defforward(self, batched_inputs):ifnotself.training:returnself.inference(batched_inputs) images = self.preprocess_image(batched_inputs)if"instances"inbatched_inputs[0]: gt_instances = [x["instances"].to(self.device)forxinbatched_inputs]else: gt_instances =Nonefeatures = self.backbone(ima...
for input, prop in zip(batched_inputs, proposals): img = input["image"].cpu().numpy() ... img = img.transpose(1, 2, 0) ... v_pred = Visualizer(img, None) v_pred = v_pred.overlay_instances( boxes=prop.proposal_boxes[0:box_size].tensor.cpu().numpy() ) prop_img = v_pr...
def forward(self, batched_inputs): if not self.training: return self.inference(batched_inputs) images = self.preprocess_image(batched_inputs) if "instances" in batched_inputs[0]: gt_instances = [x["instances"].to(self.device) for x in batched_inputs] else: gt_instances = None f...
The batched ``list[mapped_dict]`` is what this dataloader will return. Args: cfg (CfgNode): the config mapper (callable): a callable which takes a sample (dict) from dataset and returns the format to be consumed by the model. By default it will be `DatasetMapper(cfg, True)`. Return...
File"/home/star/Detectron2/detectron2-master/detectron2/layers/__init__.py", line 5,in<module>from.nmsimportbatched_nms, batched_nms_rotated, nms, nms_rotated File"/home/star/Detectron2/detectron2-master/detectron2/layers/nms.py", line 6,in<module>fromtorchvision.opsimportboxes as box...
File "/home/ecoation/anaconda3/envs/detectron2/lib/python3.8/site-packages/detectron2/modeling/meta_arch/rcnn.py", line 228, in preprocess_image images = [self._move_to_current_device(x["image"]) for x in batched_inputs] File "/home/ecoation/anaconda3/envs/detectron2/lib/python3.8...
# If True, each batch should contain only images for which the aspect ratio # is compatible. This groups portrait images together, and landscape images # are not batched with portrait images. _C.DATALOADER.ASPECT_RATIO_GROUPING = True
[0, -1, 1] # Total number of RPN examples per image _C.MODEL.RPN.BATCH_SIZE_PER_IMAGE = 256 # Target fraction of foreground (positive) examples per RPN minibatch _C.MODEL.RPN.POSITIVE_FRACTION = 0.5 # Weights on (dx, dy, dw, dh) for normalizing RPN anchor regression targets _C...
org.fh.util; import java.io.File; import java.io.FileInputStream; import java.util.ArrayList;...
cost_mask = batch_sigmoid_ce_loss_jit(out_mask, tgt_mask) RuntimeError: nvrtc: error: invalid value for --gpu-architecture (-arch) nvrtc compilation failed: #define NAN __int_as_float(0x7fffffff) #define POS_INFINITY __int_as_float(0x7f800000) ...