def show_chipmatch_graph(ibs, cm_list, qreq_, fnum=None, pnum=None, **kwargs):
r"""
CommandLine:
python -m ibeis.viz.viz_graph --test-show_chipmatch_graph:0 --show
python -m ibeis.viz.viz_graph --test-show_chipmatch_graph:1 --show
python -m ibeis.viz.viz_graph --test-show_chipmatch_graph:1 --show --zoom=.15
python -m ibeis.viz.viz_graph --test-show_chipmatch_graph:1 --zoom=.25 --save foo.jpg --diskshow --figsize=12,6 --dpath=. --dpi=280
Example:
>>> # DISABLE_DOCTEST
>>> from ibeis.viz.viz_graph import * # NOQA
>>> from ibeis.algo.hots.chip_match import * # NOQA
>>> ibs, qreq_, cm_list = plh.testdata_post_sver('PZ_MTEST', qaid_list=[1, 2, 3, 4, 5, 6, 7, 18])
>>> [cm.score_nsum(qreq_) for cm in cm_list]
>>> ut.quit_if_noshow()
>>> daid = cm.get_groundtruth_daids()[0]
>>> zoom = ut.get_argval('--zoom', float, .4)
>>> show_chipmatch_graph(ibs, cm_list, qreq_, zoom=zoom)
>>> #cm.show_single_annotmatch(qreq_, daid)
>>> ut.show_if_requested()
Example:
>>> # DISABLE_DOCTEST
>>> from ibeis.viz.viz_graph import * # NOQA
>>> from ibeis.algo.hots.chip_match import * # NOQA
>>> #ibs, qreq_, cm_list = plh.testdata_post_sver('PZ_MTEST', qaid_list='all')
>>> ibs, qreq_, cm_list = plh.testdata_pre_sver('PZ_MTEST', qaid_list='all')
>>> [cm.score_nsum(qreq_) for cm in cm_list]
>>> ut.quit_if_noshow()
>>> daid = cm.get_groundtruth_daids()[0]
>>> zoom = ut.get_argval('--zoom', float, .4)
>>> show_chipmatch_graph(ibs, cm_list, qreq_, zoom=zoom)
>>> #cm.show_single_annotmatch(qreq_, daid)
>>> ut.show_if_requested()
"""
pass
# breaking
num = 3
qaid_list = [cm.qaid for cm in cm_list]
daids_list = [cm.get_top_aids(num).tolist() for cm in cm_list]
scores_list = [cm.get_annot_scores(daids) for cm, daids in zip(cm_list, daids_list)]
#graph = netx.Graph()
#node = graph.add_node(img)
# FDSFDS!!!
netx_graph = make_ibeis_matching_graph(ibs, qaid_list, daids_list, scores_list)
fnum = None
zoom = kwargs.get('zoom', .4)
viz_netx_chipgraph(ibs, netx_graph, fnum=fnum, with_images=True, zoom=zoom)
def plot(self, fnum, pnum):
from ibeis.viz.viz_graph import viz_netx_chipgraph
self.update_netx_graph()
self.pos = viz_netx_chipgraph(self.ibs, self.netx_graph,
fnum=self.fnum, with_images=self.with_images,
zoom=zoom)
self.ax = pt.gca()
for aid in self.selected_aids:
self.highlight_aid(aid)
pass
def get_annotmatch_subgraph(ibs):
r"""
http://bokeh.pydata.org/en/latest/
https://github.com/jsexauer/networkx_viewer
TODO: Need a special visualization
In the web I need:
* graph of annotations matches.
* can move them around.
* edit lines between them.
* http://stackoverflow.com/questions/15373530/web-graph-visualization-tool
This should share functionality with a name view.
Args:
ibs (IBEISController): ibeis controller object
CommandLine:
python -m ibeis.annotmatch_funcs --exec-get_annotmatch_subgraph --show
# Networkx example
python -m ibeis.viz.viz_graph --test-show_chipmatch_graph:0 --show
Ignore:
from ibeis import viz
Example:
>>> # ENABLE_DOCTEST
>>> from ibeis.annotmatch_funcs import * # NOQA
>>> import ibeis
>>> ibs = ibeis.opendb(defaultdb='PZ_MTEST')
>>> result = get_annotmatch_subgraph(ibs)
>>> ut.show_if_requested()
"""
#import ibeis
#ibs = ibeis.opendb(db='PZ_MTEST')
#rowids = ibs._get_all_annotmatch_rowids()
#aids1 = ibs.get_annotmatch_aid1(rowids)
#aids2 = ibs.get_annotmatch_aid2(rowids)
#
#
nids = ibs.get_valid_nids()
nids = nids[0:5]
aids_list = ibs.get_name_aids(nids)
import itertools
unflat_edges = (list(itertools.product(aids, aids)) for aids in aids_list)
aid_pairs = [tup for tup in ut.iflatten(unflat_edges) if tup[0] != tup[1]]
aids1 = ut.get_list_column(aid_pairs, 0)
aids2 = ut.get_list_column(aid_pairs, 1)
# Enumerate annotmatch properties
rng = np.random.RandomState(0)
edge_props = {
'weight': rng.rand(len(aids1)),
'reviewer_confidence': rng.rand(len(aids1)),
'algo_confidence': rng.rand(len(aids1)),
}
# Remove data that does not need to be visualized
# (dont show all the aids if you dont have to)
thresh = .5
flags = edge_props['weight'] > thresh
aids1_ = ut.compress(aids1, flags)
aids2_ = ut.compress(aids2, flags)
chosen_props = ut.dict_subset(edge_props, ['weight'])
edge_props = ut.map_dict_vals(ut.partial(ut.compress, flag_list=flags),
chosen_props)
edge_keys = list(edge_props.keys())
edge_vals = ut.dict_take(edge_props, edge_keys)
edge_attr_list = [dict(zip(edge_keys, vals_)) for vals_ in zip(*edge_vals)]
unique_aids = list(set(aids1_ + aids2_))
# Make a graph between the chips
nodes = unique_aids
edges = list(zip(aids1_, aids2_, edge_attr_list))
import networkx as nx
graph = nx.DiGraph()
graph.add_nodes_from(nodes)
graph.add_edges_from(edges)
from ibeis.viz import viz_graph
fnum = None
#zoom = kwargs.get('zoom', .4)
viz_graph.viz_netx_chipgraph(ibs,
graph,
fnum=fnum,
with_images=True,
augment_graph=False)
def get_annotmatch_subgraph(ibs):
r"""
http://bokeh.pydata.org/en/latest/
https://github.com/jsexauer/networkx_viewer
TODO: Need a special visualization
In the web I need:
* graph of annotations matches.
* can move them around.
* edit lines between them.
* http://stackoverflow.com/questions/15373530/web-graph-visualization-tool
This should share functionality with a name view.
Args:
ibs (IBEISController): ibeis controller object
CommandLine:
python -m ibeis.annotmatch_funcs --exec-get_annotmatch_subgraph --show
# Networkx example
python -m ibeis.viz.viz_graph --test-show_chipmatch_graph:0 --show
Ignore:
from ibeis import viz
Example:
>>> # ENABLE_DOCTEST
>>> from ibeis.annotmatch_funcs import * # NOQA
>>> import ibeis
>>> ibs = ibeis.opendb(defaultdb='PZ_MTEST')
>>> result = get_annotmatch_subgraph(ibs)
>>> ut.show_if_requested()
"""
#import ibeis
#ibs = ibeis.opendb(db='PZ_MTEST')
#rowids = ibs._get_all_annotmatch_rowids()
#aids1 = ibs.get_annotmatch_aid1(rowids)
#aids2 = ibs.get_annotmatch_aid2(rowids)
#
#
nids = ibs.get_valid_nids()
nids = nids[0:5]
aids_list = ibs.get_name_aids(nids)
import itertools
unflat_edges = (list(itertools.product(aids, aids)) for aids in aids_list)
aid_pairs = [tup for tup in ut.iflatten(unflat_edges) if tup[0] != tup[1]]
aids1 = ut.get_list_column(aid_pairs, 0)
aids2 = ut.get_list_column(aid_pairs, 1)
# Enumerate annotmatch properties
rng = np.random.RandomState(0)
edge_props = {
'weight': rng.rand(len(aids1)),
'reviewer_confidence': rng.rand(len(aids1)),
'algo_confidence': rng.rand(len(aids1)),
}
# Remove data that does not need to be visualized
# (dont show all the aids if you dont have to)
thresh = .5
flags = edge_props['weight'] > thresh
aids1 = ut.compress(aids1, flags)
aids2 = ut.compress(aids2, flags)
edge_props = {key: ut.compress(val, flags) for key, val in edge_props.items()}
edge_keys = list(edge_props.keys())
edge_vals = ut.dict_take(edge_props, edge_keys)
unique_aids = list(set(aids1 + aids2))
# Make a graph between the chips
nodes = list(zip(unique_aids))
edges = list(zip(aids1, aids2, *edge_vals))
node_lbls = [('aid', 'int')]
edge_lbls = [('weight', 'float')]
from ibeis.viz import viz_graph
netx_graph = viz_graph.make_netx_graph(nodes, edges, node_lbls, edge_lbls)
fnum = None
#zoom = kwargs.get('zoom', .4)
zoom = .4
viz_graph.viz_netx_chipgraph(ibs, netx_graph, fnum=fnum, with_images=True, zoom=zoom)
def merge_viewpoint_graph():
r"""
CommandLine:
python -m ibeis.scripts.specialdraw merge_viewpoint_graph --show
Example:
>>> # DISABLE_DOCTEST
>>> from ibeis.scripts.specialdraw import * # NOQA
>>> result = merge_viewpoint_graph()
>>> print(result)
>>> ut.quit_if_noshow()
>>> import plottool as pt
>>> ut.show_if_requested()
"""
import plottool as pt
import ibeis
import networkx as nx
defaultdb = 'PZ_Master1'
ibs = ibeis.opendb(defaultdb=defaultdb)
#nids = None
aids = ibs.get_name_aids(4875)
ibs.print_annot_stats(aids)
left_aids = ibs.filter_annots_general(aids, view='left')[0:3]
right_aids = ibs.filter_annots_general(aids, view='right')
right_aids = list(set(right_aids) - {14517})[0:3]
back = ibs.filter_annots_general(aids, view='back')[0:4]
backleft = ibs.filter_annots_general(aids, view='backleft')[0:4]
backright = ibs.filter_annots_general(aids, view='backright')[0:4]
right_graph = nx.DiGraph(ut.upper_diag_self_prodx(right_aids))
left_graph = nx.DiGraph(ut.upper_diag_self_prodx(left_aids))
back_edges = [
tuple([back[0], backright[0]][::1]),
tuple([back[0], backleft[0]][::1]),
]
back_graph = nx.DiGraph(back_edges)
# Let the graph be a bit smaller
right_graph.edge[right_aids[1]][
right_aids[2]]['constraint'] = ut.get_argflag('--constraint')
left_graph.edge[left_aids[1]][left_aids[2]]['constraint'] = ut.get_argflag(
'--constraint')
#right_graph = right_graph.to_undirected().to_directed()
#left_graph = left_graph.to_undirected().to_directed()
nx.set_node_attributes(right_graph, 'groupid', 'right')
nx.set_node_attributes(left_graph, 'groupid', 'left')
#nx.set_node_attributes(right_graph, 'scale', .2)
#nx.set_node_attributes(left_graph, 'scale', .2)
#back_graph.node[back[0]]['scale'] = 2.3
nx.set_node_attributes(back_graph, 'groupid', 'back')
view_graph = nx.compose_all([left_graph, back_graph, right_graph])
view_graph.add_edges_from([
[backright[0], right_aids[0]][::-1],
[backleft[0], left_aids[0]][::-1],
])
pt.ensure_pylab_qt4()
graph = graph = view_graph # NOQA
#graph = graph.to_undirected()
nx.set_edge_attributes(graph, 'color', pt.DARK_ORANGE[0:3])
#nx.set_edge_attributes(graph, 'color', pt.BLACK)
nx.set_edge_attributes(graph, 'color',
{edge: pt.LIGHT_BLUE[0:3]
for edge in back_edges})
#pt.close_all_figures();
from ibeis.viz import viz_graph
layoutkw = {
'nodesep': 1,
}
viz_graph.viz_netx_chipgraph(ibs,
graph,
with_images=1,
prog='dot',
augment_graph=False,
layoutkw=layoutkw)
if False:
"""
#view_graph = left_graph
pt.close_all_figures(); viz_netx_chipgraph(ibs, view_graph, with_images=0, prog='neato')
#viz_netx_chipgraph(ibs, view_graph, layout='pydot', with_images=False)
#back_graph = make_name_graph_interaction(ibs, aids=back, with_all=False)
aids = left_aids + back + backleft + backright + right_aids
for aid, chip in zip(aids, ibs.get_annot_chips(aids)):
fpath = ut.truepath('~/slides/merge/aid_%d.jpg' % (aid,))
vt.imwrite(fpath, vt.resize_to_maxdims(chip, (400, 400)))
ut.copy_files_to(, )
aids = ibs.filterannots_by_tags(ibs.get_valid_aids(),
dict(has_any_annotmatch='splitcase'))
aid1 = ibs.group_annots_by_name_dict(aids)[252]
aid2 = ibs.group_annots_by_name_dict(aids)[6791]
aids1 = ibs.get_annot_groundtruth(aid1)[0][0:4]
aids2 = ibs.get_annot_groundtruth(aid2)[0]
make_name_graph_interaction(ibs, aids=aids1 + aids2, with_all=False)
ut.ensuredir(ut.truthpath('~/slides/split/))
for aid, chip in zip(aids, ibs.get_annot_chips(aids)):
fpath = ut.truepath('~/slides/merge/aidA_%d.jpg' % (aid,))
vt.imwrite(fpath, vt.resize_to_maxdims(chip, (400, 400)))
"""
pass
def merge_viewpoint_graph():
r"""
CommandLine:
python -m ibeis.scripts.specialdraw merge_viewpoint_graph --show
Example:
>>> # DISABLE_DOCTEST
>>> from ibeis.scripts.specialdraw import * # NOQA
>>> result = merge_viewpoint_graph()
>>> print(result)
>>> ut.quit_if_noshow()
>>> import plottool as pt
>>> ut.show_if_requested()
"""
import plottool as pt
import ibeis
import networkx as nx
defaultdb = 'PZ_Master1'
ibs = ibeis.opendb(defaultdb=defaultdb)
#nids = None
aids = ibs.get_name_aids(4875)
ibs.print_annot_stats(aids)
left_aids = ibs.filter_annots_general(aids, view='left')[0:3]
right_aids = ibs.filter_annots_general(aids, view='right')
right_aids = list(set(right_aids) - {14517})[0:3]
back = ibs.filter_annots_general(aids, view='back')[0:4]
backleft = ibs.filter_annots_general(aids, view='backleft')[0:4]
backright = ibs.filter_annots_general(aids, view='backright')[0:4]
right_graph = nx.DiGraph(ut.upper_diag_self_prodx(right_aids))
left_graph = nx.DiGraph(ut.upper_diag_self_prodx(left_aids))
back_edges = [
tuple([back[0], backright[0]][::1]),
tuple([back[0], backleft[0]][::1]),
]
back_graph = nx.DiGraph(back_edges)
# Let the graph be a bit smaller
right_graph.edge[right_aids[1]][right_aids[2]]['constraint'] = ut.get_argflag('--constraint')
left_graph.edge[left_aids[1]][left_aids[2]]['constraint'] = ut.get_argflag('--constraint')
#right_graph = right_graph.to_undirected().to_directed()
#left_graph = left_graph.to_undirected().to_directed()
nx.set_node_attributes(right_graph, 'groupid', 'right')
nx.set_node_attributes(left_graph, 'groupid', 'left')
#nx.set_node_attributes(right_graph, 'scale', .2)
#nx.set_node_attributes(left_graph, 'scale', .2)
#back_graph.node[back[0]]['scale'] = 2.3
nx.set_node_attributes(back_graph, 'groupid', 'back')
view_graph = nx.compose_all([left_graph, back_graph, right_graph])
view_graph.add_edges_from([
[backright[0], right_aids[0]][::-1],
[backleft[0], left_aids[0]][::-1],
])
pt.ensure_pylab_qt4()
graph = graph = view_graph # NOQA
#graph = graph.to_undirected()
nx.set_edge_attributes(graph, 'color', pt.DARK_ORANGE[0:3])
#nx.set_edge_attributes(graph, 'color', pt.BLACK)
nx.set_edge_attributes(graph, 'color', {edge: pt.LIGHT_BLUE[0:3] for edge in back_edges})
#pt.close_all_figures();
from ibeis.viz import viz_graph
layoutkw = {
'nodesep': 1,
}
viz_graph.viz_netx_chipgraph(ibs, graph, with_images=1, prog='dot',
augment_graph=False, layoutkw=layoutkw)
if False:
"""
#view_graph = left_graph
pt.close_all_figures(); viz_netx_chipgraph(ibs, view_graph, with_images=0, prog='neato')
#viz_netx_chipgraph(ibs, view_graph, layout='pydot', with_images=False)
#back_graph = make_name_graph_interaction(ibs, aids=back, with_all=False)
aids = left_aids + back + backleft + backright + right_aids
for aid, chip in zip(aids, ibs.get_annot_chips(aids)):
fpath = ut.truepath('~/slides/merge/aid_%d.jpg' % (aid,))
vt.imwrite(fpath, vt.resize_to_maxdims(chip, (400, 400)))
ut.copy_files_to(, )
aids = ibs.filterannots_by_tags(ibs.get_valid_aids(),
dict(has_any_annotmatch='splitcase'))
aid1 = ibs.group_annots_by_name_dict(aids)[252]
aid2 = ibs.group_annots_by_name_dict(aids)[6791]
aids1 = ibs.get_annot_groundtruth(aid1)[0][0:4]
aids2 = ibs.get_annot_groundtruth(aid2)[0]
make_name_graph_interaction(ibs, aids=aids1 + aids2, with_all=False)
ut.ensuredir(ut.truthpath('~/slides/split/))
for aid, chip in zip(aids, ibs.get_annot_chips(aids)):
fpath = ut.truepath('~/slides/merge/aidA_%d.jpg' % (aid,))
vt.imwrite(fpath, vt.resize_to_maxdims(chip, (400, 400)))
"""
pass
