Comments (3)
Please feel free to use the outputs. However, we don't have scale information. We only have distributed raster images without any scale information.
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Cool, thank you. In that case I'll just give them reasonable random sizes.
from floorplantransformation.
Actually I just realised that I can probably infer scale from the width of the doors.
This website seems to give specs on that:
http://web.mit.edu/cron/group/chinahousing/english/resources/BuildingCode.html
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Related Issues (20)
- To know Support gpu and cuda versions. HOT 1
- bad performance of pytorch model compared to lua HOT 50
- Hello,i dont know generated floorplan.txt last two column means what, could you explain it,thanks HOT 1
- The instruction for running annotator
- Licence for this project HOT 2
- No such file or directory: '../data/train.txt' HOT 3
- help with torch version
- Running predicition on a single image (PyTorch)
- Provided pre-trained model for Pytorch does not perform good. HOT 2
- Error while running renderer.py HOT 1
- init.lua:389: module 'cv' not found:No LuaRocks module found for cv HOT 1
- Don'tHavePermissionToAccessUrl HOT 4
- Update the DRN weights webroot url
- how to generate floorplan.txt file for any other image in the dataset in python
- The floor is not visible in the 3D output HOT 1
- Getting exception immediately after training starts
- The trained model HOT 3
- PYTORCH Prediction output HOT 3
- obtain the original R2V image
- Can we get you pretrained model? HOT 1
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