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

Bar plot of counts of each shot in the dataset

Pie chart for the distribution of shots in the dataset

Accuracy and plots of all models

InceptionNetV2

DenseNet

ResNet50

EfficientNet

Conclusion

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