def plot_gps_html(gps_list):
""" Plots gps coordinates on a map projection
InstallBasemap:
sudo apt-get install libgeos-dev
pip install git+https://github.com/matplotlib/basemap
http://matplotlib.org/basemap/users/examples.html
pip install gmplot
sudo apt-get install netcdf-bin
sudo apt-get install libnetcdf-dev
pip install netCDF4
Ignore:
pip install git+git://github.com/myuser/foo.git@v123
Example:
>>> # DISABLE_DOCTEST
>>> from wbia.algo.preproc.preproc_occurrence import * # NOQA
>>> import wbia
>>> ibs = wbia.opendb(defaultdb='testdb1')
>>> images = ibs.images()
>>> # Setup GPS points to draw
>>> print('Setup GPS points')
>>> gps_list_ = np.array(images.gps2)
>>> unixtime_list_ = np.array(images.unixtime2)
>>> has_gps = np.all(np.logical_not(np.isnan(gps_list_)), axis=1)
>>> has_unixtime = np.logical_not(np.isnan(unixtime_list_))
>>> isvalid = np.logical_and(has_gps, has_unixtime)
>>> gps_list = gps_list_.compress(isvalid, axis=0)
>>> unixtime_list = unixtime_list_.compress(isvalid) # NOQA
>>> plot_image_gps(gps_list)
"""
import wbia.plottool as pt
import gmplot
import matplotlib as mpl
import vtool as vt
pt.qt4ensure()
lat = gps_list.T[0]
lon = gps_list.T[1]
# Get extent of
bbox = vt.bbox_from_verts(gps_list)
centerx, centery = vt.bbox_center(bbox)
gmap = gmplot.GoogleMapPlotter(centerx, centery, 13)
color = mpl.colors.rgb2hex(pt.ORANGE)
gmap.scatter(lat, lon, color=color, size=100, marker=False)
gmap.draw('mymap.html')
ut.startfile('mymap.html')
def makewarp(imgBGR):
# hack a projection matrix using dummy homogrpahy
imgBGRA = cv2.cvtColor(imgBGR, cv2.COLOR_BGR2BGRA)
imgBGRA[:, :, 3] = .87 * 255 # hack alpha
imgBGRA = vt.pad_image(imgBGRA, 2, value=[0, 0, 255, 255])
size = np.array(vt.get_size(imgBGRA))
pts1 = np.array([(0, 0), (0, 1), (1, 1), (1, 0)]) * size
x_adjust = .15
y_adjust = .5
pts2 = np.array([(x_adjust, 0), (0, 1 - y_adjust), (1, 1 - y_adjust), (1 - x_adjust, 0)]) * size
H = cv2.findHomography(pts1, pts2)[0]
dsize = np.array(vt.bbox_from_verts(pts2)[2:4]).astype(np.int)
warpkw = dict(flags=cv2.INTER_LANCZOS4, borderMode=cv2.BORDER_CONSTANT)
imgBGRA_warped = cv2.warpPerspective(imgBGRA, H, tuple(dsize), **warpkw)
return imgBGRA_warped
def makewarp(imgBGR):
# hack a projection matrix using dummy homogrpahy
imgBGRA = cv2.cvtColor(imgBGR, cv2.COLOR_BGR2BGRA)
imgBGRA[:, :, 3] = .87 * 255 # hack alpha
imgBGRA = vt.pad_image(imgBGRA, 2, value=[0, 0, 255, 255])
size = np.array(vt.get_size(imgBGRA))
pts1 = np.array([(0, 0), (0, 1), (1, 1), (1, 0)]) * size
x_adjust = .15
y_adjust = .5
pts2 = np.array([(x_adjust, 0), (0, 1 - y_adjust), (1, 1 - y_adjust),
(1 - x_adjust, 0)]) * size
H = cv2.findHomography(pts1, pts2)[0]
dsize = np.array(vt.bbox_from_verts(pts2)[2:4]).astype(np.int)
warpkw = dict(flags=cv2.INTER_LANCZOS4, borderMode=cv2.BORDER_CONSTANT)
imgBGRA_warped = cv2.warpPerspective(imgBGRA, H, tuple(dsize),
**warpkw)
return imgBGRA_warped
def show_chip(ibs,
aid,
in_image=False,
annote=True,
title_suffix='',
weight_label=None,
weights=None,
config2_=None,
**kwargs):
r"""Driver function to show chips
Args:
ibs (wbia.IBEISController):
aid (int): annotation rowid
in_image (bool): displays annotation with the context of its source image
annote (bool): enables overlay annoations
title_suffix (str):
weight_label (None): (default = None)
weights (None): (default = None)
config2_ (dict): (default = None)
Kwargs:
enable_chip_title_prefix, nokpts, kpts_subset, kpts, text_color,
notitle, draw_lbls, show_aidstr, show_gname, show_name, show_nid,
show_exemplar, show_num_gt, show_quality_text, show_viewcode, fnum,
title, figtitle, pnum, interpolation, cmap, heatmap, data_colorbar,
darken, update, xlabel, redraw_image, ax, alpha, docla, doclf,
projection, pts, ell
color (3/4-tuple, ndarray, or str): colors for keypoints
CommandLine:
python -m wbia.viz.viz_chip show_chip --show --ecc
python -c "import utool as ut; ut.print_auto_docstr('wbia.viz.viz_chip', 'show_chip')"
python -m wbia.viz.viz_chip show_chip --show --db NNP_Master3 --aids 14047 --no-annote
python -m wbia.viz.viz_chip show_chip --show --db NNP_Master3 --aids 14047 --no-annote
python -m wbia.viz.viz_chip show_chip --show --db PZ_MTEST --aid 1 --bgmethod=cnn
python -m wbia.viz.viz_chip show_chip --show --db PZ_MTEST --aid 1 --bgmethod=cnn --scale_max=30
python -m wbia.viz.viz_chip show_chip --show --db PZ_MTEST --aid 1 --ecc --draw_lbls=False --notitle --save=~/slides/lnbnn_query.jpg --dpi=300
Example:
>>> # xdoctest: +REQUIRES(module:wbia_cnn)
>>> # VIZ_TEST
>>> from wbia.viz.viz_chip import * # NOQA
>>> import numpy as np
>>> import vtool as vt
>>> in_image = False
>>> ibs, aid_list, kwargs, config2_ = testdata_showchip()
>>> aid = aid_list[0]
>>> if True:
>>> import matplotlib as mpl
>>> from wbia.scripts.thesis import TMP_RC
>>> mpl.rcParams.update(TMP_RC)
>>> if ut.get_argflag('--ecc'):
>>> kpts = ibs.get_annot_kpts(aid, config2_=config2_)
>>> weights = ibs.get_annot_fgweights([aid], ensure=True, config2_=config2_)[0]
>>> kpts = ut.random_sample(kpts[weights > .9], 200, seed=0)
>>> ecc = vt.get_kpts_eccentricity(kpts)
>>> scale = 1 / vt.get_scales(kpts)
>>> #s = ecc if config2_.affine_invariance else scale
>>> s = scale
>>> colors = pt.scores_to_color(s, cmap_='jet')
>>> kwargs['color'] = colors
>>> kwargs['kpts'] = kpts
>>> kwargs['ell_linewidth'] = 3
>>> kwargs['ell_alpha'] = .7
>>> show_chip(ibs, aid, in_image=in_image, config2_=config2_, **kwargs)
>>> pt.show_if_requested()
"""
if ut.VERBOSE:
logger.info('[viz] show_chip(aid=%r)' % (aid, ))
# ibs.assert_valid_aids((aid,))
# Get chip
# logger.info('in_image = %r' % (in_image,))
chip = vh.get_chips(ibs, aid, in_image=in_image, config2_=config2_)
# Create chip title
chip_text = vh.get_annot_texts(ibs, [aid], **kwargs)[0]
if kwargs.get('enable_chip_title_prefix', True):
chip_title_text = chip_text + title_suffix
else:
chip_title_text = title_suffix
chip_title_text = chip_title_text.strip('\n')
# Draw chip
fig, ax = pt.imshow(chip, **kwargs)
# Populate axis user data
vh.set_ibsdat(ax, 'viztype', 'chip')
vh.set_ibsdat(ax, 'aid', aid)
if annote and not kwargs.get('nokpts', False):
# Get and draw keypoints
if 'color' not in kwargs:
if weight_label == 'fg_weights':
if weights is None and ibs.has_species_detector(
ibs.get_annot_species_texts(aid)):
weight_label = 'fg_weights'
weights = ibs.get_annot_fgweights([aid],
ensure=True,
config2_=config2_)[0]
if weights is not None:
cmap_ = 'hot'
# if weight_label == 'dstncvs':
# cmap_ = 'rainbow'
color = pt.scores_to_color(weights,
cmap_=cmap_,
reverse_cmap=False)
kwargs['color'] = color
kwargs['ell_color'] = color
kwargs['pts_color'] = color
kpts_ = vh.get_kpts(
ibs,
aid,
in_image,
config2_=config2_,
kpts_subset=kwargs.get('kpts_subset', None),
kpts=kwargs.pop('kpts', None),
)
pt.viz_keypoints._annotate_kpts(kpts_, **kwargs)
if kwargs.get('draw_lbls', True):
pt.upperleft_text(chip_text, color=kwargs.get('text_color', None))
use_title = not kwargs.get('notitle', False)
if use_title:
pt.set_title(chip_title_text)
if in_image:
gid = ibs.get_annot_gids(aid)
aid_list = ibs.get_image_aids(gid)
annotekw = viz_image.get_annot_annotations(ibs,
aid_list,
sel_aids=[aid],
draw_lbls=kwargs.get(
'draw_lbls', True))
# Put annotation centers in the axis
ph.set_plotdat(ax, 'annotation_bbox_list', annotekw['bbox_list'])
ph.set_plotdat(ax, 'aid_list', aid_list)
pt.viz_image2.draw_image_overlay(ax, **annotekw)
zoom_ = ut.get_argval('--zoom', type_=float, default=None)
if zoom_ is not None:
import vtool as vt
# Zoom into the chip for some image context
rotated_verts = ibs.get_annot_rotated_verts(aid)
bbox = ibs.get_annot_bboxes(aid)
# logger.info(bbox)
# logger.info(rotated_verts)
rotated_bbox = vt.bbox_from_verts(rotated_verts)
imgw, imgh = ibs.get_image_sizes(gid)
pad_factor = zoom_
pad_length = min(bbox[2], bbox[3]) * pad_factor
minx = max(rotated_bbox[0] - pad_length, 0)
miny = max(rotated_bbox[1] - pad_length, 0)
maxx = min((rotated_bbox[0] + rotated_bbox[2]) + pad_length, imgw)
maxy = min((rotated_bbox[1] + rotated_bbox[3]) + pad_length, imgh)
# maxy = imgh - maxy
# miny = imgh - miny
ax = pt.gca()
ax.set_xlim(minx, maxx)
ax.set_ylim(miny, maxy)
ax.invert_yaxis()
else:
ph.set_plotdat(ax, 'chipshape', chip.shape)
# if 'featweights' in vars() and 'color' in kwargs:
if weights is not None and weight_label is not None:
# # HACK HACK HACK
if len(weights) > 0:
cb = pt.colorbar(weights, kwargs['color'])
cb.set_label(weight_label)
return fig, ax
def fix_annotation_orientation(ibs, min_percentage=0.95):
"""
Fixes the annotations that are outside the bounds of the image due to a
changed image orientation flag in the database
CommandLine:
python -m ibeis.scripts.fix_annotation_orientation_issue fix_annotation_orientation
Example:
>>> # ENABLE_DOCTEST
>>> import ibeis
>>> from ibeis.scripts.fix_annotation_orientation_issue import * # NOQA
>>> ibs = ibeis.opendb()
>>> unfixable_gid_list = fix_annotation_orientation(ibs)
>>> assert len(unfixable_gid_list) == 0
"""
from vtool import exif
def bbox_overlap(bbox1, bbox2):
ax1 = bbox1[0]
ay1 = bbox1[1]
ax2 = bbox1[0] + bbox1[2]
ay2 = bbox1[1] + bbox1[3]
bx1 = bbox2[0]
by1 = bbox2[1]
bx2 = bbox2[0] + bbox2[2]
by2 = bbox2[1] + bbox2[3]
overlap_x = max(0, min(ax2, bx2) - max(ax1, bx1))
overlap_y = max(0, min(ay2, by2) - max(ay1, by1))
return overlap_x * overlap_y
orient_dict = exif.ORIENTATION_DICT_INVERSE
good_orient_list = [
exif.ORIENTATION_UNDEFINED,
exif.ORIENTATION_000,
]
good_orient_key_list = [
orient_dict.get(good_orient) for good_orient in good_orient_list
]
assert None not in good_orient_key_list
gid_list = ibs.get_valid_gids()
orient_list = ibs.get_image_orientation(gid_list)
flag_list = [orient not in good_orient_key_list for orient in orient_list]
# Filter based on based gids
unfixable_gid_list = []
gid_list = ut.filter_items(gid_list, flag_list)
if len(gid_list) > 0:
args = (len(gid_list), )
print('Found %d images with non-standard orientations' % args)
aids_list = ibs.get_image_aids(gid_list,
is_staged=None,
__check_staged__=False)
size_list = ibs.get_image_sizes(gid_list)
invalid_gid_list = []
zipped = zip(gid_list, orient_list, aids_list, size_list)
for gid, orient, aid_list, (w, h) in zipped:
image = ibs.get_images(gid)
h_, w_ = image.shape[:2]
if h != h_ or w != w_:
ibs._set_image_sizes([gid], [w_], [h_])
orient_str = exif.ORIENTATION_DICT[orient]
image_bbox = (0, 0, w, h)
verts_list = ibs.get_annot_rotated_verts(aid_list)
invalid = False
for aid, vert_list in zip(aid_list, verts_list):
annot_bbox = vt.bbox_from_verts(vert_list)
overlap = bbox_overlap(image_bbox, annot_bbox)
area = annot_bbox[2] * annot_bbox[3]
percentage = overlap / area
if percentage < min_percentage:
args = (gid, orient_str, aid, overlap, area, percentage)
print(
'\tInvalid GID %r, Orient %r, AID %r: Overlap %0.2f, Area %0.2f (%0.2f %%)'
% args)
invalid = True
# break
if invalid:
invalid_gid_list.append(gid)
invalid_gid_list = list(set(invalid_gid_list))
if len(invalid_gid_list) > 0:
args = (
len(invalid_gid_list),
len(gid_list),
invalid_gid_list,
)
print('Found %d / %d images with invalid annotations = %r' % args)
orient_list = ibs.get_image_orientation(invalid_gid_list)
aids_list = ibs.get_image_aids(invalid_gid_list,
is_staged=None,
__check_staged__=False)
size_list = ibs.get_image_sizes(invalid_gid_list)
zipped = zip(invalid_gid_list, orient_list, aids_list, size_list)
for invalid_gid, orient, aid_list, (w, h) in zipped:
orient_str = exif.ORIENTATION_DICT[orient]
image_bbox = (0, 0, w, h)
args = (
invalid_gid,
len(aid_list),
)
print('Fixing GID %r with %d annotations' % args)
theta = np.pi / 2.0
tx = 0.0
ty = 0.0
if orient == orient_dict.get(exif.ORIENTATION_090):
theta *= 1.0
tx = w
elif orient == orient_dict.get(exif.ORIENTATION_180):
theta *= 2.0
tx = w
ty = h
elif orient == orient_dict.get(exif.ORIENTATION_270):
theta *= -1.0
ty = h
else:
raise ValueError('Unrecognized invalid orientation')
H = np.array([[np.cos(theta), -np.sin(theta), tx],
[np.sin(theta), np.cos(theta), ty],
[0.0, 0.0, 1.0]])
# print(H)
verts_list = ibs.get_annot_rotated_verts(aid_list)
for aid, vert_list in zip(aid_list, verts_list):
vert_list = np.array(vert_list)
# print(vert_list)
vert_list = vert_list.T
transformed_vert_list = vt.transform_points_with_homography(
H, vert_list)
transformed_vert_list = transformed_vert_list.T
# print(transformed_vert_list)
ibs.set_annot_verts([aid], [transformed_vert_list],
update_visual_uuids=False)
current_theta = ibs.get_annot_thetas(aid)
new_theta = current_theta + theta
ibs.set_annot_thetas(aid,
new_theta,
update_visual_uuids=False)
fixed_vert_list = ibs.get_annot_rotated_verts(aid)
fixed_annot_bbox = vt.bbox_from_verts(fixed_vert_list)
fixed_overlap = bbox_overlap(image_bbox, fixed_annot_bbox)
fixed_area = fixed_annot_bbox[2] * fixed_annot_bbox[3]
fixed_percentage = fixed_overlap / fixed_area
args = (invalid_gid, orient_str, aid, fixed_overlap,
fixed_area, fixed_percentage)
print(
'\tFixing GID %r, Orient %r, AID %r: Overlap %0.2f, Area %0.2f (%0.2f %%)'
% args)
if fixed_percentage < min_percentage:
print('\tWARNING: FIXING DID NOT CORRECT AID %r' %
(aid, ))
unfixable_gid_list.append(gid)
print('Un-fixable gid_list = %r' % (unfixable_gid_list, ))
return unfixable_gid_list
def show_chip(ibs, aid, in_image=False, annote=True, title_suffix='',
weight_label=None, weights=None, config2_=None, **kwargs):
r""" Driver function to show chips
Args:
ibs (ibeis.IBEISController):
aid (int): annotation rowid
in_image (bool): displays annotation with the context of its source image
annote (bool): enables overlay annoations
title_suffix (str):
weight_label (None): (default = None)
weights (None): (default = None)
config2_ (dict): (default = None)
Kwargs:
enable_chip_title_prefix, nokpts, kpts_subset, kpts, text_color,
notitle, draw_lbls, show_aidstr, show_gname, show_name, show_nid,
show_exemplar, show_num_gt, show_quality_text, show_yawtext, fnum,
title, figtitle, pnum, interpolation, cmap, heatmap, data_colorbar,
darken, update, xlabel, redraw_image, ax, alpha, docla, doclf,
projection, use_gridspec, pts, ell
color (3/4-tuple, ndarray, or str): colors for keypoints
CommandLine:
python -m ibeis.viz.viz_chip --test-show_chip --show --ecc
python -c "import utool as ut; ut.print_auto_docstr('ibeis.viz.viz_chip', 'show_chip')"
python -m ibeis.viz.viz_chip --test-show_chip --show --db NNP_Master3 --aids 14047 --no-annote
python -m ibeis.viz.viz_chip --test-show_chip --show --db NNP_Master3 --aids 14047 --no-annote
python -m ibeis.viz.viz_chip --test-show_chip --show --db PZ_MTEST --aid 1 --bgmethod=cnn
python -m ibeis.viz.viz_chip --test-show_chip --show --db PZ_MTEST --aid 1 --bgmethod=cnn --scale_max=30
Example:
>>> # VIZ_TEST
>>> from ibeis.viz.viz_chip import * # NOQA
>>> import numpy as np
>>> import vtool as vt
>>> in_image = False
>>> ibs, aid_list, kwargs, config2_ = testdata_showchip()
>>> aid = aid_list[0]
>>> if ut.get_argflag('--ecc'):
>>> kpts = ibs.get_annot_kpts(aid, config2_=config2_)
>>> weights = ibs.get_annot_fgweights([aid], ensure=True, config2_=config2_)[0]
>>> kpts = ut.random_sample(kpts[weights > .9], 200, seed=0)
>>> ecc = vt.get_kpts_eccentricity(kpts)
>>> scale = 1 / vt.get_scales(kpts)
>>> s = ecc if config2_.affine_invariance else scale
>>> colors = pt.scores_to_color(s, cmap_='jet')
>>> kwargs['color'] = colors
>>> kwargs['kpts'] = kpts
>>> show_chip(ibs, aid, in_image=in_image, config2_=config2_, **kwargs)
>>> pt.show_if_requested()
"""
if ut.VERBOSE:
print('[viz] show_chip(aid=%r)' % (aid,))
#ibs.assert_valid_aids((aid,))
# Get chip
#print('in_image = %r' % (in_image,))
chip = vh.get_chips(ibs, aid, in_image=in_image, config2_=config2_)
# Create chip title
chip_text = vh.get_annot_texts(ibs, [aid], **kwargs)[0]
if kwargs.get('enable_chip_title_prefix', True):
chip_title_text = chip_text + title_suffix
else:
chip_title_text = title_suffix
chip_title_text = chip_title_text.strip('\n')
# Draw chip
fig, ax = pt.imshow(chip, **kwargs)
# Populate axis user data
vh.set_ibsdat(ax, 'viztype', 'chip')
vh.set_ibsdat(ax, 'aid', aid)
if annote and not kwargs.get('nokpts', False):
# Get and draw keypoints
if 'color' not in kwargs:
if weight_label == 'fg_weights':
if weights is None and ibs.has_species_detector(ibs.get_annot_species_texts(aid)):
weight_label = 'fg_weights'
weights = ibs.get_annot_fgweights([aid], ensure=True, config2_=config2_)[0]
if weights is not None:
cmap_ = 'hot'
#if weight_label == 'dstncvs':
# cmap_ = 'rainbow'
color = pt.scores_to_color(weights, cmap_=cmap_, reverse_cmap=False)
kwargs['color'] = color
kwargs['ell_color'] = color
kwargs['pts_color'] = color
kpts_ = vh.get_kpts(ibs, aid, in_image, config2_=config2_,
kpts_subset=kwargs.get('kpts_subset', None),
kpts=kwargs.get('kpts', None))
try:
del kwargs['kpts']
except KeyError:
pass
pt.viz_keypoints._annotate_kpts(kpts_, **kwargs)
if not ut.get_argflag('--noaidlabel'):
pt.upperleft_text(chip_text, color=kwargs.get('text_color', None))
use_title = not kwargs.get('notitle', False)
if use_title:
pt.set_title(chip_title_text)
if in_image:
gid = ibs.get_annot_gids(aid)
aid_list = ibs.get_image_aids(gid)
annotekw = viz_image.get_annot_annotations(
ibs, aid_list, sel_aids=[aid], draw_lbls=kwargs.get('draw_lbls', True))
# Put annotation centers in the axis
ph.set_plotdat(ax, 'annotation_bbox_list', annotekw['bbox_list'])
ph.set_plotdat(ax, 'aid_list', aid_list)
pt.viz_image2.draw_image_overlay(ax, **annotekw)
zoom_ = ut.get_argval('--zoom', type_=float, default=None)
if zoom_ is not None:
import vtool as vt
# Zoom into the chip for some image context
rotated_verts = ibs.get_annot_rotated_verts(aid)
bbox = ibs.get_annot_bboxes(aid)
#print(bbox)
#print(rotated_verts)
rotated_bbox = vt.bbox_from_verts(rotated_verts)
imgw, imgh = ibs.get_image_sizes(gid)
pad_factor = zoom_
pad_length = min(bbox[2], bbox[3]) * pad_factor
minx = max(rotated_bbox[0] - pad_length, 0)
miny = max(rotated_bbox[1] - pad_length, 0)
maxx = min((rotated_bbox[0] + rotated_bbox[2]) + pad_length, imgw)
maxy = min((rotated_bbox[1] + rotated_bbox[3]) + pad_length, imgh)
#maxy = imgh - maxy
#miny = imgh - miny
ax = pt.gca()
ax.set_xlim(minx, maxx)
ax.set_ylim(miny, maxy)
ax.invert_yaxis()
else:
ph.set_plotdat(ax, 'chipshape', chip.shape)
#if 'featweights' in vars() and 'color' in kwargs:
if weights is not None and weight_label is not None:
## HACK HACK HACK
if len(weights) > 0:
cb = pt.colorbar(weights, kwargs['color'])
cb.set_label(weight_label)
return fig, ax
