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)