Visual processing method and device based on augmented reality glasses

Abstract

The invention discloses a visual processing method and device based on augmented reality glasses, and relates to the technical field of augmented reality glasses. In the method, a first video corresponding to a target goldfish is acquired; extracting the first video to obtain behavior features and posture features; inputting the behavior features and the posture features into a preset model for processing to obtain a first judgment result; if the first judgment result is an abnormal result, obtaining historical feeding time and historical feeding amount of the target goldfish; determining a first feeding amount according to the target period, and when the historical feeding amount is the same as the first feeding amount, determining to obtain a target time difference value; and when the target time difference value is greater than a preset first time threshold value, determining that the target goldfish is in a hungry state, generating feeding prompt information according to the hungry state, and sending the feeding prompt information to the target augmented reality glasses. By implementing the technical scheme provided by the invention, the problem of insufficient or excessive feeding amount caused by a traditional evaluation method based on time is avoided, and the feeding accuracy is improved.

Description

Technical Field

[0001] The present application relates to the technical field of augmented reality glasses, and in particular to a visual processing method and device based on augmented reality glasses. Background Art

[0002] Monitoring the hunger status of goldfish is a key link to ensure their healthy growth and maintain the ecological balance in the aquarium. As an aquatic vertebrate, the growth rate, behavioral habits and physiological function of goldfish are closely related to their feeding behavior. Long-term hunger will significantly inhibit the growth of goldfish, weaken their immune system function, and lead to a series of adverse physical signs such as emaciation, weak fins, and dull body color. In extreme cases, hunger may also induce a variety of diseases, seriously reducing the survival probability and quality of life of goldfish.

[0003] Therefore, accurately assessing the hunger state of goldfish and adjusting feeding strategies accordingly are crucial to ensure the health of goldfish. However, in current goldfish breeding practices, the assessment of goldfish hunger state mainly relies on a rough estimate of feeding time, which is used as a reference for arranging subsequent feeding. However, this time-based assessment method cannot accurately reflect the actual nutritional needs and satiety of goldfish, resulting in insufficient or excessive feeding, which in turn has an adverse effect on the growth, development and health of goldfish.

[0004] Therefore, there is an urgent need for a visual processing method and device based on augmented reality glasses that can solve the above-mentioned technical problems. Summary of the invention

[0005] The present application provides a visual processing method and device based on augmented reality glasses. The method collects activity videos of target goldfish through augmented reality glasses, analyzes and processes the activity videos, determines the state of the target goldfish, and then judges whether the target goldfish is in a hungry state based on historical feeding time and feeding amount. This method can more accurately reflect the actual nutritional needs and satiety of the goldfish, thereby avoiding the problem of insufficient or excessive feeding caused by traditional time-based evaluation methods and improving the accuracy of feeding.

[0006] In a first aspect, the present application provides a visual processing method based on augmented reality glasses, which is applied to a server, and the method includes: obtaining a first video corresponding to a target goldfish, the first video is a video of the target goldfish moving in water using the target augmented reality glasses, and the target goldfish is any goldfish to be monitored; identifying the first video to obtain a target period, which is the current growth period of the target goldfish, and the growth period includes the fry period, the young fish period and the adult fish period; extracting the first video to obtain behavioral characteristics and body characteristics; inputting the behavioral characteristics and body characteristics into a preset model for processing to obtain a first judgment result; if the first judgment result is an abnormal result, obtaining The target goldfish's historical feeding time and historical feeding amount; determining a first feeding amount according to a target period, and when the historical feeding amount is the same as the first feeding amount, confirming the acquisition of a target time difference, where the target time difference is the difference between the historical feeding time and the first time, and the first time is the time corresponding to the acquisition of the first video; determining a preset first time threshold according to the first feeding amount, and judging whether the target time difference is greater than the preset first time threshold; when the target time difference is greater than the preset first time threshold, confirming that the target goldfish is in a hungry state, generating feeding prompt information according to the hungry state, and sending the feeding prompt information to the target augmented reality glasses so that the user can view the feeding prompt information according to the target augmented reality glasses.

[0007] By adopting the above technical solution, the target augmented reality glasses are used to collect the activity video of the target goldfish, which provides real-time goldfish activity data, and the growth period of the goldfish (fry period, juvenile period, adult period) is determined based on the video recognition technology, because the nutritional requirements of goldfish in different growth periods are different; then the behavioral characteristics and body characteristics of the goldfish are extracted from the first video, and these characteristics can more directly reflect the health status and nutritional status of the goldfish; the extracted behavioral characteristics and body characteristics are input into the preset model for processing to obtain a first judgment result, if the first judgment result is an abnormal state, the first feeding amount is determined according to the target period, when the historical feeding amount is the same as the first feeding amount, the target time difference is calculated to evaluate whether it is necessary to feed again, and the target time difference is compared with the preset first time threshold, it can be accurately determined whether the target goldfish is in a hungry state, when it is confirmed that the target goldfish is in a hungry state, a feeding prompt message is generated and sent to the user through the target augmented reality glasses, which can more accurately reflect the actual nutritional needs and satiety of the goldfish, thereby avoiding the problem of insufficient or excessive feeding that may be caused by the traditional time-based evaluation method, which not only improves the accuracy of feeding, but also helps to maintain the growth and development and health status of the goldfish.

[0008] Optionally, after the target time difference is greater than a preset first time threshold, the method also includes: obtaining water quality data corresponding to the target area, the target area being the area of ​​the water quality environment where the target goldfish is located; obtaining water clarity and water temperature values ​​from the water quality data; determining whether the water clarity is equal to a preset water clarity, and whether the water temperature value is equal to a preset water temperature threshold; when the water clarity is equal to the preset water clarity, and the water temperature value is equal to the preset water temperature threshold, confirming that the target area is in a normal water quality stage to determine that the target goldfish is in a hungry state.

[0009] By adopting the above technical solution, water clarity and water temperature data are obtained from water quality data. Water clarity and water temperature data can more comprehensively evaluate the environmental conditions of goldfish, thereby more accurately judging whether the goldfish is in a hungry state. It can first confirm whether the water quality is normal, avoid misjudgment caused by water quality problems, improve the reliability of judgment, and provide users with a better breeding experience.

[0010] Optionally, after determining whether the water clarity is equal to the preset water clarity and whether the water temperature value is equal to the preset water temperature threshold, the method also includes: when the water clarity is not equal to the preset water clarity and the water temperature value is not equal to the preset water temperature threshold, confirming that the target area is in the water quality abnormality stage; determining the preset second time threshold according to the water quality abnormality stage; determining whether the target time difference is greater than the preset second time threshold; when the target time difference is less than or equal to the preset second time threshold, confirming that the target goldfish is in a first non-hungry state, generating half-feeding prompt information according to the first non-hungry state, and sending the half-feeding prompt information to the target augmented reality glasses so that the user can view the half-feeding prompt information according to the target augmented reality glasses, the half-feeding prompt information indicating that a target amount of feed is fed to the target goldfish, and the target amount is half of the amount corresponding to the historical feeding amount.

[0011] By adopting the above technical solution, when the water clarity or water temperature values ​​do not meet the preset conditions, the abnormal water quality stage can be quickly identified, thereby reminding the breeder to take timely measures to improve the water quality; in the abnormal water quality stage, the target goldfish may reduce its appetite due to stress response or physiological discomfort, confirming that the target goldfish is in the first non-hungry state, and generating half-feeding prompt information, effectively reducing the risk of overfeeding due to water quality problems.

[0012] Optionally, feeding prompt information is generated according to the hunger state, specifically including: obtaining a target number, the target number being the total number of goldfish in the target area; determining a second feeding amount according to the target number; integrating the second time and the second feeding amount to obtain feeding prompt information, the second time being the time corresponding to when it is confirmed that the target goldfish is in a hungry state.

[0013] By adopting the above technical solution, the total number of goldfish in the target area, that is, the target number, can be obtained, and the second feeding amount required for each goldfish can be determined based on the target number. This personalized feeding strategy helps to ensure that each goldfish can obtain appropriate nutritional intake and avoid health problems caused by insufficient or overfeeding. Accurate feeding amount calculation helps to reduce feed waste and improve feed utilization.

[0014] Optionally, after obtaining the target number, the method also includes: determining whether the target number is greater than a preset number, the preset number being the number of goldfish that can be normally raised in the target area; when the target number is greater than the preset number, confirming that the target area is in an abnormal raising state, generating raising information based on the abnormal raising state, and sending the raising information to the target augmented reality glasses, and the user views the raising information based on the target augmented reality glasses.

[0015] By adopting the above technical solution, the total number of goldfish in the target area, that is, the target number, is compared with the preset number. When the target number is greater than the preset number, it is confirmed that the target area is in an abnormal breeding state, and the problem of excessive breeding density can be discovered in time to prevent the occurrence of abnormal breeding conditions.

[0016] Optionally, before the behavioral characteristics and body characteristics are input into the preset model for processing and the first judgment result is obtained, a preset model needs to be constructed, specifically including: obtaining historical body characteristic data and historical behavioral characteristic data of the target goldfish, the historical body characteristic data including body size data, weight data, fin status data and color data, and the historical behavioral characteristic data including swimming speed data, foraging behavior data and spitting frequency data; screening the historical body characteristic data and historical behavioral characteristic data to obtain historical characteristics; obtaining a second judgment result by inputting the historical characteristics into the preset model for training, and storing the corresponding relationship between the second judgment result and the historical characteristics in the preset model.

[0017] By adopting the above technical solution, the specific physical characteristics (such as body size, weight, fin status, color) and behavioral characteristics (such as swimming speed, foraging behavior, and spitting frequency) of the target goldfish are collected, and the screened historical characteristics are input into the preset model for training. The judgment ability and accuracy of the model can be continuously optimized, and the correspondence between the training results and the historical characteristics is stored in the preset model. Subsequently, the different health states of the goldfish can be more accurately identified according to the model.

[0018] Optionally, after determining whether the target time difference is greater than a preset first time threshold, the method further includes: when the target time difference is less than or equal to the preset first time threshold, confirming that the target goldfish is in a second non-hunger state, the second non-hunger state indicating that the target goldfish is in a full stomach stage.

[0019] By adopting the above technical solution, the target time difference is compared with the preset first time threshold. When the target time difference is less than or equal to the preset first time threshold, it is confirmed that the target goldfish is in a full state, and the breeder can adjust the feeding strategy according to this information; based on automatic monitoring and judgment of the goldfish's full state, personalized feeding suggestions can be provided to the breeder, thereby achieving more refined and intelligent feeding management.

[0020] In a second aspect of the present application, a visual processing device based on augmented reality glasses is provided, the device is a server, the server includes an acquisition unit, a processing unit and a confirmation unit; the acquisition unit acquires a first video corresponding to a target goldfish, the first video is a video of the target goldfish moving in water captured using the target augmented reality glasses, the target goldfish is any goldfish to be monitored; the processing unit identifies the first video and obtains a target period, the target period is the current growth period of the target goldfish, the growth period includes the fry period, the young fish period and the adult fish period; the first video is extracted to obtain behavioral characteristics and body characteristics; the behavioral characteristics and body characteristics are input into a preset model for processing to obtain a first judgment result; if the first judgment result If the result is abnormal, the historical feeding time and historical feeding amount of the target goldfish are obtained; the first feeding amount is determined according to the target period, and when the historical feeding amount is the same as the first feeding amount, the target time difference is confirmed to be obtained, and the target time difference is the difference between the historical feeding time and the first time, and the first time is the time corresponding to the first video; a preset first time threshold is determined according to the first feeding amount, and it is judged whether the target time difference is greater than the preset first time threshold; a confirmation unit confirms that the target goldfish is in a hungry state when the target time difference is greater than the preset first time threshold, and generates feeding prompt information according to the hungry state, and sends the feeding prompt information to the target augmented reality glasses so that the user can view the feeding prompt information according to the target augmented reality glasses.

[0021] Optionally, the acquisition unit is used to obtain water quality data corresponding to the target area, the target area is the area of ​​the water quality environment where the target goldfish is located; water clarity and water temperature values ​​are obtained from the water quality data; the processing unit is used to determine whether the water clarity is equal to the preset water clarity, and whether the water temperature value is equal to the preset water temperature threshold; the confirmation unit is used to confirm that the target area is in a normal water quality stage when the water clarity is equal to the preset water clarity and the water temperature value is equal to the preset water temperature threshold, so as to determine that the target goldfish is in a hungry state.

[0022] Optionally, the confirmation unit is used to confirm that the target area is in the abnormal water quality stage when the water clarity is not equal to the preset water clarity and the water temperature value is not equal to the preset water temperature threshold; the processing unit is used to determine the preset second time threshold according to the abnormal water quality stage; and judge whether the target time difference is greater than the preset second time threshold; the confirmation unit is used to confirm that the target goldfish is in a first non-hungry state when the target time difference is less than or equal to the preset second time threshold, generate half-feeding prompt information according to the first non-hungry state, and send the half-feeding prompt information to the target augmented reality glasses so that the user can view the half-feeding prompt information according to the target augmented reality glasses. The half-feeding prompt information indicates that a target amount of feed is fed to the target goldfish, and the target amount is half of the historical feeding amount.

[0023] Optionally, the acquisition unit is used to obtain a target number, which is the total number of goldfish in the target area; the processing unit is used to determine a second feeding amount based on the target number; the second time and the second feeding amount are integrated to obtain feeding prompt information, and the second time is the time corresponding to when it is confirmed that the target goldfish is in a hungry state.

[0024] Optionally, the processing unit is used to determine whether the target number is greater than a preset number, the preset number being the number of goldfish that can be normally raised in the target area; the confirmation unit is used to confirm that the target area is in an abnormal breeding state when the target number is greater than the preset number, generate breeding information based on the abnormal breeding state, and send the breeding information to the target augmented reality glasses, and the user views the breeding information based on the target augmented reality glasses.

[0025] Optionally, the acquisition unit is used to obtain historical body characteristic data and historical behavior characteristic data of the target goldfish, the historical body characteristic data including body size data, weight data, fin status data and color data, and the historical behavior characteristic data including swimming speed data, foraging behavior data and spitting frequency data; the processing unit is used to screen the historical body characteristic data and the historical behavior characteristic data to obtain historical characteristics; the second judgment result is obtained by inputting the historical characteristics into a preset model for training, and the corresponding relationship between the second judgment result and the historical characteristics is stored in the preset model.

[0026] Optionally, the confirmation unit is used to confirm that the target goldfish is in a second non-hunger state when the target time difference is less than or equal to a preset first time threshold, and the second non-hunger state indicates that the target goldfish is in a full stomach stage.

[0027] In a third aspect of the present application, an electronic device is provided, which includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory, so that an electronic device executes any one of the methods described above in the present application.

[0028] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, any one of the above methods of the present application is executed.

[0029] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Use the target augmented reality glasses to collect the activity video of the target goldfish, which provides real-time goldfish activity data. The growth period of the goldfish (fry period, juvenile period, adult period) is determined based on video recognition technology, because the nutritional requirements of goldfish in different growth periods are different; then extract the behavioral characteristics and body characteristics of the goldfish from the first video, which can more directly reflect the health status and nutritional status of the goldfish; input the extracted behavioral characteristics and body characteristics into the preset model for processing to obtain the first judgment result. If the first judgment result is an abnormal state, determine the first feeding amount according to the target period. When the historical feeding amount is the same as the first feeding amount, calculate the target time difference to evaluate whether it is necessary to feed again. Compare the target time difference with the preset first time threshold to accurately determine whether the target goldfish is in a hungry state. When it is confirmed that the target goldfish is in a hungry state, generate a feeding prompt message and send it to the user through the target augmented reality glasses, which can more accurately reflect the actual nutritional needs and satiety of the goldfish, thereby avoiding the problem of insufficient or excessive feeding that may be caused by the traditional time-based evaluation method, which not only improves the accuracy of feeding, but also helps to maintain the growth and development and health status of the goldfish.

[0030] 2. Obtain water clarity and water temperature data from water quality data. Water clarity and water temperature data can more comprehensively evaluate the environmental conditions of goldfish, so as to more accurately determine whether the goldfish is hungry. You can first confirm whether the water quality is normal to avoid misjudgment caused by water quality problems, improve the reliability of judgment, and provide users with a better breeding experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a flowchart of a visual processing method based on augmented reality glasses provided in an embodiment of the present application; Figure 2 is a structural schematic diagram of a visual processing device based on augmented reality glasses provided in an embodiment of the present application; Figure 3 It is a structural schematic diagram of an electronic device disclosed in an embodiment of the present application.

[0032] Explanation of reference numerals: 201, acquisition unit; 202, processing unit; 203, confirmation unit; 300, electronic device; 301, processor; 302, memory; 303, user interface; 304, network interface; 305, communication bus. DETAILED DESCRIPTION

[0033] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0034] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0035] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0036] Monitoring the hunger status of goldfish is a key link to ensure their healthy growth and maintain the ecological balance in the aquarium. As an aquatic vertebrate, the growth rate, behavioral habits and physiological function of goldfish are closely related to their feeding behavior. Long-term hunger will significantly inhibit the growth of goldfish, weaken their immune system function, and lead to a series of adverse physical signs such as emaciation, weak fins, and dull body color. In extreme cases, hunger may also induce a variety of diseases, seriously reducing the survival probability and quality of life of goldfish.

[0037] Therefore, accurately assessing the hunger state of goldfish and adjusting feeding strategies accordingly are crucial to ensure the health of goldfish. However, in current goldfish breeding practices, the assessment of goldfish hunger state mainly relies on a rough estimate of feeding time, which is used as a reference for arranging subsequent feeding. However, this time-based assessment method cannot accurately reflect the actual nutritional needs and satiety of goldfish, resulting in insufficient or excessive feeding, which in turn has an adverse effect on the growth, development and health of goldfish.

[0038] Therefore, how to solve the problem of insufficient or excessive feeding caused by traditional time-based evaluation methods. The embodiment of the present application provides a visual processing method based on augmented reality glasses, which is applied to a server. The server of the present application can provide a platform for hunger monitoring services for goldfish breeding. Figure 1 is a flowchart of a visual processing method based on augmented reality glasses provided in an embodiment of the present application, with reference to Figure 1 The method includes the following steps S101-S108.

[0039] S101: Obtain a first video corresponding to a target goldfish, where the first video is a video of the target goldfish moving in water captured using target augmented reality glasses.

[0040] In the above S101, the target goldfish is any goldfish to be monitored in the target area. First, make sure that the user has correctly worn and turned on the target augmented reality glasses (AR glasses), and the camera function of the target augmented glasses is activated. The target user refers to the person who raises goldfish. Use the camera function of the AR glasses to record the video of the target area where the target goldfish is located. Make sure that the video is clear and can fully capture the activities of the goldfish. At this time, the target area refers to the aquarium or pond. After the AR glasses complete the video recording of the goldfish's activities, the first video is transmitted to the server through the network so that the server can obtain the first video sent by the target augmented reality glasses.

[0041] S102: Identify the first video to obtain a target period, where the target period is the current growth period of the target goldfish, and the growth period includes a fry period, a young fish period, and an adult fish period.

[0042] In the above S102, when obtaining the first video, the goldfish image in the first video is preprocessed using image recognition technology, including denoising, contrast enhancement, etc. The key features of the goldfish are extracted, such as body size, scale color, fin shape, etc. The extracted features are input into a pre-trained machine learning model, and the growth model determines the growth period (fry, young fish, adult fish) of the goldfish based on the features. The fry period refers to the period when the small fish can swim and forage on their own, and the body length gradually grows to about 3 cm, and the breed characteristics begin to appear. The young fish period refers to the goldfish with a body length of more than 3 cm and a growth of more than 2 months. At this stage, the body development of the goldfish is basically formed, the characteristics of each fin are obvious, the body color is gradually bright, but the gonads are not yet mature. The adult fish period refers to the period when the young fish undergoes further growth and development, the gonads are fully mature, and enters the adult fish period. At this time, the goldfish will have obvious secondary sexual characteristics during the breeding season.

[0043] S103: Extract the first video to obtain behavioral features and body features.

[0044] In the above S103, after determining the target period of the target goldfish, the first video is extracted, and the behavior pattern of the goldfish, such as swimming speed, swimming trajectory, whether it jumps frequently, whether it forages for food, etc., is identified by analyzing the first video. The first video is further analyzed to measure the body length, body width, tail fin length and other body parameters of the goldfish. The behavior pattern and body parameters are then screened to screen out the features related to the hunger state, thereby obtaining the behavior features and body features.

[0045] S104: Inputting the behavior characteristics and body shape characteristics into a preset model for processing to obtain a first judgment result.

[0046] In the above S104, before the behavioral characteristics and body characteristics are input into the preset model for processing and the first judgment result is obtained, a preset model needs to be constructed, specifically including: obtaining the historical body characteristic data and historical behavioral characteristic data of the target goldfish, the historical body characteristic data including body size data, weight data, fin status data and color data, and the historical behavioral characteristic data including swimming speed data, foraging behavior data and spitting frequency data; screening the historical body characteristic data and historical behavioral characteristic data to obtain historical characteristics; obtaining the second judgment result by inputting the historical characteristics into the preset model for training, and storing the corresponding relationship between the second judgment result and the historical characteristics in the preset model.

[0047] Specifically, a large amount of physical characteristic data and behavioral characteristic data of goldfish under different hunger states are collected. The physical characteristic data include body size data, weight data, fin status data and color data. Accurate measuring tools (such as vernier calipers) can be used to measure various parts of the goldfish's body, including body length (the longest distance from the tip of the mouth to the tail fin), body height (the vertical distance from the highest point of the goldfish's body to the abdomen), body width (measurement of the widest part of the fish body), etc. The weight of the goldfish is measured using accurate measuring tools such as electronic scales. The shape, size, color and whether there is damage or deformation of the dorsal fin, tail fin and other fins of the goldfish are observed and recorded. The color of various parts of the goldfish's body is recorded, including body color, fin color and whether there are spots or stripes. Then the behavioral characteristic data are obtained, which include swimming speed data, foraging behavior data and spitting frequency data. The swimming distance or speed of the goldfish within a certain period of time is recorded by video recording. Observe and record the behavioral characteristics of the goldfish when foraging, such as foraging frequency, foraging time, foraging method, etc. The frequency of goldfish spitting out water (i.e., the goldfish expelling water through the rapid opening and closing of its mouth) is also recorded, which helps to assess the health and activity of the goldfish. Check and remove outliers, duplicate values, or invalid data to ensure the accuracy and consistency of the data. According to the needs and goals of the preset model, filter out key features related to the health, growth, or behavior of the target goldfish from the historical body feature data and historical behavioral feature data. According to actual needs, select a suitable preset model, such as a machine learning model (such as a decision tree, support vector machine, neural network, etc.) or a deep learning model (such as a convolutional neural network, recurrent neural network, etc.). Preprocess the historical features, such as standardization, normalization, or encoding, to ensure that the data meets the input requirements of the preset model. Input the preprocessed historical features into the preset model for training. During the training process, use the data of goldfish with known hunger status to train the model. Take the extracted features as input to predict the hunger status of the goldfish, and the preset model will learn the mapping relationship between the historical features and the second judgment result. The preset model stores multiple corresponding relationships, one of which represents a hunger state of the goldfish. It can also be classified and constructed based on the different growth stages of the goldfish, that is, goldfish in different growth stages correspond to different behavioral characteristics and body characteristics, so as to better analyze the hunger state of each goldfish in the future. Through model training, the second judgment result of the hunger state of the target goldfish is obtained. These results can be healthy state, abnormal state, active state, etc. The trained preset model is applied to the new goldfish data to predict its hunger state.It is also possible to store historical behavioral characteristics and historical body characteristics of goldfish in different hunger states, then obtain the behavioral characteristics and body characteristics of the target goldfish, calculate the first similarity between the behavioral characteristics and multiple historical behavioral characteristics in turn, and then calculate the second similarity between the body characteristics and the historical body characteristics in turn, and judge whether the first similarity and the second similarity exceed a preset threshold. If there is a situation where the preset threshold is exceeded, the hunger state corresponding to the preset threshold is obtained, and the hunger state is output as the judgment result.

[0048] After the preset model is constructed, the preset model can judge the health status or whether the behavior is abnormal based on the behavior and body characteristics of the goldfish. The extracted behavior characteristics and body characteristics are input into the model. The model outputs a first judgment result based on the input characteristics. The first judgment result includes normal or abnormal. Normal means that the target goldfish is currently in a full state and healthy. Abnormal means that the target goldfish is not in a full state.

[0049] S105: If the first judgment result is an abnormal result, the historical feeding time and historical feeding amount of the target goldfish are obtained.

[0050] In the above S105, when it is determined that the first judgment result is an abnormal result, the historical feeding records of the target goldfish are queried from the goldfish management system, including the time and amount of each feeding. Each time the goldfish is fed, the feeding time and amount need to be recorded for subsequent review.

[0051] S106: Determine a first feeding amount according to the target period, and when the historical feeding amount is the same as the first feeding amount, confirm to obtain a target time difference, where the target time difference is the difference between the historical feeding time and the first time.

[0052] In the above S106, after determining that the target goldfish is in the target period, the appropriate feeding amount (first feeding amount) for the period is determined by consulting relevant information or consulting experts according to the growth period (target period) of the target goldfish. Then the historical feeding amount is compared with the first feeding amount of the target period. If they are the same, the difference (target time difference) between the historical feeding time and the time corresponding to the acquisition of the first video (first time) is calculated.

[0053] S107: Determine a preset first time threshold according to the first feeding amount, and determine whether the target time difference is greater than the preset first time threshold.

[0054] In the above S107, according to the target period currently in which the target goldfish is, the interval feeding time corresponding to the target period is obtained from the historical feeding database. At this time, the interval feeding time is set when the target goldfish is in good health and the water quality is good. When determining the interval feeding time, the interval feeding time is used as the preset first time threshold. Then the calculated target time difference is compared with the preset first time threshold.

[0055] S108: When the target time difference is greater than the preset first time threshold, it is confirmed that the target goldfish is in a hungry state, feeding prompt information is generated according to the hunger state, and the feeding prompt information is sent to the target augmented reality glasses so that the user can view the feeding prompt information according to the target augmented reality glasses.

[0056] In the above S108, if the target time difference is greater than the preset first time threshold, it is also necessary to judge the water quality of the target goldfish's current area. If the water quality is in a normal state, it can be confirmed that the target goldfish is in a hungry state, which is helpful to timely discover and deal with water quality problems and ensure the monitoring growth of goldfish. Specifically, it includes: obtaining water quality data corresponding to the target area, the target area is the area of ​​the water quality environment where the target goldfish is located; obtaining water clarity and water temperature values ​​from the water quality data; judging whether the water clarity is equal to the preset water clarity, and whether the water temperature value is equal to the preset water temperature threshold; when the water clarity is equal to the preset water clarity, and the water temperature value is equal to the preset water temperature threshold, confirm that the target area is in the normal water quality stage to determine that the target goldfish is in a hungry state. Specifically, first clarify the water quality environment area where the target goldfish is located, which is usually a specific fish tank, aquarium or pond. According to the characteristics of the target area, select appropriate water quality monitoring equipment. These devices can be professional water quality monitors or intelligent devices with integrated water quality monitoring functions, such as intelligent fish tanks. Use monitoring equipment to monitor the water quality of the target area in real time or regularly and collect relevant data. These data should include multiple indicators such as water clarity, water temperature, pH value, dissolved oxygen, ammonia nitrogen content, nitrite content, etc. From the collected water quality data, filter out the data of the two key indicators of water clarity and water temperature. According to the physiological characteristics and living habits of goldfish, set a reasonable preset water clarity and preset water temperature threshold. These preset values ​​are usually determined based on the optimal water quality conditions for goldfish growth. Compare the actual measured water clarity and water temperature values ​​with the preset values. If the actual measured water clarity and water temperature values ​​are both equal to the preset values, the water quality is judged to be in the normal stage; if one or two indicators do not meet the conditions, the water quality is judged to be in the abnormal stage. If both the water clarity and water temperature meet the preset conditions, the target area is confirmed to be in the normal water quality stage. On the basis of confirming that the water quality is normal, and when the target time difference is greater than the preset first time threshold, it can be determined that the target goldfish is in a hungry state.

[0057] In addition, after determining that the target goldfish is in a hungry state, a feeding prompt information is generated according to the hungry state, specifically including: obtaining a target number, which is the total number of goldfish in the target area; determining a second feeding amount according to the target number; integrating the second time and the second feeding amount to obtain feeding prompt information, wherein the second time is the time corresponding to when the target goldfish is confirmed to be in a hungry state. Specifically, firstly, the target area is clarified, that is, the specific environment where the goldfish is located, such as a fish tank, an aquarium, or a pond. An appropriate method is used to count the goldfish in the target area. This can be done by direct observation and manual counting, or by using a professional counting tool (such as a fish counter). If the number of goldfish is large or the distribution is relatively scattered, multiple observations and counting may be required to ensure accuracy. The counting results are recorded as a basis for determining the second feeding amount later. A reasonable feeding standard is formulated based on factors such as the growth stage, body size, activity level, and water quality of the goldfish. This standard usually includes the amount of feed that each goldfish should ingest per day or the amount of feed that should be put in each unit volume of water. The second feeding amount is calculated based on the target number (i.e., the total number of goldfish) and the feeding standard. This usually involves multiplying the feeding amount per goldfish by the total number of goldfish, or multiplying the feeding amount per unit volume of water by the volume of water in the target area. Based on the calculated second feeding amount, make appropriate adjustments according to the actual situation of the goldfish (such as appetite, health, etc.). If multiple goldfish in the target area are in a hungry state, the feeding amount can be appropriately increased; conversely, if multiple goldfish in the target area are in a non-hungry state, the feeding amount should be appropriately reduced. The second time refers to the time corresponding to when the target goldfish is confirmed to be in a hungry state. This time is usually determined by observing the behavioral characteristics of the goldfish (such as foraging behavior, slow swimming, etc.) and body characteristics (such as dull body color, emaciation, etc.), and combined with historical feeding records. The second time and the second feeding amount are integrated to form a complete feeding reminder message. This message should include information such as the total number of goldfish, the time to confirm the hungry state, and the corresponding feeding amount. The integrated information is used to generate feeding reminder information in an appropriate manner (such as text, image or voice, etc.). This information should be clear and easy for users to understand and operate, such as "The goldfish is hungry, you can feed it the second feeding amount as soon as possible." The generated feeding reminder information will then be sent to the target augmented reality glasses via wireless transmission so that the user can view and take action.

[0058] Further, when the water clarity is not equal to the preset water clarity, and the water temperature value is not equal to the preset water temperature threshold, the target area is confirmed to be in the water quality abnormal stage; the preset second time threshold is determined according to the water quality abnormal stage; it is judged whether the target time difference is greater than the preset second time threshold; when the target time difference is less than or equal to the preset second time threshold, it is confirmed that the target goldfish is in the first non-hungry state, and a half-feeding prompt information is generated according to the first non-hungry state, and the half-feeding prompt information is sent to the target augmented reality glasses, so that the user can view the half-feeding prompt information according to the target augmented reality glasses, and the half-feeding prompt information indicates that the target goldfish is fed with a target amount of feed, and the target amount is one-half of the historical feeding amount. Specifically, after obtaining the water quality data of the target area, the water clarity and water temperature values ​​therein are compared with the preset clarity and water temperature thresholds. If the water clarity is not equal to the preset water clarity, and the water temperature value is not equal to the preset water temperature threshold, the target area is confirmed to be in the water quality abnormal stage. Based on the degree of water quality abnormality and the adaptability of goldfish to water quality changes, a reasonable preset second time threshold is set. This time threshold is usually used to determine whether the goldfish needs to adjust its feeding strategy when the water quality is abnormal. If the water quality is more serious, the time threshold may need to be shortened so that countermeasures can be taken more quickly; if the water quality is relatively mild, the time threshold can be appropriately extended. Calculate the difference between the historical feeding time and the first time to obtain the target time difference. Compare the target time difference with the preset second time threshold. If the target time difference is less than or equal to the preset second time threshold, it is confirmed that the target goldfish is in the first non-hunger state. In this state, the goldfish may have a poor appetite due to abnormal water quality, but still need to be fed in moderation to maintain its physical strength. According to the first non-hunger state, a half-feeding prompt message is generated. This message suggests that the user feed the target goldfish a target amount of feed, where the target amount is half of the historical feeding amount. This is to avoid problems such as indigestion or anorexia of goldfish caused by abnormal water quality. The generated half-feeding prompt message is sent to the target augmented reality glasses via wireless transmission. After the user wears the target augmented reality glasses, he can view the received half-feeding prompt message in real time and perform corresponding feeding operations according to the prompt. For example, after determining that the target goldfish is in the first non-hungry state, obtain the historical feeding amount corresponding to the target goldfish. If the historical feeding amount is 10g, the target amount is 5g at this time, and confirm to generate 5g feeding prompt information. At this time, the 5g feeding prompt information indicates half-feeding prompt information.

[0059] At this time, when the target time difference is greater than the preset second time threshold, it is confirmed that the target goldfish is in a hungry state, and feeding prompt information needs to be generated according to the hunger state so that the user can feed the target goldfish in time according to the feeding prompt information.

[0060] Furthermore, when the target time difference is less than or equal to the preset first time threshold, it is confirmed that the target goldfish is in the second non-hunger state, and the second non-hunger state indicates that the target goldfish is in the full stomach stage. Specifically, if the target time difference is less than or equal to the preset first time threshold, it is confirmed that the target goldfish is in the second non-hunger state, i.e., the full stomach stage. This is because during this time period, the goldfish may still be digesting the food fed last time, so the target goldfish currently does not have hunger behavior.

[0061] In a possible implementation, the stocking density of goldfish in the target area is also monitored. When the number of goldfish is too large and exceeds the carrying capacity of the breeding environment, it will pose a potential threat to the health and growth of the goldfish. A prompt message needs to be sent to the user to remind the user to pay attention and take measures, including: judging whether the target number is greater than the preset number, the preset number is the number of goldfish that can be normally raised in the target area; when the target number is greater than the preset number, confirming that the target area is in an abnormal breeding state, generating breeding information according to the abnormal breeding state, and sending the breeding information to the target augmented reality glasses, and the user views the breeding information according to the target augmented reality glasses. Specifically, the total number of goldfish in the target area, that is, the target number, is obtained by observation and counting. This can be done by directly observing the number of goldfish, or by using an intelligent device (such as a camera with image recognition technology) to automatically count. The preset number is the upper limit of the number of goldfish that can be normally raised in the target area. This value is usually determined based on factors such as the size of the target area, water quality conditions, the processing capacity of the filtration system, and the growth needs of goldfish. The preset number should be set according to the actual situation before or during the breeding of goldfish, and recorded in the breeding management system. Compare the target number with the preset number to determine whether the target number exceeds the preset number. If the target number is greater than the preset number, it is confirmed that the target area is in an abnormal feeding state. The abnormal feeding state indicates that the number of goldfish in the target area is too large, which may exceed the carrying capacity of the feeding environment and pose a potential threat to the health and growth of the goldfish. Formulate the content of the feeding information according to the abnormal feeding state. The feeding information should include information such as confirmation of the abnormal feeding state, possible hazards (such as deterioration of water quality, restricted growth of goldfish, etc.), recommended countermeasures (such as reducing the number of goldfish, improving the feeding environment, etc.), and emergency contact information. According to the display capabilities of the target augmented reality glasses and user needs, select the appropriate feeding information format. This can be in the form of text, images, videos or audio so that users can clearly understand and receive the information. Send the generated feeding information to the target augmented reality glasses by wireless transmission. This usually involves using Bluetooth, Wi-Fi or other wireless communication technologies to transmit information from the feeding management system or smart device to the target augmented reality glasses. After the user wears the target augmented reality glasses, he can view the received feeding information in real time. Through the display interface of the glasses, users can clearly see the prompts of abnormal feeding status, recommended countermeasures, emergency contact information, etc. For example, if the target number is 10, the preset number in the target area is set to 8. At this time, the target number is greater than the preset number, and it is confirmed that there are too many goldfish in the target area. Feeding information needs to be sent to the user so that the user can adjust the goldfish feeding density in the target area.

[0062] Further, when the target number is less than or equal to the preset number, it is confirmed that the stocking density of goldfish in the target area is in a normal state and there is no need to adjust the stocking density.

[0063] The embodiment of the present application also provides a visual processing device based on augmented reality glasses, Figure 2 is a schematic diagram of the structure of a visual processing device based on augmented reality glasses provided in an embodiment of the present application, with reference to Figure 2 The device is a server, and the server includes an acquisition unit 201, a processing unit 202 and a confirmation unit 203.

[0064] The acquisition unit 201 acquires a first video corresponding to a target goldfish, where the first video is a video of the target goldfish moving in water captured using target augmented reality glasses, and the target goldfish is any goldfish to be monitored.

[0065] The processing unit 202 identifies the first video and obtains a target period, which is the current growth period of the target goldfish, and the growth period includes a fry period, a young fish period and an adult fish period; extracts the first video to obtain behavioral characteristics and physical characteristics; inputs the behavioral characteristics and physical characteristics into a preset model for processing to obtain a first judgment result; if the first judgment result is an abnormal result, obtains the historical feeding time and the historical feeding amount of the target goldfish; determines the first feeding amount according to the target period, and when the historical feeding amount is the same as the first feeding amount, confirms that a target time difference is obtained, and the target time difference is the difference between the historical feeding time and the first time, and the first time is the time corresponding to the acquisition of the first video; determines a preset first time threshold according to the first feeding amount, and determines whether the target time difference is greater than the preset first time threshold.

[0066] The confirmation unit 203 confirms that the target goldfish is in a hungry state when the target time difference is greater than the preset first time threshold, generates feeding prompt information according to the hunger state, and sends the feeding prompt information to the target augmented reality glasses so that the user can view the feeding prompt information according to the target augmented reality glasses.

[0067] In a possible implementation, the acquisition unit 201 is used to acquire water quality data corresponding to a target area, where the target area is the area of ​​the water quality environment where the target goldfish is located; water clarity and water temperature values ​​are acquired from the water quality data; the processing unit 202 is used to determine whether the water clarity is equal to a preset water clarity, and whether the water temperature value is equal to a preset water temperature threshold; the confirmation unit 203 is used to confirm that the target area is in a normal water quality stage when the water clarity is equal to the preset water clarity, and the water temperature value is equal to the preset water temperature threshold, so as to determine that the target goldfish is in a hungry state.

[0068] In a possible implementation, the confirmation unit 203 is used to confirm that the target area is in the water quality abnormality stage when the water clarity is not equal to the preset water clarity and the water temperature value is not equal to the preset water temperature threshold; the processing unit 202 is used to determine the preset second time threshold according to the water quality abnormality stage; and judge whether the target time difference is greater than the preset second time threshold; the confirmation unit 203 is used to confirm that the target goldfish is in a first non-hungry state when the target time difference is less than or equal to the preset second time threshold, generate half-feeding prompt information according to the first non-hungry state, and send the half-feeding prompt information to the target augmented reality glasses so that the user can view the half-feeding prompt information according to the target augmented reality glasses. The half-feeding prompt information indicates that a target amount of feed is fed to the target goldfish, and the target amount is half of the historical feeding amount.

[0069] In a possible implementation, the acquisition unit 201 is used to obtain a target number, which is the total number of goldfish in the target area; the processing unit 202 is used to determine a second feeding amount based on the target number; the second time and the second feeding amount are integrated to obtain feeding prompt information, and the second time is the time corresponding to when it is confirmed that the target goldfish is in a hungry state.

[0070] In one possible implementation, the processing unit 202 is used to determine whether the target number is greater than a preset number, where the preset number is the number of goldfish that can be normally raised in the target area; the confirmation unit 203 is used to confirm that the target area is in an abnormal breeding state when the target number is greater than the preset number, generate breeding information based on the abnormal breeding state, and send the breeding information to the target augmented reality glasses, and the user views the breeding information based on the target augmented reality glasses.

[0071] In a possible implementation, the acquisition unit 201 is used to acquire historical physical characteristic data and historical behavioral characteristic data of the target goldfish, the historical physical characteristic data including body size data, weight data, fin status data and color data, and the historical behavioral characteristic data including swimming speed data, foraging behavior data and spitting frequency data; the processing unit 202 is used to screen the historical physical characteristic data and the historical behavioral characteristic data to obtain historical characteristics; the second judgment result is obtained by inputting the historical characteristics into a preset model for training, and the corresponding relationship between the second judgment result and the historical characteristics is stored in the preset model.

[0072] In a possible implementation, the confirmation unit 203 is used to confirm that the target goldfish is in a second non-hunger state when the target time difference is less than or equal to a preset first time threshold, and the second non-hunger state indicates that the target goldfish is in a full stomach stage.

[0073] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0074] The present application also discloses an electronic device. Figure 3 , Figure 3 The electronic device 300 may include: at least one processor 301 , at least one network interface 304 , a user interface 303 , a memory 302 , and at least one communication bus 305 .

[0075] The communication bus 305 is used to realize the connection and communication between these components.

[0076] The user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0077] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0078] Among them, the processor 301 may include one or more processing cores. The processor 301 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 302, and calling data stored in the memory 302. Optionally, the processor 301 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 301 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application requests; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 301, and it can be implemented separately through a chip.

[0079] Among them, the memory 302 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 302 includes a non-transitory computer-readable storage medium. The memory 302 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 302 may include a program storage area and a data storage area, wherein the program storage area. Instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc. can be stored; the data storage area can store data involved in the above-mentioned various method embodiments, etc. The memory 302 can also be optionally at least one storage device located away from the aforementioned processor 301.

[0080] like Figure 3 As shown, the memory 302 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program based on visual processing of augmented reality glasses.

[0081] exist Figure 3In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 301 can be used to call the application program based on visual processing of augmented reality glasses stored in the memory 302. When executed by one or more processors, the electronic device executes one or more methods described in the above embodiments.

[0082] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0083] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0084] In the several embodiments provided in the present application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0085] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0086] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0087] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0088] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, it will be easy for those skilled in the art to think of other embodiments of the present disclosure. This application is intended to cover any variation, use or adaptive change of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field that are not recorded in the present disclosure.

Claims

1. A visual processing method based on augmented reality glasses, characterized in that: Applied in a server, the method comprises: Obtaining a first video corresponding to a target goldfish, wherein the first video is a video of the target goldfish moving in water captured using target augmented reality glasses, and the target goldfish is any goldfish to be monitored; Identify the first video to obtain a target period, where the target period is the current growth period of the target goldfish, and the growth period includes a fry period, a young fish period, and an adult fish period; Extracting the first video to obtain behavioral features and body features; Inputting the behavior characteristics and the body characteristics into a preset model for processing to obtain a first judgment result; If the first judgment result is an abnormal result, obtaining the historical feeding time and historical feeding amount of the target goldfish; Determine a first feeding amount according to the target period, and when the historical feeding amount is the same as the first feeding amount, confirm to obtain a target time difference, where the target time difference is the difference between the historical feeding time and a first time, where the first time is the time corresponding to obtaining the first video; Determine a preset first time threshold according to the first feeding amount, and judge whether the target time difference is greater than the preset first time threshold; When the target time difference is greater than the preset first time threshold, it is confirmed that the target goldfish is in a hungry state, feeding prompt information is generated according to the hunger state, and the feeding prompt information is sent to the target augmented reality glasses so that the user can view the feeding prompt information according to the target augmented reality glasses.

2. The method according to claim 1, characterized in that After the target time difference is greater than the preset first time threshold, the method further includes: Acquire water quality data corresponding to a target area, wherein the target area is an area of ​​the water quality environment where the target goldfish is located; Obtaining water clarity and water temperature values ​​from the water quality data; Determine whether the water clarity is equal to a preset water clarity, and whether the water temperature value is equal to a preset water temperature threshold; When the water clarity is equal to the preset water clarity, and the water temperature value is equal to the preset water temperature threshold, the target area is confirmed to be in the normal water quality stage to determine that the target goldfish is in the hungry state.

3. The method according to claim 2, characterized in that After determining whether the water clarity is equal to a preset water clarity and whether the water temperature value is equal to a preset water temperature threshold, the method further includes: When the water clarity is not equal to the preset water clarity, and the water temperature value is not equal to the preset water temperature threshold, it is confirmed that the target area is in the water quality abnormal stage; Determining a preset second time threshold according to the abnormal water quality stage; Determine whether the target time difference is greater than the preset second time threshold; When the target time difference is less than or equal to the preset second time threshold, it is confirmed that the target goldfish is in a first non-hunger state, half-feeding prompt information is generated according to the first non-hunger state, and the half-feeding prompt information is sent to the target augmented reality glasses so that the user can view the half-feeding prompt information according to the target augmented reality glasses. The half-feeding prompt information indicates that a target amount of feed is fed to the target goldfish, and the target amount is half of the historical feeding amount.

4. The method according to claim 2, characterized in that: The step of generating feeding prompt information according to the hunger state specifically includes: Obtaining a target number, where the target number is the total number of goldfish in the target area; determining a second feeding amount according to the target amount; The second time and the second feeding amount are integrated to obtain the feeding prompt information, wherein the second time is the time corresponding to when it is confirmed that the target goldfish is in the hungry state.

5. The method according to claim 4, characterized in that After obtaining the target quantity, the method further includes: Determining whether the target number is greater than a preset number, where the preset number is the number of goldfish that can normally be raised in the target area; When the target number is greater than the preset number, it is confirmed that the target area is in an abnormal feeding state, feeding information is generated according to the abnormal feeding state, and the feeding information is sent to the target augmented reality glasses, and the user views the feeding information according to the target augmented reality glasses.

6. The method according to claim 1, characterized in that Before the behavior characteristics and the body characteristics are input into the preset model for processing to obtain the first judgment result, the preset model needs to be constructed, which specifically includes: Acquire historical body characteristic data and historical behavior characteristic data of the target goldfish, wherein the historical body characteristic data includes body size data, weight data, fin status data and color data, and the historical behavior characteristic data includes swimming speed data, foraging behavior data and spitting frequency data; Screening the historical body feature data and the historical behavior feature data to obtain historical features; The second judgment result is obtained by inputting the historical features into the preset model for training, and the corresponding relationship between the second judgment result and the historical features is stored in the preset model.

7. The method according to claim 1, characterized in that After determining whether the target time difference is greater than the preset first time threshold, the method further includes: When the target time difference is less than or equal to the preset first time threshold, it is confirmed that the target goldfish is in a second non-hunger state, and the second non-hunger state indicates that the target goldfish is in a full stomach stage.

8. A visual processing device based on augmented reality glasses, characterized in that: The device is a server, and the server comprises an acquisition unit (201), a processing unit (202) and a confirmation unit (203); The acquisition unit (201) acquires a first video corresponding to a target goldfish, wherein the first video is a video of the target goldfish moving in water captured using target augmented reality glasses, and the target goldfish is any goldfish to be monitored; The processing unit (202) identifies the first video to obtain a target period, wherein the target period is the current growth period of the target goldfish, and the growth period includes a fry period, a young fish period, and an adult fish period; extracts the first video to obtain behavioral characteristics and body shape characteristics; The behavior characteristics and the body characteristics are input into a preset model for processing to obtain a first judgment result; if the first judgment result is an abnormal result, the historical feeding time and the historical feeding amount of the target goldfish are obtained; the first feeding amount is determined according to the target period, and when the historical feeding amount is the same as the first feeding amount, it is confirmed to obtain a target time difference, and the target time difference is the difference between the historical feeding time and the first time, and the first time is the time corresponding to the acquisition of the first video; Determine a preset first time threshold according to the first feeding amount, and judge whether the target time difference is greater than the preset first time threshold; The confirmation unit (203) confirms that the target goldfish is in a hungry state when the target time difference is greater than the preset first time threshold, generates feeding prompt information according to the hunger state, and sends the feeding prompt information to the target augmented reality glasses so that the user can view the feeding prompt information according to the target augmented reality glasses.

9. An electronic device, characterized in that: The electronic device (300) comprises a processor (301), a memory (302), a user interface (303) and a network interface (304), wherein the memory (302) is used to store instructions, the user interface (303) and the network interface (304) are used to communicate with other devices, and the processor (301) is used to execute the instructions stored in the memory (302) so that the electronic device (300) executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is executed.

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