jmmaheswar/diqa

DIQA

In this research study, key frames were extracted from a collection of videos captured using different devices, including LG, iPhone SE, and iPhone 6. The selected videos were 10 seconds in duration and encompassed various documents with distinct characteristics such as shadows, blur, and varied brightness. The goal of this investigation was to evaluate the quality of the extracted key frames, focusing on their suitability for document analysis tasks.

Coefficient of determination (R^2): 0.94

Considering that the model is a linear regression, the sharpness_prediction values can be interpreted as the model's estimated sharpness based on the given input features. The model aims to find a linear relationship between the input features and the sharpness value.

Based on the provided data, we can make a few observations:

The sharpness_prediction values generally follow a similar trend as the actual sharpness values. In some cases, the predicted values are close to the actual values, indicating that the linear regression model captures the underlying relationship reasonably well.

However, there are cases where the predicted sharpness values deviate from the actual values. This could be due to various factors such as noise in the data, the limitations of the linear regression model in capturing complex relationships, or potential issues with the model's training or input features.

To evaluate the goodness of the linear regression model, it would be helpful to assess its performance using appropriate evaluation metrics such as mean squared error (MSE), mean absolute error (MAE), or R-squared (coefficient of determination). These metrics provide a quantitative measure of the model's accuracy and how well it fits the data.

It's important to note that a single snapshot of data is not sufficient to draw definitive conclusions about the model's overall performance. A thorough evaluation would require assessing the model on a larger dataset, ideally with a separate test set to evaluate its generalization ability.