pytorch_fasterrcnn
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Fine-Tune Pytorch Faster RCNN for your own task.
Pytorch Faster RCNN
- Note that this PyPi package is no longer maintained. It will work fine upto this release, but I won't do bug fixes.
- The entire code and API is migrated to Quickvison, it has similar API and is maintained actively.
Faster RCNN Fine-Tune Implementation in Pytorch.
How to use ?
- git clone the repo
git clone https://github.com/oke-aditya/pytorch_fasterrcnn.git
- Install PyTorch and torchvision for your system.
Simply edit the config file to set your hyper parameters.
- Keep the training and validation csv file as follows
NOTE
Do not use target as 0 class. It is reserved as background.
image_id xtl ytl xbr ybr target
1 xmin ymin xmax ymax 1
1 xmin ymin xmax ymax 2
2 xmin ymin xmax ymax 3
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Simply edit the config file to set your hyper parameters
-
Run the train.py file
Features: -
- It works for multiple class object detection.
Backbones Supported: -
-
Note that backbones are pretrained on imagenet.
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Following backbones are supported
- vgg11, vgg13, vgg16, vgg19
- resnet18, resnet34, resnet50, resnet101, resnet152
- renext101
- mobilenet_v2
Sample Outputs
Helmet Detector
Mask Detector
If you like the implemenation or have taken an inspiration do give a star :-)