(self, cfg, img_size=(416, 416), verbose=False)
| 446 | # YOLOv3 object detection model |
| 447 | |
| 448 | def __init__(self, cfg, img_size=(416, 416), verbose=False): |
| 449 | super(Darknet, self).__init__() |
| 450 | |
| 451 | self.module_defs = parse_model_cfg(cfg) |
| 452 | self.module_list, self.routs = create_modules(self.module_defs, img_size, cfg) |
| 453 | self.yolo_layers = get_yolo_layers(self) |
| 454 | # torch_utils.initialize_weights(self) |
| 455 | |
| 456 | # Darknet Header https://github.com/AlexeyAB/darknet/issues/2914#issuecomment-496675346 |
| 457 | self.version = np.array([0, 2, 5], dtype=np.int32) # (int32) version info: major, minor, revision |
| 458 | self.seen = np.array([0], dtype=np.int64) # (int64) number of images seen during training |
| 459 | self.info(verbose) if not ONNX_EXPORT else None # print model description |
| 460 | |
| 461 | def forward(self, x, augment=False, verbose=False): |
| 462 |
no test coverage detected