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Yolo v1 re-implementation

Pre-training

1. pretraing for 20 convolution layers using ImageNet 2012 datasets.

  • until Top 5 87% acc

Training

1. Using PASCAL 2007, 2012 datasets.

  • 15496 images for training (70%)
  • 6640 images for validation (30%)

2. 135 epochs, batch-size 64, momentum 0.9, decay 0.0005

3. Different learning rate for epochs

4. extensive data augmentation

Experiment

mAP 51.7 (Implement)
63.4 (In paper)

Class aeroplane bicycle bird boat bottle bus car cat chair cow
AP 74.8 51.7 56.9 36.6 16.0 68.0 46.3 85.1 26.7 51.7
Class dining table dog horse motorbike person potted plant sheep sofa train tv&monitor
AP 37.2 77.9 52.6 54.8 61.6 19.1 54.1 43.8 75.4 43.7

Test Images

horse_and_person result