pytorch based implementation faster rcnn

pytorch-faster-rcnn

• pytorch-faster-rcnn
  • Framework Structure
    • backbone
    • config
    • dataloader
    • test
    • utils

pytorch based implementation of faster rcnn framework(Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks)

Framework Structure

backbone

This module includes backbone feature extraction network

• vgg16:vgg16 net network(Very Deep Convolutional Networks for Large-Scale Image Recognition)
• fpn101:resnet101 fpn network(Deep Residual Learning for Image Recognition) (Feature Pyramid Networks for Object Detection)
• hrnet:high resolution net(Deep High-Resolution Representation Learning for Visual Recognition)
• mobile_net:mobile_net v2 network(MobileNetV2: Inverted Residuals and Linear Bottlenecks)

config

This module includes config parameters in training period and testing period

• test_config: specify config parameters in testing period like model_file, image_path_dir, save_dir, etc.
• train_config: specify config parameters in training period like backbone network, batch_size, image_path_dir, anchor_size, ect.

dataloader

This module inherits pytorch dataloader classes, dataset IO.You can also generate your own dataset dataloader IO and put it in this module

• coco_dataset: coco(Common Objects in Context) dataset dataloader IO

test

This module includes the utils function test(common called unit test, also called UT)

• anchor_utils_test: some unit testing for utils/anchor_utils.py

utils

This module includes some utilies for image processing, network architectures building, anchor generating, loss function, etc.

• anchor_utils: some basic function for building anchors
• im_utils: some basic function for image processing

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