Esempio n. 1
0
def setup_incremental_test(ibs_gt, clear_names=True, aid_order='shuffle'):
    r"""
    CommandLine:
        python -m ibeis.algo.hots.automated_helpers --test-setup_incremental_test:0

        python dev.py -t custom --cfg codename:vsone_unnorm --db PZ_MTEST --allgt --vf --va
        python dev.py -t custom --cfg codename:vsone_unnorm --db PZ_MTEST --allgt --vf --va --index 0 4 8 --verbose

    Example:
        >>> # DISABLE_DOCTEST
        >>> from ibeis.algo.hots.automated_helpers import *  # NOQA
        >>> import ibeis # NOQA
        >>> ibs_gt = ibeis.opendb('PZ_MTEST')
        >>> ibs2, aid_list1, aid1_to_aid2 = setup_incremental_test(ibs_gt)

    Example:
        >>> # DISABLE_DOCTEST
        >>> from ibeis.algo.hots.automated_helpers import *  # NOQA
        >>> import ibeis  # NOQA
        >>> ibs_gt = ibeis.opendb('GZ_ALL')
        >>> ibs2, aid_list1, aid1_to_aid2 = setup_incremental_test(ibs_gt)
    """
    print('\n\n---- SETUP INCREMENTAL TEST ---\n\n')
    # Take a known dataase
    # Create an empty database to test in

    ONLY_GT = True
    if ONLY_GT:
        # use only annotations that will have matches in test
        aid_list1_ = ibs_gt.get_aids_with_groundtruth()
    else:
        # use every annotation in test
        aid_list1_ = ibs_gt.get_valid_aids()

    if ut.get_argflag('--gzdev'):
        # Use a custom selection of gzall
        from ibeis.algo.hots import devcases
        assert ibs_gt.get_dbname() == 'GZ_ALL', 'not gzall'
        vuuid_list, ignore_vuuids = devcases.get_gzall_small_test()
        # TODO; include all names of these annots too
        aid_list = ibs_gt.get_annot_aids_from_visual_uuid(vuuid_list)
        ignore_aid_list = ibs_gt.get_annot_aids_from_visual_uuid(ignore_vuuids)
        ignore_nid_list = ibs_gt.get_annot_nids(ignore_aid_list)
        ut.assert_all_not_None(aid_list)
        other_aids = ut.flatten(ibs_gt.get_annot_groundtruth(aid_list))
        aid_list.extend(other_aids)
        aid_list = sorted(set(aid_list))
        nid_list = ibs_gt.get_annot_nids(aid_list)
        isinvalid_list = [nid in ignore_nid_list for nid in nid_list]
        print('Filtering %r annots specified to ignore' %
              (sum(isinvalid_list), ))
        aid_list = ut.filterfalse_items(aid_list, isinvalid_list)
        #ut.embed()
        aid_list1_ = aid_list
        #ut.embed()

    # Add aids in a random order
    VALID_ORDERS = ['shuffle', 'stagger', 'same']
    #AID_ORDER = 'shuffle'
    aid_order = ut.get_argval('--aid-order', default=aid_order)
    assert VALID_ORDERS.index(aid_order) > -1

    if aid_order == 'shuffle':
        aid_list1 = ut.deterministic_shuffle(aid_list1_[:])
    elif aid_order == 'stagger':
        from six.moves import zip_longest, filter
        aid_groups, unique_nid_list = ibs_gt.group_annots_by_name(aid_list1_)

        def stagger_group(list_):
            return ut.filter_Nones(ut.iflatten(zip_longest(*list_)))

        aid_multiton_group = list(
            filter(lambda aids: len(aids) > 1, aid_groups))
        aid_list1 = stagger_group(aid_multiton_group)
        pass
    elif aid_order == 'same':
        aid_list1 = aid_list1_

    # If reset is true the test database is started completely from scratch
    reset = ut.get_argflag('--reset')

    aid1_to_aid2 = {}  # annotation mapping

    ibs2 = make_incremental_test_database(ibs_gt, aid_list1, reset)

    # Preadd all annotatinos to the test database
    aids_chunk1 = aid_list1
    aid_list2 = add_annot_chunk(ibs_gt, ibs2, aids_chunk1, aid1_to_aid2)

    #ut.embed()
    # Assert annotation visual uuids are in agreement
    if ut.DEBUG2:
        annot_testdb_consistency_checks(ibs_gt, ibs2, aid_list1, aid_list2)

    # Remove names and exemplar information from test database
    if clear_names:
        ensure_testdb_clean_data(ibs_gt, ibs2, aid_list1, aid_list2)

    # Preprocess features before testing
    ibs2.ensure_annotation_data(aid_list2, featweights=True)

    return ibs2, aid_list1, aid1_to_aid2
Esempio n. 2
0
def setup_incremental_test(ibs_gt, clear_names=True, aid_order='shuffle'):
    r"""
    CommandLine:
        python -m ibeis.algo.hots.automated_helpers --test-setup_incremental_test:0

        python dev.py -t custom --cfg codename:vsone_unnorm --db PZ_MTEST --allgt --vf --va
        python dev.py -t custom --cfg codename:vsone_unnorm --db PZ_MTEST --allgt --vf --va --index 0 4 8 --verbose

    Example:
        >>> # DISABLE_DOCTEST
        >>> from ibeis.algo.hots.automated_helpers import *  # NOQA
        >>> import ibeis # NOQA
        >>> ibs_gt = ibeis.opendb('PZ_MTEST')
        >>> ibs2, aid_list1, aid1_to_aid2 = setup_incremental_test(ibs_gt)

    Example:
        >>> # DISABLE_DOCTEST
        >>> from ibeis.algo.hots.automated_helpers import *  # NOQA
        >>> import ibeis  # NOQA
        >>> ibs_gt = ibeis.opendb('GZ_ALL')
        >>> ibs2, aid_list1, aid1_to_aid2 = setup_incremental_test(ibs_gt)
    """
    print('\n\n---- SETUP INCREMENTAL TEST ---\n\n')
    # Take a known dataase
    # Create an empty database to test in

    ONLY_GT = True
    if ONLY_GT:
        # use only annotations that will have matches in test
        aid_list1_ = ibs_gt.get_aids_with_groundtruth()
    else:
        # use every annotation in test
        aid_list1_ = ibs_gt.get_valid_aids()

    if ut.get_argflag('--gzdev'):
        # Use a custom selection of gzall
        from ibeis.algo.hots import devcases
        assert ibs_gt.get_dbname() == 'GZ_ALL', 'not gzall'
        vuuid_list, ignore_vuuids = devcases.get_gzall_small_test()
        # TODO; include all names of these annots too
        aid_list = ibs_gt.get_annot_aids_from_visual_uuid(vuuid_list)
        ignore_aid_list = ibs_gt.get_annot_aids_from_visual_uuid(ignore_vuuids)
        ignore_nid_list = ibs_gt.get_annot_nids(ignore_aid_list)
        ut.assert_all_not_None(aid_list)
        other_aids = ut.flatten(ibs_gt.get_annot_groundtruth(aid_list))
        aid_list.extend(other_aids)
        aid_list = sorted(set(aid_list))
        nid_list = ibs_gt.get_annot_nids(aid_list)
        isinvalid_list = [nid in ignore_nid_list for nid in nid_list]
        print('Filtering %r annots specified to ignore' % (sum(isinvalid_list),))
        aid_list = ut.filterfalse_items(aid_list, isinvalid_list)
        #ut.embed()
        aid_list1_ = aid_list
        #ut.embed()

    # Add aids in a random order
    VALID_ORDERS = ['shuffle', 'stagger', 'same']
    #AID_ORDER = 'shuffle'
    aid_order = ut.get_argval('--aid-order', default=aid_order)
    assert VALID_ORDERS.index(aid_order) > -1

    if aid_order == 'shuffle':
        aid_list1 = ut.deterministic_shuffle(aid_list1_[:])
    elif aid_order == 'stagger':
        from six.moves import zip_longest, filter
        aid_groups, unique_nid_list = ibs_gt.group_annots_by_name(aid_list1_)
        def stagger_group(list_):
            return ut.filter_Nones(ut.iflatten(zip_longest(*list_)))
        aid_multiton_group = list(filter(lambda aids: len(aids) > 1, aid_groups))
        aid_list1 = stagger_group(aid_multiton_group)
        pass
    elif aid_order == 'same':
        aid_list1 = aid_list1_

    # If reset is true the test database is started completely from scratch
    reset = ut.get_argflag('--reset')

    aid1_to_aid2 = {}  # annotation mapping

    ibs2 = make_incremental_test_database(ibs_gt, aid_list1, reset)

    # Preadd all annotatinos to the test database
    aids_chunk1 = aid_list1
    aid_list2 = add_annot_chunk(ibs_gt, ibs2, aids_chunk1, aid1_to_aid2)

    #ut.embed()
    # Assert annotation visual uuids are in agreement
    if ut.DEBUG2:
        annot_testdb_consistency_checks(ibs_gt, ibs2, aid_list1, aid_list2)

    # Remove names and exemplar information from test database
    if clear_names:
        ensure_testdb_clean_data(ibs_gt, ibs2, aid_list1, aid_list2)

    # Preprocess features before testing
    ibs2.ensure_annotation_data(aid_list2, featweights=True)

    return ibs2, aid_list1, aid1_to_aid2
def augment_nnindexer_experiment():
    """

    References:
        http://answers.opencv.org/question/44592/flann-index-training-fails-with-segfault/

    CommandLine:
        utprof.py -m wbia.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment
        python -m wbia.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment

        python -m wbia.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment --db PZ_MTEST --diskshow --adjust=.1 --save "augment_experiment_{db}.png" --dpath='.' --dpi=180 --figsize=9,6
        python -m wbia.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment --db PZ_Master0 --diskshow --adjust=.1 --save "augment_experiment_{db}.png" --dpath='.' --dpi=180 --figsize=9,6 --nosave-flann --show
        python -m wbia.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment --db PZ_Master0 --diskshow --adjust=.1 --save "augment_experiment_{db}.png" --dpath='.' --dpi=180 --figsize=9,6 --nosave-flann --show


        python -m wbia.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment --db PZ_Master0 --diskshow --adjust=.1 --save "augment_experiment_{db}.png" --dpath='.' --dpi=180 --figsize=9,6 --nosave-flann --no-api-cache --nocache-uuids

        python -m wbia.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment --db PZ_MTEST --show
        python -m wbia.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment --db PZ_Master0 --show

        # RUNS THE SEGFAULTING CASE
        python -m wbia.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment --db PZ_Master0 --show
        # Debug it
        gdb python
        run -m wbia.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment --db PZ_Master0 --show
        gdb python
        run -m wbia.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment --db PZ_Master0 --diskshow --adjust=.1 --save "augment_experiment_{db}.png" --dpath='.' --dpi=180 --figsize=9,6


    Example:
        >>> # DISABLE_DOCTEST
        >>> from wbia.algo.hots._neighbor_experiment import *  # NOQA
        >>> # execute function
        >>> augment_nnindexer_experiment()
        >>> # verify results
        >>> ut.show_if_requested()

    """
    import wbia

    # build test data
    # ibs = wbia.opendb('PZ_MTEST')
    ibs = wbia.opendb(defaultdb='PZ_Master0')
    if ibs.get_dbname() == 'PZ_MTEST':
        initial = 1
        addition_stride = 4
        max_ceiling = 100
    elif ibs.get_dbname() == 'PZ_Master0':
        initial = 128
        # addition_stride = 64
        # addition_stride = 128
        addition_stride = 256
        max_ceiling = 10000
        # max_ceiling = 4000
        # max_ceiling = 2000
        # max_ceiling = 600
    else:
        assert False
    all_daids = ibs.get_valid_aids(species='zebra_plains')
    qreq_ = ibs.new_query_request(all_daids, all_daids)
    max_num = min(max_ceiling, len(all_daids))

    # Clear Caches
    ibs.delete_flann_cachedir()
    neighbor_index_cache.clear_memcache()
    neighbor_index_cache.clear_uuid_cache(qreq_)

    # Setup
    all_randomize_daids_ = ut.deterministic_shuffle(all_daids[:])
    # ensure all features are computed

    nnindexer_list = []
    addition_lbl = 'Addition'
    _addition_iter = list(range(initial + 1, max_num, addition_stride))
    addition_iter = iter(
        ut.ProgressIter(_addition_iter,
                        lbl=addition_lbl,
                        freq=1,
                        autoadjust=False))
    time_list_addition = []
    # time_list_reindex = []
    addition_count_list = []
    tmp_cfgstr_list = []

    # for _ in range(80):
    #    next(addition_iter)
    try:
        memtrack = ut.MemoryTracker(disable=False)
        for count in addition_iter:
            aid_list_ = all_randomize_daids_[0:count]
            # Request an indexer which could be an augmented version of an existing indexer.
            with ut.Timer(verbose=False) as t:
                memtrack.report('BEFORE AUGMENT')
                nnindexer_ = neighbor_index_cache.request_augmented_wbia_nnindexer(
                    qreq_, aid_list_)
                memtrack.report('AFTER AUGMENT')
            nnindexer_list.append(nnindexer_)
            addition_count_list.append(count)
            time_list_addition.append(t.ellapsed)
            tmp_cfgstr_list.append(nnindexer_.cfgstr)
            logger.info('===============\n\n')
        logger.info(ut.repr2(time_list_addition))
        logger.info(ut.repr2(list(map(id, nnindexer_list))))
        logger.info(ut.repr2(tmp_cfgstr_list))
        logger.info(
            ut.repr2(list([nnindxer.cfgstr for nnindxer in nnindexer_list])))

        IS_SMALL = False

        if IS_SMALL:
            nnindexer_list = []
        reindex_label = 'Reindex'
        # go backwards for reindex
        _reindex_iter = list(range(initial + 1, max_num,
                                   addition_stride))[::-1]
        reindex_iter = ut.ProgressIter(_reindex_iter, lbl=reindex_label)
        time_list_reindex = []
        # time_list_reindex = []
        reindex_count_list = []

        for count in reindex_iter:
            logger.info('\n+===PREDONE====================\n')
            # check only a single size for memory leaks
            # count = max_num // 16 + ((x % 6) * 1)
            # x += 1

            aid_list_ = all_randomize_daids_[0:count]
            # Call the same code, but force rebuilds
            memtrack.report('BEFORE REINDEX')
            with ut.Timer(verbose=False) as t:
                nnindexer_ = neighbor_index_cache.request_augmented_wbia_nnindexer(
                    qreq_, aid_list_, force_rebuild=True, memtrack=memtrack)
            memtrack.report('AFTER REINDEX')
            ibs.print_cachestats_str()
            logger.info('[nnindex.MEMCACHE] size(NEIGHBOR_CACHE) = %s' %
                        (ut.get_object_size_str(
                            neighbor_index_cache.NEIGHBOR_CACHE.items()), ))
            logger.info('[nnindex.MEMCACHE] len(NEIGHBOR_CACHE) = %s' %
                        (len(neighbor_index_cache.NEIGHBOR_CACHE.items()), ))
            logger.info('[nnindex.MEMCACHE] size(UUID_MAP_CACHE) = %s' %
                        (ut.get_object_size_str(
                            neighbor_index_cache.UUID_MAP_CACHE), ))
            logger.info('totalsize(nnindexer) = ' +
                        ut.get_object_size_str(nnindexer_))
            memtrack.report_type(neighbor_index_cache.NeighborIndex)
            ut.print_object_size_tree(nnindexer_, lbl='nnindexer_')
            if IS_SMALL:
                nnindexer_list.append(nnindexer_)
            reindex_count_list.append(count)
            time_list_reindex.append(t.ellapsed)
            # import cv2
            # import matplotlib as mpl
            # logger.info(mem_top.mem_top(limit=30, width=120,
            #                      #exclude_refs=[cv2.__dict__, mpl.__dict__]
            #     ))
            logger.info('L___________________\n\n\n')
        logger.info(ut.repr2(time_list_reindex))
        if IS_SMALL:
            logger.info(ut.repr2(list(map(id, nnindexer_list))))
            logger.info(
                ut.repr2(list([nnindxer.cfgstr
                               for nnindxer in nnindexer_list])))
    except KeyboardInterrupt:
        logger.info('\n[train] Caught CRTL+C')
        resolution = ''
        from six.moves import input

        while not (resolution.isdigit()):
            logger.info('\n[train] What do you want to do?')
            logger.info('[train]     0 - Continue')
            logger.info('[train]     1 - Embed')
            logger.info('[train]  ELSE - Stop network training')
            resolution = input('[train] Resolution: ')
        resolution = int(resolution)
        # We have a resolution
        if resolution == 0:
            logger.info('resuming training...')
        elif resolution == 1:
            ut.embed()

    import wbia.plottool as pt

    next_fnum = iter(range(0, 1)).next  # python3 PY3
    pt.figure(fnum=next_fnum())
    if len(addition_count_list) > 0:
        pt.plot2(
            addition_count_list,
            time_list_addition,
            marker='-o',
            equal_aspect=False,
            x_label='num_annotations',
            label=addition_lbl + ' Time',
        )

    if len(reindex_count_list) > 0:
        pt.plot2(
            reindex_count_list,
            time_list_reindex,
            marker='-o',
            equal_aspect=False,
            x_label='num_annotations',
            label=reindex_label + ' Time',
        )

    pt.set_figtitle('Augmented indexer experiment')

    pt.legend()
Esempio n. 4
0
def distinct_colors(N, brightness=.878, randomize=True, hue_range=(0.0, 1.0), cmap_seed=None):
    r"""
    Args:
        N (int):
        brightness (float):

    Returns:
        list: RGB_tuples

    CommandLine:
        python -m plottool.color_funcs --test-distinct_colors --N 2 --show --hue-range=0.05,.95
        python -m plottool.color_funcs --test-distinct_colors --N 3 --show --hue-range=0.05,.95
        python -m plottool.color_funcs --test-distinct_colors --N 4 --show --hue-range=0.05,.95
        python -m plottool.color_funcs --test-distinct_colors --N 3 --show --no-randomize
        python -m plottool.color_funcs --test-distinct_colors --N 4 --show --no-randomize
        python -m plottool.color_funcs --test-distinct_colors --N 20 --show

    References:
        http://blog.jianhuashao.com/2011/09/generate-n-distinct-colors.html

    CommandLine:
        python -m plottool.color_funcs --exec-distinct_colors --show
        python -m plottool.color_funcs --exec-distinct_colors --show --no-randomize --N 50
        python -m plottool.color_funcs --exec-distinct_colors --show --cmap_seed=foobar

    Example:
        >>> # ENABLE_DOCTEST
        >>> from plottool.color_funcs import *  # NOQA
        >>> # build test data
        >>> N = ut.get_argval('--N', int, 2)
        >>> randomize = not ut.get_argflag('--no-randomize')
        >>> brightness = 0.878
        >>> # execute function
        >>> cmap_seed = ut.get_argval('--cmap_seed', str, default=None)
        >>> hue_range = ut.get_argval('--hue-range', list, default=(0.00, 1.0))
        >>> RGB_tuples = distinct_colors(N, brightness, randomize, hue_range, cmap_seed=cmap_seed)
        >>> # verify results
        >>> assert len(RGB_tuples) == N
        >>> result = str(RGB_tuples)
        >>> print(result)
        >>> ut.quit_if_noshow()
        >>> color_list = RGB_tuples
        >>> testshow_colors(color_list)
        >>> ut.show_if_requested()
    """
    # TODO: Add sin wave modulation to the sat and value
    #import plottool as pt
    if True:
        import plottool as pt
        # HACK for white figures
        remove_yellow = not pt.is_default_dark_bg()
        #if not pt.is_default_dark_bg():
        #    brightness = .8

    use_jet = False
    if use_jet:
        import plottool as pt
        cmap = pt.plt.cm.jet
        RGB_tuples = list(map(tuple, cmap(np.linspace(0, 1, N))))
    elif cmap_seed is not None:
        # Randomized map based on a seed
        #cmap_ = 'Set1'
        #cmap_ = 'Dark2'
        choices = [
            #'Set1', 'Dark2',
            'jet',
            #'gist_rainbow',
            #'rainbow',
            #'gnuplot',
            #'Accent'
        ]
        cmap_hack = ut.get_argval('--cmap-hack', type_=str, default=None)
        ncolor_hack = ut.get_argval('--ncolor-hack', type_=int, default=None)
        if cmap_hack is not None:
            choices = [cmap_hack]
        if ncolor_hack is not None:
            N = ncolor_hack
            N_ = N
        seed = sum(list(map(ord, ut.hashstr27(cmap_seed))))
        rng = np.random.RandomState(seed + 48930)
        cmap_str = rng.choice(choices, 1)[0]
        #print('cmap_str = %r' % (cmap_str,))
        cmap = pt.plt.cm.get_cmap(cmap_str)
        #ut.hashstr27(cmap_seed)
        #cmap_seed = 0
        #pass
        jitter = (rng.randn(N) / (rng.randn(100).max() / 2)).clip(-1, 1) * ((1 / (N ** 2)))
        range_ = np.linspace(0, 1, N, endpoint=False)
        #print('range_ = %r' % (range_,))
        range_ = range_ + jitter
        #print('range_ = %r' % (range_,))
        while not (np.all(range_ >= 0) and np.all(range_ <= 1)):
            range_[range_ < 0] = np.abs(range_[range_ < 0] )
            range_[range_ > 1] = 2 - range_[range_ > 1]
        #print('range_ = %r' % (range_,))
        shift = rng.rand()
        range_ = (range_ + shift) % 1
        #print('jitter = %r' % (jitter,))
        #print('shift = %r' % (shift,))
        #print('range_ = %r' % (range_,))
        if ncolor_hack is not None:
            range_ = range_[0:N_]
        RGB_tuples = list(map(tuple, cmap(range_)))
    else:
        sat = brightness
        val = brightness
        hmin, hmax = hue_range
        if remove_yellow:
            hue_skips = [(.13, .24)]
        else:
            hue_skips = []
        hue_skip_ranges = [_[1] - _[0] for _ in hue_skips]
        total_skip = sum(hue_skip_ranges)
        hmax_ = hmax - total_skip
        hue_list = np.linspace(hmin, hmax_, N, endpoint=False, dtype=np.float)
        # Remove colors (like hard to see yellows) in specified ranges
        for skip, range_ in zip(hue_skips, hue_skip_ranges):
            hue_list = [hue if hue <= skip[0] else hue + range_ for hue in hue_list]
        HSV_tuples = [(hue, sat, val) for hue in hue_list]
        RGB_tuples = [colorsys.hsv_to_rgb(*x) for x in HSV_tuples]
    if randomize:
        ut.deterministic_shuffle(RGB_tuples)
    return RGB_tuples
Esempio n. 5
0
def augment_nnindexer_experiment():
    """

    References:
        http://answers.opencv.org/question/44592/flann-index-training-fails-with-segfault/

    CommandLine:
        utprof.py -m ibeis.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment
        python -m ibeis.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment

        python -m ibeis.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment --db PZ_MTEST --diskshow --adjust=.1 --save "augment_experiment_{db}.png" --dpath='.' --dpi=180 --figsize=9,6
        python -m ibeis.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment --db PZ_Master0 --diskshow --adjust=.1 --save "augment_experiment_{db}.png" --dpath='.' --dpi=180 --figsize=9,6 --nosave-flann --show
        python -m ibeis.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment --db PZ_Master0 --diskshow --adjust=.1 --save "augment_experiment_{db}.png" --dpath='.' --dpi=180 --figsize=9,6 --nosave-flann --show


        python -m ibeis.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment --db PZ_Master0 --diskshow --adjust=.1 --save "augment_experiment_{db}.png" --dpath='.' --dpi=180 --figsize=9,6 --nosave-flann --no-api-cache --nocache-uuids

        python -m ibeis.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment --db PZ_MTEST --show
        python -m ibeis.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment --db PZ_Master0 --show

        # RUNS THE SEGFAULTING CASE
        python -m ibeis.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment --db PZ_Master0 --show
        # Debug it
        gdb python
        run -m ibeis.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment --db PZ_Master0 --show
        gdb python
        run -m ibeis.algo.hots._neighbor_experiment --test-augment_nnindexer_experiment --db PZ_Master0 --diskshow --adjust=.1 --save "augment_experiment_{db}.png" --dpath='.' --dpi=180 --figsize=9,6


    Example:
        >>> # DISABLE_DOCTEST
        >>> from ibeis.algo.hots._neighbor_experiment import *  # NOQA
        >>> # execute function
        >>> augment_nnindexer_experiment()
        >>> # verify results
        >>> ut.show_if_requested()

    """
    import ibeis
    # build test data
    #ibs = ibeis.opendb('PZ_MTEST')
    ibs = ibeis.opendb(defaultdb='PZ_Master0')
    if ibs.get_dbname() == 'PZ_MTEST':
        initial = 1
        addition_stride = 4
        max_ceiling = 100
    elif ibs.get_dbname() == 'PZ_Master0':
        initial = 128
        #addition_stride = 64
        #addition_stride = 128
        addition_stride = 256
        max_ceiling = 10000
        #max_ceiling = 4000
        #max_ceiling = 2000
        #max_ceiling = 600
    else:
        assert False
    all_daids = ibs.get_valid_aids(species='zebra_plains')
    qreq_ = ibs.new_query_request(all_daids, all_daids)
    max_num = min(max_ceiling, len(all_daids))

    # Clear Caches
    ibs.delete_flann_cachedir()
    neighbor_index_cache.clear_memcache()
    neighbor_index_cache.clear_uuid_cache(qreq_)

    # Setup
    all_randomize_daids_ = ut.deterministic_shuffle(all_daids[:])
    # ensure all features are computed
    #ibs.get_annot_vecs(all_randomize_daids_, ensure=True)
    #ibs.get_annot_fgweights(all_randomize_daids_, ensure=True)

    nnindexer_list = []
    addition_lbl = 'Addition'
    _addition_iter = list(range(initial + 1, max_num, addition_stride))
    addition_iter = iter(ut.ProgressIter(_addition_iter, lbl=addition_lbl,
                                         freq=1, autoadjust=False))
    time_list_addition = []
    #time_list_reindex = []
    addition_count_list = []
    tmp_cfgstr_list = []

    #for _ in range(80):
    #    next(addition_iter)
    try:
        memtrack = ut.MemoryTracker(disable=False)
        for count in addition_iter:
            aid_list_ = all_randomize_daids_[0:count]
            # Request an indexer which could be an augmented version of an existing indexer.
            with ut.Timer(verbose=False) as t:
                memtrack.report('BEFORE AUGMENT')
                nnindexer_ = neighbor_index_cache.request_augmented_ibeis_nnindexer(qreq_, aid_list_)
                memtrack.report('AFTER AUGMENT')
            nnindexer_list.append(nnindexer_)
            addition_count_list.append(count)
            time_list_addition.append(t.ellapsed)
            tmp_cfgstr_list.append(nnindexer_.cfgstr)
            print('===============\n\n')
        print(ut.list_str(time_list_addition))
        print(ut.list_str(list(map(id, nnindexer_list))))
        print(ut.list_str(tmp_cfgstr_list))
        print(ut.list_str(list([nnindxer.cfgstr for nnindxer in nnindexer_list])))

        IS_SMALL = False

        if IS_SMALL:
            nnindexer_list = []
        reindex_label = 'Reindex'
        # go backwards for reindex
        _reindex_iter = list(range(initial + 1, max_num, addition_stride))[::-1]
        reindex_iter = ut.ProgressIter(_reindex_iter, lbl=reindex_label)
        time_list_reindex = []
        #time_list_reindex = []
        reindex_count_list = []

        for count in reindex_iter:
            print('\n+===PREDONE====================\n')
            # check only a single size for memory leaks
            #count = max_num // 16 + ((x % 6) * 1)
            #x += 1

            aid_list_ = all_randomize_daids_[0:count]
            # Call the same code, but force rebuilds
            memtrack.report('BEFORE REINDEX')
            with ut.Timer(verbose=False) as t:
                nnindexer_ = neighbor_index_cache.request_augmented_ibeis_nnindexer(
                    qreq_, aid_list_, force_rebuild=True, memtrack=memtrack)
            memtrack.report('AFTER REINDEX')
            ibs.print_cachestats_str()
            print('[nnindex.MEMCACHE] size(NEIGHBOR_CACHE) = %s' % (
                ut.get_object_size_str(neighbor_index_cache.NEIGHBOR_CACHE.items()),))
            print('[nnindex.MEMCACHE] len(NEIGHBOR_CACHE) = %s' % (
                len(neighbor_index_cache.NEIGHBOR_CACHE.items()),))
            print('[nnindex.MEMCACHE] size(UUID_MAP_CACHE) = %s' % (
                ut.get_object_size_str(neighbor_index_cache.UUID_MAP_CACHE),))
            print('totalsize(nnindexer) = ' + ut.get_object_size_str(nnindexer_))
            memtrack.report_type(neighbor_index_cache.NeighborIndex)
            ut.print_object_size_tree(nnindexer_, lbl='nnindexer_')
            if IS_SMALL:
                nnindexer_list.append(nnindexer_)
            reindex_count_list.append(count)
            time_list_reindex.append(t.ellapsed)
            #import cv2
            #import matplotlib as mpl
            #print(mem_top.mem_top(limit=30, width=120,
            #                      #exclude_refs=[cv2.__dict__, mpl.__dict__]
            #     ))
            print('L___________________\n\n\n')
        print(ut.list_str(time_list_reindex))
        if IS_SMALL:
            print(ut.list_str(list(map(id, nnindexer_list))))
            print(ut.list_str(list([nnindxer.cfgstr for nnindxer in nnindexer_list])))
    except KeyboardInterrupt:
            print('\n[train] Caught CRTL+C')
            resolution = ''
            from six.moves import input
            while not (resolution.isdigit()):
                print('\n[train] What do you want to do?')
                print('[train]     0 - Continue')
                print('[train]     1 - Embed')
                print('[train]  ELSE - Stop network training')
                resolution = input('[train] Resolution: ')
            resolution = int(resolution)
            # We have a resolution
            if resolution == 0:
                print('resuming training...')
            elif resolution == 1:
                ut.embed()

    import plottool as pt

    next_fnum = iter(range(0, 1)).next  # python3 PY3
    pt.figure(fnum=next_fnum())
    if len(addition_count_list) > 0:
        pt.plot2(addition_count_list, time_list_addition, marker='-o', equal_aspect=False,
                 x_label='num_annotations', label=addition_lbl + ' Time')

    if len(reindex_count_list) > 0:
        pt.plot2(reindex_count_list, time_list_reindex, marker='-o', equal_aspect=False,
                 x_label='num_annotations', label=reindex_label + ' Time')

    pt.set_figtitle('Augmented indexer experiment')

    pt.legend()
Esempio n. 6
0
def distinct_colors(N,
                    brightness=0.878,
                    randomize=True,
                    hue_range=(0.0, 1.0),
                    cmap_seed=None):
    r"""
    Args:
        N (int):
        brightness (float):

    Returns:
        list: RGB_tuples

    CommandLine:
        python -m wbia.plottool.color_funcs --test-distinct_colors --N 2 --show --hue-range=0.05,.95
        python -m wbia.plottool.color_funcs --test-distinct_colors --N 3 --show --hue-range=0.05,.95
        python -m wbia.plottool.color_funcs --test-distinct_colors --N 4 --show --hue-range=0.05,.95
        python -m wbia.plottool.color_funcs --test-distinct_colors --N 3 --show --no-randomize
        python -m wbia.plottool.color_funcs --test-distinct_colors --N 4 --show --no-randomize
        python -m wbia.plottool.color_funcs --test-distinct_colors --N 6 --show --no-randomize
        python -m wbia.plottool.color_funcs --test-distinct_colors --N 20 --show

    References:
        http://blog.jianhuashao.com/2011/09/generate-n-distinct-colors.html

    CommandLine:
        python -m wbia.plottool.color_funcs --exec-distinct_colors --show
        python -m wbia.plottool.color_funcs --exec-distinct_colors --show --no-randomize --N 50
        python -m wbia.plottool.color_funcs --exec-distinct_colors --show --cmap_seed=foobar

    Example:
        >>> # ENABLE_DOCTEST
        >>> from wbia.plottool.color_funcs import *  # NOQA
        >>> # build test data
        >>> N = ut.get_argval('--N', int, 2)
        >>> randomize = not ut.get_argflag('--no-randomize')
        >>> brightness = 0.878
        >>> # execute function
        >>> cmap_seed = ut.get_argval('--cmap_seed', str, default=None)
        >>> hue_range = ut.get_argval('--hue-range', list, default=(0.00, 1.0))
        >>> RGB_tuples = distinct_colors(N, brightness, randomize, hue_range, cmap_seed=cmap_seed)
        >>> # verify results
        >>> assert len(RGB_tuples) == N
        >>> result = str(RGB_tuples)
        >>> print(result)
        >>> ut.quit_if_noshow()
        >>> color_list = RGB_tuples
        >>> testshow_colors(color_list)
        >>> import wbia.plottool as pt
        >>> pt.show_if_requested()
    """
    # TODO: Add sin wave modulation to the sat and value
    # import wbia.plottool as pt
    if True:
        import wbia.plottool as pt

        # HACK for white figures
        remove_yellow = not pt.is_default_dark_bg()
        # if not pt.is_default_dark_bg():
        #    brightness = .8

    use_jet = False
    if use_jet:
        import wbia.plottool as pt

        cmap = pt.plt.cm.jet
        RGB_tuples = list(map(tuple, cmap(np.linspace(0, 1, N))))
    elif cmap_seed is not None:
        # Randomized map based on a seed
        # cmap_ = 'Set1'
        # cmap_ = 'Dark2'
        choices = [
            # 'Set1', 'Dark2',
            'jet',
            # 'gist_rainbow',
            # 'rainbow',
            # 'gnuplot',
            # 'Accent'
        ]
        cmap_hack = ut.get_argval('--cmap-hack', type_=str, default=None)
        ncolor_hack = ut.get_argval('--ncolor-hack', type_=int, default=None)
        if cmap_hack is not None:
            choices = [cmap_hack]
        if ncolor_hack is not None:
            N = ncolor_hack
            N_ = N
        seed = sum(list(map(ord, ut.hashstr27(cmap_seed))))
        rng = np.random.RandomState(seed + 48930)
        cmap_str = rng.choice(choices, 1)[0]
        # print('cmap_str = %r' % (cmap_str,))
        cmap = pt.plt.cm.get_cmap(cmap_str)
        # ut.hashstr27(cmap_seed)
        # cmap_seed = 0
        # pass
        jitter = (rng.randn(N) /
                  (rng.randn(100).max() / 2)).clip(-1, 1) * ((1 / (N**2)))
        range_ = np.linspace(0, 1, N, endpoint=False)
        # print('range_ = %r' % (range_,))
        range_ = range_ + jitter
        # print('range_ = %r' % (range_,))
        while not (np.all(range_ >= 0) and np.all(range_ <= 1)):
            range_[range_ < 0] = np.abs(range_[range_ < 0])
            range_[range_ > 1] = 2 - range_[range_ > 1]
        # print('range_ = %r' % (range_,))
        shift = rng.rand()
        range_ = (range_ + shift) % 1
        # print('jitter = %r' % (jitter,))
        # print('shift = %r' % (shift,))
        # print('range_ = %r' % (range_,))
        if ncolor_hack is not None:
            range_ = range_[0:N_]
        RGB_tuples = list(map(tuple, cmap(range_)))
    else:
        sat = brightness
        val = brightness
        hmin, hmax = hue_range
        if remove_yellow:
            hue_skips = [(0.13, 0.24)]
        else:
            hue_skips = []
        hue_skip_ranges = [_[1] - _[0] for _ in hue_skips]
        total_skip = sum(hue_skip_ranges)
        hmax_ = hmax - total_skip
        hue_list = np.linspace(hmin, hmax_, N, endpoint=False, dtype=np.float)
        # Remove colors (like hard to see yellows) in specified ranges
        for skip, range_ in zip(hue_skips, hue_skip_ranges):
            hue_list = [
                hue if hue <= skip[0] else hue + range_ for hue in hue_list
            ]
        HSV_tuples = [(hue, sat, val) for hue in hue_list]
        RGB_tuples = [colorsys.hsv_to_rgb(*x) for x in HSV_tuples]
    if randomize:
        ut.deterministic_shuffle(RGB_tuples)
    return RGB_tuples