_y, theta]
    # (cx, cy) = conic center
    # Rx and Ry = conic radii
    # theta is the counterclockwise angle
    fitz_ellipses = [cv2.fitEllipse(mser) for mser in regions]

    # http://answers.opencv.org/question/19015/how-to-use-mser-in-python/
    #hulls = [cv2.convexHull(p.reshape(-1, 1, 2)) for p in regions]
    #hull_ells = [cv2.fitEllipse(hull[:, 0]) for hull in hulls]
    invVR_mats = []
    for ell in fitz_ellipses:
        ((cx, cy), (dx, dy), degrees) = ell
        theta = np.radians(degrees)  # opencv lives in radians
        # Convert diameter to radians
        rx = dx / 2
        ry = dy / 2
        S = vt.scale_mat3x3(rx, ry)
        T = vt.translation_mat3x3(cx, cy)
        R = vt.rotation_mat3x3(theta)
        invVR = T.dot(R.dot(S))
        invVR_mats.append(invVR)
    invVR_mats = np.array(invVR_mats)
    #_oris = vt.get_invVR_mats_oris(invVR_mats)
    kpts2_ = vt.flatten_invV_mats_to_kpts(invVR_mats)

    self = Keypoints(kpts2_)
    self.add_info('regions', regions)
    flags = (self.eccentricity < .9)
    #flags = self.scale < np.mean(self.scale)
    #flags = self.scale < np.median(self.scale)
    self = self.compress(flags)
    import plottool as pt
    #pt.interact_keypoints.ishow_keypoints(imgBGR, self.kparr, None, ell_alpha=.4, color='distinct', fnum=2)
    #import plottool as pt
    vis = imgBGR.copy()

    for region in self.info['regions']:
        vis[region.T[1], region.T[0], :] = 0

    #regions, bbox = mser.detectRegions(gray)
    #hulls = [cv2.convexHull(p.reshape(-1, 1, 2)) for p in self.info['regions']]
    #cv2.polylines(vis, hulls, 1, (0, 255, 0))
    #for region in self.info['regions']:
    #    ell = cv2.fitEllipse(region)
    #    cv2.ellipse(vis, ell, (255))
    pt.interact_keypoints.ishow_keypoints(vis,
                                          self.kparr,
                                          None,
                                          ell_alpha=.4,
                                          color='distinct',
                                          fnum=2)
    #pt.imshow(vis, fnum=2)
    pt.update()

    #extractor = extract_factory['DAISY']()

    #desc_type_to_dtype = {
    #    cv2.CV_8U: np.uint8,
    #    cv2.CV_8s: np.uint,
    #}
    #def alloc_desc(extractor):
    #    desc_type = extractor.descriptorType()
    #    desc_size = extractor.descriptorSize()
    #    dtype = desc_type_to_dtype[desc_type]
    #    shape = (len(cv2_kpts), desc_size)
    #    desc = np.empty(shape, dtype=dtype)
    #    return desc

    #ut.search_module(cv2, 'array', recursive=True)
    #ut.search_module(cv2, 'freak', recursive=True)
    #ut.search_module(cv2, 'out', recursive=True)

    #cv2_kpts = cv2_kpts[0:2]

    #for key, factory in just_desc_factory_.items():
    #    extractor = factory()
    #    desc = alloc_desc(extractor)
    #    desc = extractor.compute(imgGray, cv2_kpts)
    #    feats[key] = (desc,)
    #    #extractor.compute(imgGray, cv2_kpts, desc)
    #    pass
    #kpts = np.array(list(map(from_cv2_kpts, cv2_kpts)))

    #orb = cv2.ORB()
    #kp1, des1 = orb.detectAndCompute(imgGray, None)
    #blober = cv2.SimpleBlobDetector_create()
    #haris_kpts = cv2.cornerHarris(imgGray, 2, 3, 0.04)

    #[name for name in dir(cv2) if 'mat' in name.lower()]
    #[name for name in dir(cv2.xfeatures2d) if 'desc' in name.lower()]

    #[name for name in dir(cv2) if 'detect' in name.lower()]
    #[name for name in dir(cv2) if 'extract' in name.lower()]
    #[name for name in dir(cv2) if 'ellip' in name.lower()]

    #sift = cv2.xfeatures2d.SIFT_create()
    #cv2_kpts = sift.detect(imgGray)
    #desc = sift.compute(imgGray, cv2_kpts)[1]

    #freak = cv2.xfeatures2d.FREAK_create()
    #cv2_kpts = freak.detect(imgGray)
    #desc = freak.compute(imgGray, cv2_kpts)[1]
    pass
Пример #18
0
 def visualize_support(normalizer, update=True, fnum=None, pnum=(1, 1, 1)):
     plot_support(normalizer.tn_support, normalizer.tp_support, fnum=fnum, pnum=pnum)
     if update:
         import plottool as pt
         pt.update()
def export_testset_for_chuck(ibs, min_num_annots):
    """
    Exports a set with some number of annotations that has good demo examples.
    multiple annotations per name and large time variation within names.

    Args:
        ibs (IBEISController):  ibeis controller object

    CommandLine:
        python -m ibeis.other.ibsfuncs --test-export_testset_for_chuck --dbdir /raid/work2/Turk/PZ_Master --min-num-annots 100
        python -m ibeis.other.ibsfuncs --test-export_testset_for_chuck --dbdir /raid/work2/Turk/PZ_Master --min-num-annots 500

        python -m ibeis.other.ibsfuncs --test-export_testset_for_chuck --dbdir /raid/work2/Turk/GZ_Master --min-num-annots 100
        python -m ibeis.other.ibsfuncs --test-export_testset_for_chuck --dbdir
        /raid/work2/Turk/GZ_Master --min-num-annots 500_DOCTEST


        python -m ibeis.other.ibsfuncs --test-export_testset_for_chuck --db GIR_Tanya --min-num-annots 100

    Example:
        >>> # DISABLE_DOCTEST
        >>> from ibeis.other.ibsfuncs import *  # NOQA
        >>> import ibeis
        >>> # build test data
        >>> #dbdir = ut.get_argval(('--dbdir',), type_=str, default='testdb1')
        >>> min_num_annots = ut.get_argval(('--min-num-annots',), type_=int, default=500)
        >>> #ibs = ibeis.opendb('testdb1')
        >>> #ibs = ibeis.opendb(dbdir='/raid/work2/Turk/PZ_Master')
        >>> ibs = ibeis.opendb()  # dbdir=dbdir)
        >>> #ibs = ibeis.opendb(dbdir='/raid/work2/Turk/GZ_Master')
        >>> print(ibs.get_dbinfo_str())
        >>> #ibs = ibeis.opendb('testdb1')
        >>> # execute function
        >>> result = export_testset_for_chuck(ibs, min_num_annots)
        >>> # verify results
        >>> print(result)

    min_num_annots = 500
    """
    import numpy as np

    min_num_annots_per_name = 3
    max_annot_per_image = 5
    #3

    #min_num_annots_per_name = 1
    #max_annot_per_image = 3000

    nid_list = ibs.get_valid_nids()
    aids_list = ibs.get_name_aids(nid_list)
    nAids_list = list(map(len, aids_list))
    nOther_aids_list = ibs.unflat_map(ibs.get_annot_num_contact_aids, aids_list)

    invalid_by_num_annots = [num < min_num_annots_per_name for num in nAids_list]
    invalid_by_num_others = [any([num > max_annot_per_image for num in nums])
                             for nums in nOther_aids_list]
    invalid_list = ut.or_lists(invalid_by_num_annots, invalid_by_num_others)

    valid_nids = ut.filterfalse_items(nid_list, invalid_list)

    def get_name_time_variation(ibs, nid_list):
        aids_list      = ibs.get_name_aids(nid_list)
        unixtimes_list = ibs.unflat_map(ibs.get_annot_image_unixtimes, aids_list)
        unixtimes_arrs = list(map(np.array, unixtimes_list))
        fixtimes_list  = [arr[arr > 0] for arr in unixtimes_arrs]
        std_list       = [np.std(arr) if len(arr) > 1 else 0 for arr in fixtimes_list]
        return std_list

    std_list = get_name_time_variation(ibs, valid_nids)
    sorted_nids = ut.sortedby(valid_nids, std_list, reverse=True)

    # Find which names to include
    num_annot_cumsum = np.cumsum(ibs.get_name_num_annotations(sorted_nids))
    pos_list = np.where(num_annot_cumsum >= min_num_annots)[0]
    assert len(pos_list) > 0

    nid_list_chosen = sorted_nids[:pos_list[0] + 1]
    print('using names:')
    print(ibs.get_name_texts(nid_list_chosen))
    aids_list_chosen = ibs.get_name_aids(nid_list_chosen)
    aid_list_chosen = ut.flatten(aids_list_chosen)
    gid_list_chosen = ibs.get_annot_gids(aid_list_chosen)
    #ut.debug_duplicate_items(gid_list_chosen)

    # make sure not too many other annots are along for the ride
    other_aids = ibs.get_annot_contact_aids(aid_list_chosen)
    unexpected_aids = list(set(ut.flatten(other_aids)).difference(set(aid_list_chosen)))
    print('got %d unexpected_aids' % (len(unexpected_aids),))

    from ibeis.dbio import export_subset

    def new_nonconflicting_dbpath(ibs):
        dpath, dbname = split(ibs.get_dbdir())
        base_fmtstr = dbname + '_demo' + str(min_num_annots) + '_export%d'
        new_dbpath = ut.get_nonconflicting_path(base_fmtstr, dpath)
        return new_dbpath

    #ut.embed()

    dbpath = new_nonconflicting_dbpath(ibs)
    ibs_dst = ibeis.opendb(dbdir=dbpath, allow_newdir=True)
    ibs_src = ibs
    gid_list = gid_list_chosen
    export_subset.merge_databases(ibs_src, ibs_dst, gid_list=gid_list)

    DEBUG_NAME = False
    if DEBUG_NAME:
        ibs.get_name_num_annotations(sorted_nids[0:10])
        import plottool as pt
        ibeis.viz.viz_name.show_name(ibs, sorted_nids[0])
        pt.update()
Пример #20
0
def param_interaction():
    r"""
    CommandLine:
        python -m vtool.test_constrained_matching --test-param_interaction

    Notes:
        python -m vtool.test_constrained_matching --test-param_interaction
        setparam normalizer_mode=nearby
        setparam normalizer_mode=far
        setparam ratio_thresh=.625
        setparam ratio_thresh=.5

        setparam ratio_thresh2=.625
        normalizer_mode=plus

    Example:
        >>> # DISABLE_DOCTEST
        >>> from vtool.test_constrained_matching import *  # NOQA
        >>> # build test data
        >>> # execute function
        >>> testtup = param_interaction()
        >>> # verify results
        >>> result = str(testtup)
        >>> print(result)
    """
    import plottool as pt
    USE_IBEIS = False and ut.is_developer()
    if USE_IBEIS:
        from ibeis.algo.hots import devcases
        index = 2
        fpath1, fpath2, fpath3 = devcases.get_dev_test_fpaths(index)
        testtup1 = testdata_matcher(fpath1, fpath2)
        testtup2 = testdata_matcher(fpath1, fpath3)
    else:
        testtup1 = testdata_matcher('easy1.png', 'easy2.png')
        testtup2 = testdata_matcher('easy1.png', 'hard3.png')
    testtup_list = [testtup1, testtup2]
    simp_list = [SimpleMatcher(testtup) for testtup in testtup_list]
    varied_dict = dict([
        ('sver_xy_thresh', .1),
        ('ratio_thresh', .625),
        ('search_K', 7),
        ('ratio_thresh2', .625),
        ('sver_xy_thresh2', .01),
        ('normalizer_mode', ['nearby', 'far', 'plus'][1]),
        ('match_xy_thresh', .1),
    ])
    cfgdict_list = ut.all_dict_combinations(varied_dict)
    tried_configs = []

    # DEFINE CUSTOM INTRACTIONS
    custom_actions, valid_vizmodes, viz_index_, offset_fnum_ = make_custom_interactions(simp_list)
    # /DEFINE CUSTOM INTRACTIONS

    for cfgdict in ut.InteractiveIter(cfgdict_list,
                                      #default_action='reload',
                                      custom_actions=custom_actions,
                                      wraparound=True):
        for simp in simp_list:
            simp.run_matching(cfgdict=cfgdict)
        vizkey = valid_vizmodes[viz_index_[0]].replace('visualize_', '')
        print('vizkey = %r' % (vizkey,))
        for fnum_, simp in enumerate(simp_list):
            fnum = fnum_ + offset_fnum_[0]
            simp.visualize(vizkey, fnum=fnum)
        tried_configs.append(cfgdict.copy())
        print('Current Config = ')
        print(ut.dict_str(cfgdict))
        pt.present()
        pt.update()
Пример #21
0
def test_mser():
    import cv2
    import vtool as vt
    import plottool as pt
    import numpy as np
    pt.qt4ensure()
    class Keypoints(ut.NiceRepr):
        """
        Convinence class for dealing with keypoints
        """
        def __init__(self, kparr, info=None):
            self.kparr = kparr
            if info is None:
                info = {}
            self.info = info

        def add_info(self, key, val):
            self.info[key] = val

        def __nice__(self):
            return ' ' + str(len(self.kparr))

        @property
        def scale(self):
            return vt.get_scales(self.kparr)

        @property
        def eccentricity(self):
            return vt.get_kpts_eccentricity(self.kparr)

        def compress(self, flags, inplace=False):
            subarr = self.kparr.compress(flags, axis=0)
            info = {key: ut.compress(val, flags) for key, val in self.info.items()}
            return Keypoints(subarr, info)

    img_fpath = ut.grab_test_imgpath(ut.get_argval('--fname', default='zebra.png'))
    imgBGR = vt.imread(img_fpath)
    imgGray = cv2.cvtColor(imgBGR, cv2.COLOR_BGR2GRAY)
    # http://docs.opencv.org/master/d3/d28/classcv_1_1MSER.html#gsc.tab=0
    # http://stackoverflow.com/questions/17647500/exact-meaning-of-the-parameters-given-to-initialize-mser-in-opencv-2-4-x
    factory = cv2.MSER_create
    img_area = np.product(np.array(vt.get_size(imgGray)))
    _max_area = (img_area // 10)
    _delta = 8
    _min_diversity = .5

    extractor = factory(_delta=_delta, _max_area=_max_area, _min_diversity=_min_diversity)
    # bboxes are x,y,w,h
    regions, bboxes = extractor.detectRegions(imgGray)
    # ellipse definition from [Fitzgibbon95]
    # http://www.bmva.org/bmvc/1995/bmvc-95-050.pdf p518
    # ell = [c_x, c_y, R_x, R_y, theta]
    # (cx, cy) = conic center
    # Rx and Ry = conic radii
    # theta is the counterclockwise angle
    fitz_ellipses = [cv2.fitEllipse(mser) for mser in regions]

    # http://answers.opencv.org/question/19015/how-to-use-mser-in-python/
    #hulls = [cv2.convexHull(p.reshape(-1, 1, 2)) for p in regions]
    #hull_ells = [cv2.fitEllipse(hull[:, 0]) for hull in hulls]
    invVR_mats = []
    for ell in fitz_ellipses:
        ((cx, cy), (dx, dy), degrees) = ell
        theta = np.radians(degrees)  # opencv lives in radians
        # Convert diameter to radians
        rx = dx / 2
        ry = dy / 2
        S = vt.scale_mat3x3(rx, ry)
        T = vt.translation_mat3x3(cx, cy)
        R = vt.rotation_mat3x3(theta)
        invVR = T.dot(R.dot(S))
        invVR_mats.append(invVR)
    invVR_mats = np.array(invVR_mats)
    #_oris = vt.get_invVR_mats_oris(invVR_mats)
    kpts2_ = vt.flatten_invV_mats_to_kpts(invVR_mats)

    self = Keypoints(kpts2_)
    self.add_info('regions', regions)
    flags = (self.eccentricity < .9)
    #flags = self.scale < np.mean(self.scale)
    #flags = self.scale < np.median(self.scale)
    self = self.compress(flags)
    import plottool as pt
    #pt.interact_keypoints.ishow_keypoints(imgBGR, self.kparr, None, ell_alpha=.4, color='distinct', fnum=2)
    #import plottool as pt
    vis = imgBGR.copy()

    for region in self.info['regions']:
        vis[region.T[1], region.T[0], :] = 0

    #regions, bbox = mser.detectRegions(gray)
    #hulls = [cv2.convexHull(p.reshape(-1, 1, 2)) for p in self.info['regions']]
    #cv2.polylines(vis, hulls, 1, (0, 255, 0))
    #for region in self.info['regions']:
    #    ell = cv2.fitEllipse(region)
    #    cv2.ellipse(vis, ell, (255))
    pt.interact_keypoints.ishow_keypoints(vis, self.kparr, None, ell_alpha=.4, color='distinct', fnum=2)
    #pt.imshow(vis, fnum=2)
    pt.update()

    #extractor = extract_factory['DAISY']()

    #desc_type_to_dtype = {
    #    cv2.CV_8U: np.uint8,
    #    cv2.CV_8s: np.uint,
    #}
    #def alloc_desc(extractor):
    #    desc_type = extractor.descriptorType()
    #    desc_size = extractor.descriptorSize()
    #    dtype = desc_type_to_dtype[desc_type]
    #    shape = (len(cv2_kpts), desc_size)
    #    desc = np.empty(shape, dtype=dtype)
    #    return desc

    #ut.search_module(cv2, 'array', recursive=True)
    #ut.search_module(cv2, 'freak', recursive=True)
    #ut.search_module(cv2, 'out', recursive=True)

    #cv2_kpts = cv2_kpts[0:2]

    #for key, factory in just_desc_factory_.items():
    #    extractor = factory()
    #    desc = alloc_desc(extractor)
    #    desc = extractor.compute(imgGray, cv2_kpts)
    #    feats[key] = (desc,)
    #    #extractor.compute(imgGray, cv2_kpts, desc)
    #    pass
    #kpts = np.array(list(map(from_cv2_kpts, cv2_kpts)))

    #orb = cv2.ORB()
    #kp1, des1 = orb.detectAndCompute(imgGray, None)
    #blober = cv2.SimpleBlobDetector_create()
    #haris_kpts = cv2.cornerHarris(imgGray, 2, 3, 0.04)

    #[name for name in dir(cv2) if 'mat' in name.lower()]
    #[name for name in dir(cv2.xfeatures2d) if 'desc' in name.lower()]

    #[name for name in dir(cv2) if 'detect' in name.lower()]
    #[name for name in dir(cv2) if 'extract' in name.lower()]
    #[name for name in dir(cv2) if 'ellip' in name.lower()]

    #sift = cv2.xfeatures2d.SIFT_create()
    #cv2_kpts = sift.detect(imgGray)
    #desc = sift.compute(imgGray, cv2_kpts)[1]

    #freak = cv2.xfeatures2d.FREAK_create()
    #cv2_kpts = freak.detect(imgGray)
    #desc = freak.compute(imgGray, cv2_kpts)[1]
    pass
Пример #22
0
 def toggle_samefig(self):
     self.same_fig = not self.same_fig
     if self.mx is not None:
         self.select_ith_match(self.mx)
     pt.update()