(self, index)
| 126 | return self.length |
| 127 | |
| 128 | def __getitem__(self, index): |
| 129 | # Delay loading LMDB data until after initialization: https://github.com/chainer/chainermn/issues/129 |
| 130 | if self.env is None: |
| 131 | self._init_db() |
| 132 | env = self.env |
| 133 | with env.begin(write=False) as txn: |
| 134 | byteflow = txn.get(self.keys[index]) |
| 135 | ref = loads_pyarrow(byteflow) |
| 136 | # img |
| 137 | ori_img = cv2.imdecode(np.frombuffer(ref['img'], np.uint8), |
| 138 | cv2.IMREAD_COLOR) |
| 139 | img = cv2.cvtColor(ori_img, cv2.COLOR_BGR2RGB) |
| 140 | img_size = img.shape[:2] |
| 141 | # mask |
| 142 | seg_id = ref['seg_id'] |
| 143 | mask_dir = os.path.join(self.mask_dir, str(seg_id) + '.png') |
| 144 | # sentences |
| 145 | idx = np.random.choice(ref['num_sents']) |
| 146 | sents = ref['sents'] |
| 147 | # transform |
| 148 | # mask transform |
| 149 | mask = cv2.imdecode(np.frombuffer(ref['mask'], np.uint8), |
| 150 | cv2.IMREAD_GRAYSCALE) |
| 151 | mask = mask / 255. |
| 152 | if self.mode == 'train': |
| 153 | sent = sents[idx] |
| 154 | # sentence -> vector |
| 155 | img, mask, sent = self.convert(img, mask, sent, inference=False) |
| 156 | word_vec = tokenize(sent, self.word_length, True).squeeze(0) |
| 157 | pad_mask = (word_vec != 0).float() |
| 158 | return img, word_vec, mask, pad_mask |
| 159 | elif self.mode == 'val': |
| 160 | # sentence -> vector |
| 161 | sent = sents[-1] |
| 162 | word_vec = tokenize(sent, self.word_length, True).squeeze(0) |
| 163 | pad_mask = (word_vec != 0).float() |
| 164 | img, mask, sent = self.convert(img, mask, sent, inference=False) |
| 165 | return img, word_vec, mask, pad_mask |
| 166 | else: |
| 167 | # sentence -> vector |
| 168 | word_vecs = [] |
| 169 | pad_masks = [] |
| 170 | for sent in sents: |
| 171 | word_vec = tokenize(sent, self.word_length, True).squeeze(0) |
| 172 | word_vecs.append(word_vec) |
| 173 | pad_mask = (word_vec != 0).float() |
| 174 | pad_masks.append(pad_mask) |
| 175 | img, mask, sent = self.convert(img, mask, sent, inference=True) |
| 176 | return ori_img, img, word_vecs, mask, pad_masks, seg_id, sents |
| 177 | |
| 178 | def convert(self, img, mask, sent, inference=False): |
| 179 | img = Image.fromarray(np.uint8(img)) |
nothing calls this directly
no test coverage detected