UNDERWATER CAMERA BIOMASS DISTRIBUTION FORECAST
Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for underwater camera biomass prediction. In some implementations, an exemplary method includes obtaining one or more images of a population of fish captured by an underwater camera; providing data corresponding to the one or more images to a model trained to predict biomass values; obtaining output of the trained model including a predicted biomass value indicating a future biomass of a fish within the population of fish; and determining an action based on the predicted biomass value.
1 . A method comprising:
obtaining one or more images of a population of fish captured by an underwater camera;
providing data corresponding to the one or more images to a model trained to predict biomass values;
obtaining output of the trained model including a predicted biomass value indicating a future biomass of a fish within the population of fish; and
determining an action based on the predicted biomass value.
2 . The method of claim 1 , wherein the data corresponding to the one or more images comprises:
historical data of the fish, including one or more values indicating historical biomasses of the fish.
3 . The method of claim 1 , comprising training the model, wherein training the model includes:
providing a portion of historical data of one or more fish not included in the population of fish to the model;
obtaining output of the model indicating predicted biomass values of the one or more fish;
generating an error term by comparing the predicted biomass values to known biomass values of the one or more fish included in a second portion of the historical data; and
adjusting one or more parameters of the model based on the error term.
4 . The method of claim 3 , wherein adjusting the one or more parameters of the model based on the error term comprises:
providing the error term to the model configured to perform backpropagation.
5 . The method of claim 1 , comprising:
determining, based on the one or more images, a data set including a value that indicates a length between a first point on the fish and a second point on the fish.
6 . The method of claim 5 , comprising:
providing the data set including the value that indicates the length between the first point on the fish and the second point on the fish to a model trained to predict biomass; and
obtaining output of the model trained to predict biomass as a biomass value of the fish.
7 . The method of claim 6 , wherein the data corresponding to the one or more images comprises:
the biomass value of the fish.
8 . The method of claim 5 , comprising:
detecting the first point and second point on the fish.
9 . The method of claim 8 , wherein detecting the points comprises:
providing the images to a model trained to detect feature points on a fish body.
10 . The method of claim 1 , comprising:
detecting the fish within an image of the one or more images using a model trained to detect fish.
11 . The method of claim 1 , wherein the action comprises:
adjusting a feeding system providing feed to the fish.
12 . The method of claim 1 , wherein the action comprises:
sending data including the predicted biomass value to a user device, wherein the data is configured to, when displayed on the user device, present a user of the user device with a visual representation of the predicted biomass value.
13 . A non-transitory, computer-readable medium storing one or more instructions executable by a computer system to perform operations comprising:
obtaining one or more images of a population of fish captured by an underwater camera;
providing data corresponding to the one or more images to a model trained to predict biomass values;
obtaining output of the trained model including a predicted biomass value indicating a future biomass of a fish within the population of fish; and
determining an action based on the predicted biomass value.
14 . The medium of claim 13 , wherein the data corresponding to the one or more images comprises:
historical data of the fish, including one or more values indicating historical biomasses of the fish.
15 . The medium of claim 13 , wherein the operations comprise training the model, wherein training the model includes:
providing a portion of historical data of one or more fish not included in the population of fish to the model;
obtaining output of the model indicating predicted biomass values of the one or more fish;
generating an error term by comparing the predicted biomass values to known biomass values of the one or more fish included in a second portion of the historical data; and
adjusting one or more parameters of the model based on the error term.
16 .- 19 . (canceled)
20 . A computer-implemented system, comprising:
one or more computers; and
one or more computer memory devices interoperably coupled with the one or more computers and having tangible, non-transitory, machine-readable media storing one or more instructions that, when executed by the one or more computers, perform one or more operations comprising:
obtaining one or more images of a population of fish captured by an underwater camera;
providing data corresponding to the one or more images to a model trained to predict biomass values;
obtaining output of the trained model including a predicted biomass value indicating a future biomass of a fish within the population of fish; and
determining an action based on the predicted biomass value.
21 . The method of claim 1 , wherein the predicted biomass value includes a distribution of biomasses for a group of fish that includes the fish.
22 . The method of claim 21 , wherein the distribution of biomasses for the group of fish includes a probability distribution.
23 . The method of claim 1 , wherein the action comprises:
adjusting one or more of a fish health forecast or a sales price forecast.
24 . The method of claim 1 , wherein the predicted biomass value includes an uncertainty estimate.