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Cricket Shots Detection

Aim of the project:

The project focuses on classification of different cricket shots using various Deep Learning Algorithms.

Libraries and Frameworks used:

  1. Pandas
  2. Numpy
  3. Matplotlib
  4. Seaborn
  5. Tensorflow
  6. Keras
  7. sklearn
  8. glob
  9. OpenCV

Deep Learning Algorithms used:

  1. ResNet
  2. DenseNet
  3. InceptionNet
  4. EfficientNet

Accuracy and training time comparison of all the Deep Learning Algorithms

Accuracy
ResNet 86%
DenseNet 92%
InceptionNet 96%
EfficientNet 95%

Representation of different cricket shots

EDA

Bar plot of counts of each shot in the dataset

values

Pie chart for the distribution of shots in the dataset

ri

Accuracy and plots of all models

InceptionNetV2

inv2

DenseNet

densenet

ResNet50

resnet

EfficientNet

effnet

Conclusion

InceptionNet model performs better comparative to other models used on the above dataset.