def get(self):
# parse arguments
row = int(self.get_argument('row'))
col = int(self.get_argument('col'))
result = self.app.result
predicted_label = result.label_names[row]
actual_label = result.label_names[col]
# get list of vertices in that cell
region_label_data = result.confusion_matrix_item_freq.rows[row].cells[col].items
region_label_data = region_label_data[0:150] # limit to top 150 regions
region_indices = [ region.item_id for region in region_label_data]
regions_dict = self.app.irg_reader.BatchGetRegions(region_indices)
image_ids = [ region.image_id for region in regions_dict.itervalues()]
if self.app.image_loader == None:
LOG(INFO, 'loading images...')
self.app.image_loader = visutil.BatchImageLoader(self.app.images_uri)
self.imageid_to_jpeg = self.app.image_loader.BatchGetImages(image_ids)
regionid_to_svg = {}
for region_id, region in regions_dict.iteritems():
regionid_to_svg[region_id] = self.RenderRegionSvg(region)
params = { 'actual_label' : actual_label,
'predicted_label' : predicted_label,
'region_label_data' : region_label_data,
'regions_dict' : regions_dict,
'regionid_to_svg' : regionid_to_svg,
'labelid_to_labelnames' : result.label_names
}
self.render('confusion_matrix_cell.html', **params)
return
def __init__(self):
dataset_name = 'tide_v08_distractors'
base_uri = 'local://home/ubuntu/Desktop/vol-7f209e0c/itergraph/%s' % dataset_name
self.images_uri = '%s/cropped_scaled_photoid_to_image.pert' % (
base_uri)
self.matches_uri = '%s/usift/cbir/9e6c60d825c5a9814e19c0a735747011/itergraph/0ffd08c74629993310fd73f6461673af/merged_matches.pert' % (
base_uri)
self.irg_uri = '%s/usift/cbir/9e6c60d825c5a9814e19c0a735747011/itergraph/0ffd08c74629993310fd73f6461673af/image_region_graph.pert' % (
base_uri)
self.tide_uri = '%s/objectid_to_object.pert' % (base_uri)
self.graph = graph.GetCachedGraph(self.irg_uri, self.tide_uri)
self.image_loader = visutil.BatchImageLoader(self.images_uri)
self.graph_render = renderers.GraphNeighborhoodRenderer(self.graph)
print 'done loading'
self.application = tornado.web.Application(
[
(r"/", MainHandler, dict(app=self)),
(r"/graph", GraphHandler, dict(app=self)),
#(r"/vertex", VertexHandler, dict(app=self)),
#(r"/edge", EdgeHandler, dict(app=self)),
(r"/image", ImageHandler, dict(app=self)),
],
debug=True)
return
def __init__(self):
dataset_name = 'tide_v08_distractors'
base_uri = 'local://home/ubuntu/Desktop/vol-7f209e0c/itergraph/%s' % dataset_name
self.images_uri = '%s/cropped_scaled_photoid_to_image.pert' % (
base_uri)
self.matches_uri = '%s/usift/cbir/9e6c60d825c5a9814e19c0a735747011/itergraph/0ffd08c74629993310fd73f6461673af/merged_matches.pert' % (
base_uri)
self.image_graph_uri = '%s/usift/cbir/9e6c60d825c5a9814e19c0a735747011/itergraph/0ffd08c74629993310fd73f6461673af/image_graph.pert' % (
base_uri)
self.tide_uri = '%s/objectid_to_object.pert' % (base_uri)
# dataset_name = 'tide_v08'
# base_uri = 'local://media/vol-0449ca74/itergraph/%s' % dataset_name
# self.images_uri = '%s/cropped_scaled_photoid_to_image.pert' % (base_uri)
# self.matches_uri = '%s/usift/cbir/d27df409ad95e12823feed0c658eabeb/itergraph/1b8ba7a00a9d1cd558716ce882e8408f/merged_matches.pert' % (base_uri)
# self.image_graph_uri = '%s/usift/cbir/d27df409ad95e12823feed0c658eabeb/itergraph/1b8ba7a00a9d1cd558716ce882e8408f/image_graph.pert' % (base_uri)
# self.tide_uri = '%s/objectid_to_object.pert' % (base_uri)
# dataset_name = 'tide_v14_mixed_v2'
# base_uri = 'local://media/vol-0449ca74/itergraph/%s' % dataset_name
# self.images_uri = '%s/photoid_to_image.pert' % (base_uri)
# self.matches_uri = '%s/usift/cbir/654c8f59fd938958c1c739fd65949dad/itergraph/e4baab98c10a434d90d092c71ecb566c/merged_matches.pert' % (base_uri)
# self.image_graph_uri = '%s/usift/cbir/654c8f59fd938958c1c739fd65949dad/itergraph/e4baab98c10a434d90d092c71ecb566c/image_graph.pert' % (base_uri)
# self.tide_uri = '%s/objectid_to_object.pert' % (base_uri)
self.image_graph = tide_image_graph.GetCachedTideImageGraph(
self.image_graph_uri, self.tide_uri)
self.image_loader = visutil.BatchImageLoader(self.images_uri)
self.graph_render = renderers.TideImageGraphRenderer(self.image_graph)
self.match_renderer = renderers.MatchRenderer(self.matches_uri,
self.images_uri)
print 'done loading'
self.application = tornado.web.Application([
(r"/", MainHandler, dict(app=self)),
(r"/neighborhood", NeighborhoodGraphHandler, dict(app=self)),
(r"/objectsubgraph", ObjectSubgraphHandler, dict(app=self)),
(r"/match", MatchHandler, dict(app=self)),
(r"/image", ImageHandler, dict(app=self)),
],
debug=True)
return
def GetImageLoader(self):
if self.image_loader == None:
LOG(INFO, 'loading images...')
self.image_loader = visutil.BatchImageLoader(self.images_uri)
return self.image_loader
def main():
# images_uri = 'local://media/vol-0449ca74/itergraph/tide_v14/cropped_scaled_photoid_to_image_randomaccess.pert'
# tide_uri = 'local://media/vol-0449ca74/itergraph/tide_v14/objectid_to_object.pert'
# distractor_images_uri = 'local://media/vol-0449ca74/oxc1_100k/photoid_to_image.pert'
# output_base_uri = 'local://media/vol-0449ca74/itergraph/tide_v14_mixed_v2/'
# images_uri = 'local://media/vol-0449ca74/itergraph/tide_v16/photoid_to_image.pert'
# tide_uri = 'local://media/vol-0449ca74/itergraph/tide_v16/objectid_to_object.pert'
# distractor_images_uri = 'local://media/vol-0449ca74/oxc1_100k/photoid_to_image.pert'
# output_base_uri = 'local://media/vol-0449ca74/itergraph/tide_v16_mixed/'
images_uri = 'local://media/vol-0449ca74/itergraph/tide_v18/photoid_to_image.pert'
tide_uri = 'local://media/vol-0449ca74/itergraph/tide_v18/objectid_to_object.pert'
distractor_images_uri = 'local://media/vol-0449ca74/oxc1_100k/photoid_to_image.pert'
output_base_uri = 'local://media/vol-0449ca74/itergraph/tide_v18_mixed/'
output_tide_uri = '%s/objectid_to_object.pert' % (output_base_uri)
output_images_uri = '%s/photoid_to_image.pert' % (output_base_uri)
image_loader = visutil.BatchImageLoader(images_uri)
tide_objects = OpenTideDataset(tide_uri)
distractor_image_loader = DistractorImageLoader(distractor_images_uri)
CHECK_EQ(len(tide_objects), 2)
object_a = tide_objects[0]
object_b = tide_objects[1]
new_object_a = InitNewObject(object_a)
new_object_b = InitNewObject(object_b)
a_none_image_ids = [photo.id for photo in object_a.photos if photo.label == tide_pb2.NONE ]
b_none_image_ids = [photo.id for photo in object_b.photos if photo.label == tide_pb2.NONE ]
mixed_aux_images = {}
for i, (imageid_a, imageid_b) in enumerate(zip(a_none_image_ids, b_none_image_ids)):
mixed_aux_images[imageid_a] = (imageid_a, imageid_b)
mixed_image_ids = mixed_aux_images.keys()
n = int(len(mixed_image_ids)/2.0)
InitNoneLabels(new_object_a, mixed_image_ids[0:n])
InitNoneLabels(new_object_b, mixed_image_ids[n:-1])
new_objects = [new_object_a, new_object_b]
image_ids = []
for obj in new_objects:
for photo in obj.photos:
image_ids.append(photo.id)
image_ids.sort()
# write new tide pert
tide_writer = py_pert.ProtoTableWriter()
tide_writer.Open(tide_pb2.Object(), output_tide_uri, 1)
for obj in new_objects:
tide_writer.Add(iwutil.Uint64ToKey(obj.id), obj.SerializeToString())
tide_writer.Close()
# write new image pert
try:
image_writer = py_pert.ProtoTableWriter()
image_writer.Open(iw_pb2.JpegImage(), output_images_uri, 1)
used_image_ids = set()
progress = iwutil.MakeProgressBar(len(image_ids))
for i, image_id in enumerate(image_ids):
jpeg = None
if image_id in mixed_aux_images:
imageid_a, imageid_b = mixed_aux_images[image_id]
jpeg_a = image_loader.GetImage(imageid_a)
jpeg_b = image_loader.GetImage(imageid_b)
if jpeg_a == None or jpeg_b == None:
LOG(INFO, 'skipping missing jpeg')
continue
jpeg = CreateMixedJpeg(jpeg_a, jpeg_b)
else:
distractor = None
while True:
distractor = distractor_image_loader.GetNextImage()
if distractor.width > distractor.height:
break
CHECK(distractor)
jpeg = CreateMixedJpeg(image_loader.GetImage(image_id),
distractor)
CHECK(image_id not in used_image_ids)
CHECK(jpeg)
image_writer.Add(iwutil.Uint64ToKey(image_id), jpeg.SerializeToString())
used_image_ids.add(image_id)
progress.update(i)
image_writer.Close()
except:
pass
return