TernausNetV2
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ternaus
TernausNetV2: Fully Convolutional Network for Instance Segmentation
Hello, I have a question: how to predict areas of an image (binary mask) where different objects touch or very close to each other?
Hi, i was trying to use the demo.ipynb file given, but it throws an import error. ``` ImportError Traceback (most recent call last) in ----> 1 from models.ternausnet2 import TernausNetV2...
Hi, I have a simple request to make the code runnable in cpu-only machine. It is more testing the Python notebook. Thank you.
When I run Demo.ipynb, this error occurred. `ImportError: /tmp/torch_extensions/inplace_abn/inplace_abn.so: undefined symbol: _ZN2at5ErrorC1ENS_14SourceLocationESs` Has someone solved the problem?
Anyone happen to encounter the same problem? My envrionment: Ubuntu 16.04 Torch 1.0 ninja 1.8.2.post2 cuda 9.2 RuntimeError: Error building extension 'inplace_abn': [1/3] c++ -MMD -MF inplace_abn_cpu.o.d -DTORCH_EXTENSION_NAME=inplace_abn -DTORCH_API_INCLUDE_EXTENSION_H -isystem...
I was using the load_image function given in the demo.ipynb notebook. I tested it for vegas and paris. For vegas i am getting image similar to what we get when...
Just wonder is there any plan to release training scripts? we don't any details about data preparing and loss function.....
I want to use my own dataset, but I don't want to train the network from scratch. How can I implement transfer learning on the pre-trained network?
Running Demo.ipynb yields runtime error at line: prediction = torch.sigmoid(model(input_img)).data[0].cpu().numpy() RuntimeError: Given groups=1, weight of size [64, 11, 3, 3], expected input[1, 6 72, 672, 11] to have 11 channels,...
