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Video Activity Recognition: AVA-II dataset

Looking into the possibility of analyzing simple activities (actors' poses) via single frames

File description:

  • input_ava.py: Used to generate the input numpy array.
  • input_ava_subsample.py: Used to generate the input numpy array with subsampling
  • resnet50_AVA.py: The resnet50 run on AVA data set.
  • resnet50_mnist.py The resnet50 run on mnist data set.
  • resnet101_AVA.py: The resnet101 run on AVA data set.
  • resnet101_mnist.py: The resnet101 run on mnist data set.
  • label_predict.py: Used to predict labels

Code running instruction:

First run input_ava.py:

python3 input_ava.py --data_path=AVA-II --image_path=/data/ece194n/AVA/keyframes --image_save_path=images

Then run resnet50_AVA.py to train the model:

CUDA_VISIBLE_DEVICES=0 python3 resnet50_AVA.py

Then run labels_predict.py to see the output accuracy

CUDA_VISIBLE_DEVICES=0 python3 label_predict.py

ava-ii's People

Contributors

derenlei avatar oliversun110 avatar

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