def __init__(self, annotations_file, words_count, vocab=None):
if not os.path.isfile(annotations_file):
archive_path = os.path.join(config.base_path, 'captions_train-val2014.zip')
ensure_file(archive_path, 'http://msvocds.blob.core.windows.net/annotations-1-0-3/captions_train-val2014.zip')
z = zipfile.ZipFile(archive_path)
infolist = []
for zipinfo in z.infolist():
zipinfo.filename = os.path.basename(zipinfo.filename)
infolist.append(zipinfo)
z.extractall(config.coco_path, infolist)
with open(annotations_file) as f:
self.dataset = json.load(f)
self.images = {image['id']: image for image in self.dataset['images']}
self.img_to_anns = defaultdict(list)
self.annotations = {}
for ann in self.dataset['annotations']:
self.annotations[ann['id']] = ann
self.img_to_anns[ann['image_id']] += [ann]
if vocab is not None:
self.vocab = vocab
else:
all_words = []
for ann in self.load_annotations(self.img_ids()):
all_words += word_tokenize(ann['caption'].lower())
self.vocab = Vocab(all_words, words_count)
def expand_set_files(bot, persistence, set_data):
for sticker in set_data["stickers"]:
file_id = sticker["file_id"]
file = ensure_file(bot, persistence, file_id)
yield {
"set_name": set_data["name"],
"set_title": set_data["title"],
"emoji": sticker["emoji"],
"file_id": file_id,
"url": file["file_path"],
"size": file["file_size"],
}
def __init__(self):
models_dir = config.base_path
net_file = os.path.join(models_dir, 'tensorflow_inception_graph.pb')
synset_file = os.path.join(models_dir, 'imagenet_comp_graph_label_strings.txt')
ensure_dir(models_dir)
if not (os.path.isfile(net_file) and os.path.isfile(synset_file)):
archive_path = os.path.join(models_dir, 'inception5h.zip')
ensure_file(archive_path, 'https://storage.googleapis.com/download.tensorflow.org/models/inception5h.zip')
z = zipfile.ZipFile(archive_path)
z.extractall(models_dir)
self.synset = []
with open(synset_file) as f:
for line in f:
self.synset.append(line)
graph_def = tf.GraphDef()
with open(net_file) as f:
graph_def.ParseFromString(f.read())
tf.import_graph_def(graph_def)
self.session = tf.Session()
def workflow_single_ntuple(input_ntp, input_yml, output_suffix, aux_workflows,
cpp_template='../postprocess/cpp_templates/rdx.cpp',
**kwargs):
input_ntp = ensure_file(input_ntp)
print('{}Working on {}...{}'.format(TC.GREEN, input_ntp, TC.END))
cpp_template = abs_path(cpp_template)
bm_cmd = 'babymaker -i {} -o baby.cpp -n {} -t {}'
aux_ntuples = [w(input_ntp, **kwargs) for w in aux_workflows]
if aux_ntuples:
bm_cmd += ' -f ' + ' '.join(aux_ntuples)
bm_cmd = workflow_bm_cli(bm_cmd, **kwargs).format(
abs_path(input_yml), input_ntp, cpp_template)
run_cmd(bm_cmd, **kwargs)
workflow_compile_cpp('baby.cpp', **kwargs)
run_cmd('./baby.exe --{}'.format(output_suffix), **kwargs)
