WarBean/tps_stn_pytorch
PyTorch implementation of Spatial Transformer Networks with Thin Plate Spline for automatic image rectification before classification.
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This repository provides a PyTorch implementation of Spatial Transformer Networks using Thin Plate Spline (TPS) transformations. The approach achieves spatial invariance by automatically rectifying distorted or transformed input images before feeding them into a classification network. The TPS transformation is particularly powerful as it can warp images in arbitrary ways. The implementation is end-to-end differentiable and can be plugged into existing architectures like AlexNet or ResNet without extra supervision, and has been applied to OCR tasks for rectifying distorted text images.
Frequently asked
- What is WarBean/tps_stn_pytorch?
- PyTorch implementation of Spatial Transformer Networks with Thin Plate Spline for automatic image rectification before classification.
- Is tps_stn_pytorch open source?
- Yes — WarBean/tps_stn_pytorch is an open-source project tracked on heatdrop.
- What language is tps_stn_pytorch written in?
- WarBean/tps_stn_pytorch is primarily written in Python.
- How popular is tps_stn_pytorch?
- WarBean/tps_stn_pytorch has 957 stars on GitHub.
- Where can I find tps_stn_pytorch?
- WarBean/tps_stn_pytorch is on GitHub at https://github.com/WarBean/tps_stn_pytorch.