shida666
commented
4 years ago 已解决，yaml文件不同于detectron2，可改为以下： python demo/demo.py --config-file /root/detectron2-ResNeSt/configs/COCO-InstanceSegmentation/mask_cascade_rcnn_R_50_FPN_syncbn_1x.yaml \ --input test_img/input/0_original.jpg test_img/input/1.jpg test_img/input/2.png test_img/input/3.png test_img/input/4.png --output test_img/output/ \ --opts MODEL.WEIGHTS /root/detectron2-ResNeSt/pretrain_model/pretrain_model/ResNeSt50/mask_rcnn_ResNeSt_50_FPN_syncBN_1x-f442d863.pth
最近想用下ResNeSt，于是按照步骤安装了detectron2-ResNeSt，但是在运行时遇到一点问题，错误如下： Traceback (most recent call last): File "demo/demo.py", line 89, in
predictions, visualized_output = demo.run_on_image(img)
File "/root/detectron2-ResNeSt/demo/predictor.py", line 48, in run_on_image
predictions = self.predictor(image)
File "/root/anaconda3/envs/pytorch1.4.0/lib/python3.6/site-packages/detectron2/engine/defaults.py", line 196, in call
predictions = self.model([inputs])[0]
File "/root/anaconda3/envs/pytorch1.4.0/lib/python3.6/site-packages/torch/nn/modules/module.py", line 532, in call
result = self.forward(*input, *kwargs)
File "/root/anaconda3/envs/pytorch1.4.0/lib/python3.6/site-packages/detectron2/modeling/meta_arch/rcnn.py", line 108, in forward
return self.inference(batched_inputs)
File "/root/anaconda3/envs/pytorch1.4.0/lib/python3.6/site-packages/detectron2/modeling/metaarch/rcnn.py", line 165, in inference
proposals, = self.proposal_generator(images, features, None)
File "/root/anaconda3/envs/pytorch1.4.0/lib/python3.6/site-packages/torch/nn/modules/module.py", line 532, in call
result = self.forward(input, **kwargs)
File "/root/anaconda3/envs/pytorch1.4.0/lib/python3.6/site-packages/detectron2/modeling/proposal_generator/rpn.py", line 182, in forward
self.training,
File "/root/anaconda3/envs/pytorch1.4.0/lib/python3.6/site-packages/detectron2/modeling/proposal_generator/rpn_outputs.py", line 142, in find_top_rpn_proposals
keep = batched_nms(boxes.tensor, scores_per_img, lvl, nms_thresh)
File "/root/anaconda3/envs/pytorch1.4.0/lib/python3.6/site-packages/detectron2/layers/nms.py", line 17, in batched_nms
return box_ops.batched_nms(boxes, scores, idxs, iou_threshold)
File "/root/anaconda3/envs/pytorch1.4.0/lib/python3.6/site-packages/torchvision/ops/boxes.py", line 75, in batched_nms
boxes_for_nms = boxes + offsets[:, None]
RuntimeError: The size of tensor a (1741) must match the size of tensor b (4741) at non-singleton dimension 0
我的输入如果是detectron2上原有的R50-FPN,即 python demo/demo.py --config-file /root/detectron2-ResNeSt/configs/COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml \
但是如果输入换为ResNeSt50，即 python demo/demo.py --config-file /root/detectron2-ResNeSt/configs/COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml \