Note that bbox should be a list or tuple of (x1, y1, x2, y2)
(self, image_id:int, category_id:int, bbox:list, score:float)
| 304 | self.mask_data = [] |
| 305 | |
| 306 | def add_bbox(self, image_id:int, category_id:int, bbox:list, score:float): |
| 307 | """ Note that bbox should be a list or tuple of (x1, y1, x2, y2) """ |
| 308 | bbox = [bbox[0], bbox[1], bbox[2]-bbox[0], bbox[3]-bbox[1]] |
| 309 | |
| 310 | # Round to the nearest 10th to avoid huge file sizes, as COCO suggests |
| 311 | bbox = [round(float(x)*10)/10 for x in bbox] |
| 312 | |
| 313 | self.bbox_data.append({ |
| 314 | 'image_id': int(image_id), |
| 315 | 'category_id': get_coco_cat(int(category_id)), |
| 316 | 'bbox': bbox, |
| 317 | 'score': float(score) |
| 318 | }) |
| 319 | |
| 320 | def add_mask(self, image_id:int, category_id:int, segmentation:np.ndarray, score:float): |
| 321 | """ The segmentation should be the full mask, the size of the image and with size [h, w]. """ |
no test coverage detected