def show_low_support_classes(dset):
"""
dset = merged
coarse = merged
"""
# aid = list(dset.anns.values())[0]['id']
# dset.show_annotation(aid)
dset._remove_keypoint_annotations()
gids = sorted([gid for gid, aids in dset.gid_to_aids.items() if aids])
catfreq = dset.category_annotation_frequency()
inspect_cids = []
for name, freq in catfreq.items():
if freq > 0 and freq < 50:
cid = dset.name_to_cat[name]['id']
inspect_cids.append(cid)
inspect_gids = list(
set(ub.flatten(ub.take(dset.cid_to_gids, inspect_cids))))
# inspect_gids = [gid for gid in inspect_gids if 'habcam' not in dset.imgs[gid]['file_name']]
import utool as ut
if ut.inIPython():
import IPython
IPython.get_ipython().magic('pylab qt5 --no-import-all')
print('inspect_gids = {!r}'.format(inspect_gids))
from matplotlib import pyplot as plt
for gid in ut.InteractiveIter(inspect_gids):
img = dset.imgs[gid]
print('img = {}'.format(ub.repr2(img)))
aids = dset.gid_to_aids[gid]
primary_aid = None
anns = list(ub.take(dset.anns, aids))
for ann in anns:
ann = ann.copy()
ann['category'] = dset.cats[ann['category_id']]['name']
print('ann = {}'.format(ub.repr2(ann)))
if primary_aid is None:
if ann['category_id'] in inspect_cids:
primary_aid = ann['id']
try:
fig = plt.figure(1)
fig.clf()
dset.show_annotation(primary_aid, gid=gid)
fig.canvas.draw()
except Exception:
print('cannot draw')
def qtensure():
import wbia.guitool as gt
if ut.inIPython():
import IPython
ipython = IPython.get_ipython()
if ipython is None:
# we must have exited ipython at some point
return
if gt.__PYQT__.GUITOOL_PYQT_VERSION == 5:
"""
sudo apt-get install python3-pyqt5.qtsvg
"""
# import os
# os.environ['QT_API'] = 'pyqt5'
# import matplotlib
# matplotlib.use('Qt5Agg')
# IPython.get_ipython().magic('matplotlib qt5')
# IPython.get_ipython().magic('pylab qt4')
ipython.magic('pylab qt5 --no-import-all')
else:
# IPython.get_ipython().magic('pylab qt4')
ipython.magic('pylab qt4 --no-import-all')
#!/usr/bin/env python2.7
# TODO: ADD COPYRIGHT TAG
from __future__ import absolute_import, division, print_function
import utool
import ibeis
import multiprocessing
from ibeis.model.detect import randomforest
# IBEIS
print, print_, printDBG, rrr, profile = utool.inject(__name__, '[TEST_DETECT]')
SPECIAL = utool.get_flag('--special') or utool.inIPython()
def TEST_DETECT(ibs):
# Create a HotSpotter API (hs) and GUI backend (back)
print('get_valid_ANNOTATIONS')
gid_list = ibs.get_valid_gids()[0:1]
if SPECIAL:
gid_list = utool.safe_slice(ibs.get_valid_gids(), 3)
#gid_list.extend(ibs.add_images([utool.unixpath('~/Dropbox/Chuck/detect_testimg/testgrevy.jpg')]))
species = 'zebra_grevys'
detectkw = {
'quick': True,
'save_detection_images': SPECIAL,
'save_scales': SPECIAL,
}
detect_gen = randomforest.generate_detections(ibs, gid_list, species, **detectkw)
gid_list2 = []
bbox_list2 = []
for gid, bboxes, confidences, img_conf in detect_gen:
for bbox in bboxes:
def iupdate():
if VERBOSE:
print('[pt] iupdate')
if ut.inIPython():
update()
def ensure_pylab_qt4():
if ut.inIPython():
import IPython
IPython.get_ipython().magic('pylab qt4')
def show_keypoint_annots():
merged = read_fine_merged()
def images_with_keypoints():
keypoint_gids = set()
for aid, ann in merged.anns.items():
if ann['roi_shape'] == 'keypoints':
keypoint_gids.add(ann['image_id'])
relevant = ub.dict_subset(merged.gid_to_aids, keypoint_gids)
relevant = {
gid:
[a for a in aids if merged.anns[a]['roi_shape'] == 'keypoints']
for gid, aids in relevant.items()
}
gid_list = ub.argsort(ub.map_vals(len, relevant))[::-1]
return gid_list
def sort_gids_by_nannots(gids):
return ub.argsort(
ub.map_vals(len,
ub.dict_subset(merged.gid_to_aids, gids,
default=[])))[::-1]
def images_with_keypoints_and_boxes():
keypoint_gids = set()
for aid, ann in merged.anns.items():
if ann['roi_shape'] == 'keypoints':
keypoint_gids.add(ann['image_id'])
gid_list = []
for gid in keypoint_gids:
aids = merged.gid_to_aids[gid]
types = set()
for ann in ub.take(merged.anns, aids):
types.add(ann['roi_shape'])
if len(types) > 1:
gid_list.append(gid)
gid_list = sort_gids_by_nannots(gid_list)
return gid_list
def image_from_each_dataset():
groups = ub.ddict(list)
for gid, img in merged.imgs.items():
groups[os.path.dirname(img['file_name'])].append(gid)
gid_groups = []
for gids in groups.values():
gids = sort_gids_by_nannots(gids)
gid_groups.append(gids)
# round robin sample
datas = [gid for x in zip(*gid_groups) for gid in x]
return datas
# gid_list = images_with_keypoints()
gid_list = images_with_keypoints_and_boxes()
gid_list = image_from_each_dataset()
# gid = gid_list[2]
# import matplotlib.pyplot as plt
# plt.gcf().clf()
# merged.show_annotation(gid=gid)
import utool as ut
if ut.inIPython():
import IPython
IPython.get_ipython().magic('pylab qt5 --no-import-all')
from matplotlib import pyplot as plt
for gid in ut.InteractiveIter(gid_list):
try:
fig = plt.figure(1)
fig.clf()
merged.show_annotation(gid=gid)
name = os.path.basename(
os.path.dirname(merged.imgs[gid]['file_name']))
ax = plt.gca()
plt.gca().set_title(name)
ax.set_xticks([])
ax.set_yticks([])
plt.gca().grid('off')
fig.canvas.draw()
except Exception:
print('cannot draw')
def parse_args():
ds_default = None
arch_default = 'siaml2_128'
weights_tag_default = None
# Test values
if False:
ds_default = 'liberty'
weights_tag_default = 'current'
assert ut.inIPython()
# Parse commandline args
ds_tag = ut.get_argval(('--dataset', '--ds'), type_=str,
default=ds_default)
datatype = ut.get_argval(('--datatype', '--dt'), type_=str,
default='siam-patch')
arch_tag = ut.get_argval(('--arch', '-a'), default=arch_default)
weights_tag = ut.get_argval(('--weights', '+w'), type_=str,
default=weights_tag_default)
# Incorporate new config stuff?
#NEW = False
#if NEW:
# default_dstag_cfg = {
# 'ds': 'PZ_MTEST',
# 'mode': 'patches',
# 'arch': arch_default
# }
# named_defaults_dict = {
# '': default_dstag_cfg
# }
# ut.parse_argv_cfg('dstag', named_defaults_dict=named_defaults_dict)
hyperparams = ut.argparse_dict(
{
#'batch_size': 128,
'batch_size': 256,
#'learning_rate': .0005,
'learning_rate': .1,
'momentum': .9,
#'weight_decay': 0.0005,
'weight_decay': 0.0001,
},
alias_dict={
'weight_decay': ['decay'],
'learning_rate': ['learn_rate'],
}
)
requests = ut.argparse_dict(
{
'train': False,
'test': False,
'testall': False,
'publish': False,
'ensuredata': False,
}
)
requests['test'] = requests['test'] or requests['testall']
# breakup weights tag into extern_ds and checkpoint
if weights_tag is not None and ':' in weights_tag:
extern_ds_tag, checkpoint_tag = weights_tag.split(':')
else:
extern_ds_tag = None
checkpoint_tag = weights_tag
# resolve aliases
ds_tag = DS_TAG_ALIAS2.get(ds_tag, ds_tag)
extern_ds_tag = DS_TAG_ALIAS2.get(extern_ds_tag, extern_ds_tag)
checkpoint_tag = CHECKPOINT_TAG_ALIAS.get(checkpoint_tag, checkpoint_tag)
tags = {
'ds_tag': ds_tag,
'extern_ds_tag': extern_ds_tag,
'checkpoint_tag': checkpoint_tag,
'arch_tag': arch_tag,
'datatype': datatype,
}
ut.colorprint('[netrun] * ds_tag=%r' % (ds_tag,), 'lightgray')
ut.colorprint('[netrun] * arch_tag=%r' % (arch_tag,), 'lightgray')
ut.colorprint('[netrun] * extern_ds_tag=%r' % (extern_ds_tag,), 'lightgray')
ut.colorprint('[netrun] * checkpoint_tag=%r' % (checkpoint_tag,), 'lightgray')
return requests, hyperparams, tags
def iupdate():
if VERBOSE:
print('[pt] iupdate')
if ut.inIPython():
update()
def ensure_pylab_qt4():
if ut.inIPython():
import IPython
IPython.get_ipython().magic('pylab qt4')
