def filterObjectsInsideCertainObjects(c, args):
c.execute('SELECT imagefile FROM images')
for imagefile, in progressbar(c.fetchall()):
# Shadow objects.
c.execute(
'SELECT * FROM objects WHERE imagefile=? AND (%s)' %
args.where_shadowing_objects, (imagefile, ))
shadow_object_entries = c.fetchall()
logging.info('Found %d shadowing objects.', len(shadow_object_entries))
# Populate polygons of the shadow objects.
shadow_object_polygons = []
for shadow_object_entry in shadow_object_entries:
shadow_objectid = backendDb.objectField(shadow_object_entry,
'objectid')
c.execute('SELECT y,x FROM polygons WHERE objectid=?',
(shadow_objectid, ))
shadow_polygon = c.fetchall()
shadow_object_polygons.append(shadow_polygon)
shadow_object_ids_set = set([
backendDb.objectField(entry, 'objectid')
for entry in shadow_object_entries
])
# Get all the objects that can be considered.
c.execute(
'SELECT * FROM objects WHERE imagefile=? AND (%s)' %
args.where_objects, (imagefile, ))
object_entries = c.fetchall()
logging.info('Total %d objects satisfying the condition.',
len(object_entries))
for object_entry in object_entries:
objectid = backendDb.objectField(object_entry, 'objectid')
if objectid in shadow_object_ids_set:
logging.debug('Object %d is in the shadow set', objectid)
continue
c.execute('SELECT AVG(y),AVG(x) FROM polygons WHERE objectid=?',
(objectid, ))
center_yx = c.fetchone()
# If polygon does not exist, use bbox.
if center_yx[0] is None:
roi = utilBoxes.bbox2roi(
backendDb.objectField(object_entry, 'bbox'))
center_yx = (roi[0] + roi[2]) / 2, (roi[1] + roi[3]) / 2
logging.debug('center_yx: %s', str(center_yx))
for shadow_object_entry, shadow_polygon in zip(
shadow_object_entries, shadow_object_polygons):
# Get the shadow roi, or polygon if it exists.
shadow_objectid = backendDb.objectField(
object_entry, 'objectid')
# Check that the center is within the shadow polygon or bbox.
if len(shadow_polygon) > 0:
is_inside = cv2.pointPolygonTest(np.array(shadow_polygon),
center_yx, False) >= 0
else:
shadow_roi = utilBoxes.bbox2roi(
backendDb.objectField(shadow_object_entry, 'bbox'))
is_inside = (center_yx[0] > shadow_roi[0]
and center_yx[0] < shadow_roi[2]
and center_yx[1] > shadow_roi[1]
and center_yx[1] < shadow_roi[3])
if is_inside:
backendDb.deleteObject(c, objectid)
# We do not need to check other shadow_object_entries.
continue
def test_negativeDims(self):
with self.assertRaises(ValueError):
utilBoxes.bbox2roi([1, 2, 3, -1])
def test_normal(self):
self.assertEqual(utilBoxes.bbox2roi([1, 2, 3, 4]), [2, 1, 6, 4])
self.assertEqual(utilBoxes.bbox2roi((1, 2, 3, 4)), [2, 1, 6, 4])
def test_notNumbers(self):
with self.assertRaises(TypeError):
utilBoxes.bbox2roi(['a', 'b', 'c', 'd'])
def test_moreThanFourNumbers(self):
with self.assertRaises(ValueError):
utilBoxes.bbox2roi([42, 42, 42, 42, 42])
def test_notSequence(self):
with self.assertRaises(TypeError):
utilBoxes.bbox2roi(42)
def test_zeroDims(self):
self.assertEqual(utilBoxes.bbox2roi([1, 2, 0, 0]), [2, 1, 2, 1])
def importBdd(c, args):
if args.with_display:
imreader = backendMedia.MediaReader(args.rootdir)
image_paths = sorted(glob(op.join(args.images_dir, '*.jpg')))
logging.info('Found %d JPG images in %s' %
(len(image_paths), args.images_dir))
if args.detection_json:
if not op.exists(args.detection_json):
raise FileNotFoundError('Annotation file not found at "%s".' %
args.detection_json)
logging.info(
'Loading the json with annotations. This may take a few seconds.')
with open(args.detection_json) as f:
detections = json.load(f)
# Dict with image name as the key.
detections = {d['name']: d for d in detections}
for image_path in progressbar(image_paths):
filename = op.splitext(op.basename(image_path))[0]
logging.debug('Processing image: "%s"' % filename)
# Add image to the database.
imheight, imwidth = backendMedia.getPictureSize(image_path)
imagefile = op.relpath(image_path, args.rootdir)
c.execute('INSERT INTO images(imagefile,width,height) VALUES (?,?,?)',
(imagefile, imwidth, imheight))
if args.with_display:
img = imreader.imread(imagefile)
# Detection annotations.
if args.detection_json:
imagename = op.basename(imagefile)
if imagename not in detections:
logging.error('Cant find image name "%s" in "%s"',
args.detection_json, imagename)
continue
detections_for_image = detections[imagename]
image_properties = detections_for_image['attributes']
for object_ in detections_for_image['labels']:
object_bddid = object_['id']
object_name = object_['category']
object_properties = {
key: value
for key, value in object_['attributes'].items()
if value != 'none'
}
object_properties.update(image_properties)
# Skip 3d object. TODO: import it to properties.
if 'box3d' in object_:
logging.warning('Will skip 3D object %d.' % object_bddid)
continue
# Get the bbox if exists.
x1 = y1 = width = height = None
if 'box2d' in object_:
box2d = object_['box2d']
x1 = int(float(box2d['x1']))
y1 = int(float(box2d['y1']))
width = int(float(box2d['x2']) - x1)
height = int(float(box2d['y2']) - y1)
if args.with_display:
roi = utilBoxes.bbox2roi((x1, y1, width, height))
util.drawScoredRoi(img, roi, object_name)
c.execute(
'INSERT INTO objects(imagefile,x1,y1,width,height,name) '
'VALUES (?,?,?,?,?,?)',
(imagefile, x1, y1, width, height, object_name))
objectid = c.lastrowid
# Get the polygon if it exists.
if 'poly2d' in object_:
if len(object_['poly2d']) > 1:
assert 0, len(object_['poly2d'])
polygon = object_['poly2d'][0]
polygon_name = None if polygon['closed'] else 'open_loop'
for pt in polygon['vertices']:
c.execute(
'INSERT INTO polygons(objectid,x,y,name) '
'VALUES (?,?,?,?)',
(objectid, pt[0], pt[1], polygon_name))
if args.with_display:
util.drawScoredPolygon(img,
[(int(x[0]), int(x[1]))
for x in polygon['vertices']],
object_name)
# Insert image-level and object-level attributes into
# "properties" table.
for key, value in object_properties.items():
c.execute(
'INSERT INTO properties(objectid,key,value) VALUES (?,?,?)',
(objectid, key, value))
# Segmentation annotations.
if args.segmentation_dir:
segmentation_path = op.join(args.segmentation_dir,
'%s_train_id.png' % filename)
if not op.exists(segmentation_path):
raise FileNotFoundError('Annotation file not found at "%s".' %
segmentation_path)
# Add image to the database.
maskfile = op.relpath(segmentation_path, args.rootdir)
c.execute('UPDATE images SET maskfile=? WHERE imagefile=?',
(maskfile, imagefile))
if args.with_display:
mask = imreader.maskread(maskfile)
img = util.drawMaskAside(img, mask, labelmap=None)
# Maybe display.
if args.with_display:
cv2.imshow('importKitti', img[:, :, ::-1])
if cv2.waitKey(-1) == 27:
args.with_display = False
cv2.destroyWindow('importKitti')