Techniques for controlled generation of training data for machine learning enabled image enhancement
AssigneeBlinkAI Technologies, Inc.
InventorsLiying Shen, Bo Zhu, Haitao Yang
Life of this patent
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Abstract
Described herein are systems and techniques for generating training data for use in training a machine learning model for image enhancement. The system may access a target image of a displayed video frame, wherein the target image represents a target output of the machine learning model. The system may access an input image of the displayed video frame, wherein the input image corresponds to the target image and represents an input to the machine learning model. The system may train the machine learning model using the target image and the input image corresponding to the target image to obtain a trained machine learning model.
Claims12
A method of training a machine learning model for enhancing images, the method comprising:
- using at least one computer hardware processor to perform:
- accessing a target image of a displayed video frame, wherein the target image represents a target output of the machine learning model;
- accessing an input image of the displayed video frame, wherein the input image corresponds to the target image and represents an input to the machine learning model;
- and
- training the machine learning model using the target image and the input image corresponding to the target image to obtain a trained machine learning model.
A system for training a machine learning model for enhancing images, the system comprising:
- a display for displaying a video frame of a video;
- a digital imaging device configured to:
- capture a target image of the displayed video frame, wherein the target image represents a target output of the machine learning model;
- and
- capture an input image of the displayed video frame, wherein the input image corresponds to the target image and represents an input to the machine learning model;
- and
- a computing device comprising at least one hardware processor and at least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by the at least one hardware processor, cause the at least one hardware processor to perform:
- accessing the target image and the input image;
- and
- training the machine learning model using the target image and the input image corresponding to the target image to obtain a trained machine learning model.
At least one computer readable storage medium storing processor-executable instructions that, when executed by at least one processor, cause the at least one processor to perform:
- accessing a target image of a displayed video frame, wherein the target image represents a target output of a machine learning model;
- accessing an input image of the displayed video frame, wherein the input image corresponds to the target image and represents an input to the machine learning model;
- and
- training the machine learning model using the target image and the input image corresponding to the target image to obtain a trained machine learning model.
Dependencies are inferred from the claim text.