System and method for implementing an experiment remotely and determining an output using a computer vision model

A method for implementing an experiment remotely and determining an output of the experiment using a computer vision model, wherein the method comprising:

• implementing the experiment remotely through a user device by a user;
• obtaining using an image capturing device, an input data of the experiment, wherein the input data comprises a video or an image;
• extracting using a frame acquisition method, one or more frames from the input data of the experiment;
• processing the one or more frames to obtain a binary image of the experiment for each frame using a computer vision model;
• determining a closed curve around a boundary of the binary image of the experiment to highlight a region of interest for locating the experiment in each frame using a contour detection method;
• determining co-ordinates of the experiment by illustrating a bounding box over the experiment in each frame using the closed curve around the boundary of the binary image of the experiment;
• and
• determining an output of the experiment from every two consecutive frames of the one or more frames by the computer vision model that calculates (i) an Euclidean distance between two consecutive centroids of the illustrated bounding box of the two consecutive frames and (ii) a time difference between the two consecutive frames of centroids of the experiment.

One or more non-transitory computer readable storage mediums storing one or more sequences of instructions, which when executed by one or more processors, causes a method for implementing an experiment remotely and determining an output of the experiment using a computer vision model, wherein the method comprising:

• implementing the experiment remotely through a user device by a user;
• obtaining using an image capturing device, an input data of the experiment, wherein the input data comprises a video or an image;
• extracting using a frame acquisition method, one or more frames from the input data of the experiment;
• processing the one or more frames to obtain a binary image of the experiment for each frame using a computer vision model;
• determining a closed curve around a boundary of the binary image of the experiment to highlight a region of interest for locating the experiment in each frame using a contour detection method;
• determining co-ordinates of the experiment by illustrating a bounding box over the experiment in each frame using the closed curve around the boundary of the binary image of the experiment;
• and
• determining an output of the experiment from every two consecutive frames of the one or more frames by the computer vision model that calculates (i) an Euclidean distance between two consecutive centroids of the illustrated bounding box of the two consecutive frames and (ii) a time difference between the two consecutive frames of centroids of the experiment.