simple-faster-rcnn-pytorch
yolov3-tf2
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| simple-faster-rcnn-pytorch | yolov3-tf2 | |
|---|---|---|
| 1 | 3 | |
| 3,891 | 2,507 | |
| - | - | |
| 0.0 | 2.8 | |
| almost 3 years ago | about 1 month ago | |
| Jupyter Notebook | Jupyter Notebook | |
| GNU General Public License v3.0 or later | MIT License |
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simple-faster-rcnn-pytorch
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ISO Easy to Modify and Use Faster RCNN PyTorch Implementation
Hi all, as the title suggests I'm looking for a GitHub repo where I can edit a Faster RCNN implementation rather easily. I'm basically looking to test an idea where I have multiple branches with feature map and bounding boxes as inputs. I've modified the built-in torchvision implementation once before, but I think it's a little more complicated than I like, and I'd rather not release the entire torchvision package as part of my own work in the future. I have looked briefly into this repo https://github.com/chenyuntc/simple-faster-rcnn-pytorch/blob/master/trainer.py but it only supports a batch size of 1, and I'm not sure what it'd take to expand that capability. Is there anything better out there?
yolov3-tf2
What are some alternatives?
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SynthDet - SynthDet - An end-to-end object detection pipeline using synthetic data
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saliency - Framework-agnostic implementation for state-of-the-art saliency methods (XRAI, BlurIG, SmoothGrad, and more).