Air conditioner interaction verification method and device, verification equipment and storage medium

Abstract

The invention discloses an air conditioner interaction verification method and device, verification equipment and a medium. The method comprises the steps that an execution requirement and an image collection rule corresponding to a to-be-verified interaction mode are determined; sending a control instruction to the air conditioner according to the execution demand, and acquiring an execution state image of an air conditioner panel according to an image acquisition rule; the panel material of the air conditioner panel is recognized according to the execution state image, anti-interference processing is conducted on the execution state image according to the panel material, and a target image is obtained; determining a detection strategy according to an interaction mode and a panel material, and detecting the target image according to the detection strategy to obtain an actual execution state of the air conditioner; and verifying whether the actual execution state is consistent with the execution demand, and outputting a verification report. According to the method, the material of the air conditioner panel is identified firstly, and then the specific interference of different materials is inhibited by combining the targeted interference resistance of the interaction mode, so that the detection precision of the air conditioner interaction state under the conditions of multiple interaction scenes and multiple material panels can be improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of air conditioners, and particularly relates to an air conditioner interaction verification method and device, a verification equipment and a storage medium. BACKGROUND

[0002] In an air conditioner laboratory or production line, it is often necessary to detect or sample check air conditioner interaction functions, that is, to verify air conditioner interaction functions. In the field of air conditioner interaction verification, existing technologies mostly rely on general solutions and lack customized designs for air conditioner product characteristics. Standardized methods such as gamma correction and Gaussian filtering are used for general image preprocessing, without considering the optical property differences of different material panels such as frosted and anti-glare panels. Under complex lighting, they are easily disturbed by reflections, oil stains and textures, resulting in image feature loss or misjudgment.

[0003] For target detection, general models such as YOLO and SSD use fixed-size anchor boxes, which have poor adaptability to small targets such as air conditioner temperature decimal places (5x8 pixels) and micro icons (8x8 pixels), and have high missing detection rates and large temperature recognition errors.

[0004] In multi-interaction verification, voice, APP and remote control interaction methods are detected independently, which cannot adapt to the visual performance differences of the same interaction on different material panels, resulting in large fluctuations in detection accuracy in multiple scenarios. At the same time, when general models are directly deployed on edge devices, only resolution reduction or pruning is used to achieve real-time performance, without customized acceleration combined with air conditioner panel recognition tasks, which cannot meet the efficient needs of batch air conditioner interaction verification. SUMMARY

[0005] Therefore, the embodiments of the present application provide an air conditioner interaction verification method, device, verification equipment and storage medium, which can improve the detection accuracy of air conditioner interaction states in multiple interaction scenarios and multiple material panels.

[0006] The first aspect of the present application provides an air conditioner interaction verification method, comprising: determining an execution requirement and an image acquisition rule corresponding to a to-be-verified interaction method; sending a control instruction to an air conditioner according to the execution requirement and acquiring an execution state image of an air conditioner panel according to the image acquisition rule; identifying a panel material of the air conditioner panel according to the execution state image, performing anti-interference processing on the execution state image according to the panel material, and obtaining a target image; determining a detection strategy according to the interaction method and the panel material, detecting the target image according to the detection strategy, and obtaining an actual execution state of the air conditioner; verifying whether the actual execution state is consistent with the execution requirement, and outputting a verification report.

[0007] In one possible implementation, the step of identifying the panel material of the air conditioner panel based on the execution state image includes: Extract the index features of the air conditioning panel area in the execution state image, wherein the index features include at least one of texture entropy, polarization degree and texture frequency; The panel material of the air conditioner panel is identified based on the aforementioned indicator characteristics.

[0008] In one possible implementation, the anti-interference processing of the execution state image based on the panel material includes: Based on the preset correspondence between panel materials and anti-interference processing methods, the anti-interference processing method corresponding to the panel material is determined. The aforementioned anti-interference processing method is used to perform anti-interference processing on the execution state image.

[0009] In one possible implementation, the correspondence between the preset panel material and the anti-interference processing method includes: The anti-interference treatment method for the frosted panel is dynamic polarization filtering; The anti-glare panel uses a multi-scale exposure fusion combined with backlight compensation as its anti-interference processing method. The anti-interference processing method corresponding to the fingerprint-resistant panel is a combination of oil stain masking and Gaussian filtering; The anti-interference processing method for the brushed metal panel is Gaussian difference texture filtering combined with highlight suppression.

[0010] In one possible implementation, the detection strategy includes: The system invokes the dedicated anchor frame library corresponding to the interaction method and the panel material. The dedicated anchor frame library is a collection of anchor frames customized for small-sized targets on panels of different materials. The small-sized target refers to a target smaller than a preset size.

[0011] In one possible implementation, the image acquisition rules include at least one of acquisition distance, acquisition angle, and acquisition timing.

[0012] In one possible implementation, the method further includes: Record the first moment when the control command is sent; Record the second moment when the actual operating state of the air conditioner is obtained; The time difference between the first moment and the second moment is taken as the end-to-end latency, and the end-to-end latency is recorded in the verification report.

[0013] A second aspect of this application provides an air conditioner interactive verification device, comprising: The determination module is used to determine the execution requirements and image acquisition rules corresponding to the interaction method to be verified; The acquisition module is used to send control commands to the air conditioner according to the execution requirements and to acquire execution status images of the air conditioner panel according to the image acquisition rules. The recognition module is used to identify the panel material of the air conditioner panel based on the execution state image, and to perform anti-interference processing on the execution state image based on the panel material to obtain the target image; The detection module is used to determine a detection strategy based on the interaction method and the panel material, and to detect the target image according to the detection strategy to obtain the actual execution state of the air conditioner. The verification module is used to verify whether the actual execution status is consistent with the execution requirements and output a verification report.

[0014] In one possible implementation, the identification module is specifically used for: Extract the index features of the air conditioning panel area in the execution state image, wherein the index features include at least one of texture entropy, polarization degree and texture frequency; The panel material of the air conditioner panel is identified based on the aforementioned indicator characteristics.

[0015] In one possible implementation, the identification module is specifically used for: Based on the preset correspondence between panel materials and anti-interference processing methods, the anti-interference processing method corresponding to the panel material is determined. The aforementioned anti-interference processing method is used to perform anti-interference processing on the execution state image.

[0016] In one possible implementation, the correspondence between the preset panel material and the anti-interference processing method includes: The anti-interference treatment method for the frosted panel is dynamic polarization filtering; The anti-glare panel uses a multi-scale exposure fusion combined with backlight compensation as its anti-interference processing method. The anti-interference processing method corresponding to the fingerprint-resistant panel is a combination of oil stain masking and Gaussian filtering; The anti-interference processing method for the brushed metal panel is Gaussian difference texture filtering combined with highlight suppression.

[0017] In one possible implementation, the detection strategy includes: The system invokes the dedicated anchor frame library corresponding to the interaction method and the panel material. The dedicated anchor frame library is a collection of anchor frames customized for small-sized targets on panels of different materials. The small-sized target refers to a target smaller than a preset size.

[0018] In one possible implementation, the image acquisition rules include at least one of acquisition distance, acquisition angle, and acquisition timing.

[0019] In one possible implementation, the verification module is further configured to: Record the first moment when the control command is sent; Record the second moment when the actual operating state of the air conditioner is obtained; The time difference between the first moment and the second moment is taken as the end-to-end latency, and the end-to-end latency is recorded in the verification report.

[0020] A third aspect of this application provides a verification device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the air conditioner interactive verification method provided in the first aspect.

[0021] A computer-readable storage medium according to a fourth aspect of this application stores computer-readable instructions that can be executed by a processor to implement the air conditioning interactive verification method provided in the first aspect.

[0022] The air conditioner interaction verification method, apparatus, verification device, and storage medium provided in this application determine the execution requirements and image acquisition rules corresponding to the interaction method to be verified; send control commands to the air conditioner according to the execution requirements; acquire execution state images of the air conditioner panel according to the image acquisition rules; identify the panel material of the air conditioner panel based on the execution state images; perform anti-interference processing on the execution state images based on the panel material to obtain a target image; determine a detection strategy based on the interaction method and the panel material; detect the target image according to the detection strategy to obtain the actual execution state of the air conditioner; verify whether the actual execution state is consistent with the execution requirements; and output a verification report. Compared with the prior art, this application first identifies the air conditioner panel material and then combines the interaction method with targeted anti-interference, suppressing the interference specific to different materials and improving the feature retention rate, thereby improving the detection accuracy of air conditioner interaction state in multiple interaction scenarios and with multiple panel materials. Attached Figure Description

[0023] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Appendix Figure 1 The laboratory layout diagram for air conditioning interactive verification provided in this application is shown; Appendix Figure 2 A flowchart of an air conditioner interactive verification method provided in this application is shown; Appendix Figure 3A flowchart of the anti-interference processing provided in this application is shown; Appendix Figure 4 The structural diagram of the optimized model for accurate small target detection provided in this application is shown. Appendix Figure 5 A schematic diagram of an air conditioner interactive verification device according to an embodiment of this application is shown.

[0024] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0026] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0027] Furthermore, in this invention, descriptions involving "first," "second," etc., are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0028] In this invention, unless otherwise explicitly specified and limited, the terms "connection," "fixed," etc., should be interpreted broadly. For example, "fixed" can mean a fixed connection, a detachable connection, or an integral part; it can mean a mechanical connection or an electrical connection; it can mean a direct connection or an indirect connection through an intermediate medium; it can mean the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0029] Furthermore, the technical solutions of the various embodiments of the present invention can be combined with each other, but only if they are feasible for those skilled in the art. If the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0030] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, specific embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0031] Currently, air conditioner interaction verification methods based on general image recognition employ a standardized image enhancement algorithm that fails to differentiate between the material types of air conditioner panels (e.g., matte, anti-glare, anti-fingerprint, brushed metal, etc.). Different panel materials exhibit varying degrees of interference under diverse lighting conditions: matte panels are prone to diffuse reflection, anti-glare panels appear dim in low-light environments, anti-fingerprint panels are prone to residual oil stains and bright spots, and brushed metal panels exhibit periodic texture interference. General preprocessing methods cannot specifically suppress these material-specific interferences, leading to the loss of effective image features or misidentification, ultimately resulting in decreased detection accuracy, especially under strong or low-light conditions where accuracy is extremely poor.

[0032] 1. Frosted Panel Definition: A panel with a rough surface and diffuse reflection properties.

[0033] Interference characteristics: Sheet-like reflection under strong light.

[0034] 2. Anti-Glare Panel Definition: A panel with a surface coating to reduce specular reflection.

[0035] Interference characteristics: Low contrast under low light conditions.

[0036] 3. Anti-Fingerprint Panel Definition: A panel with an oleophobic coating on its surface.

[0037] Interference characteristics: Localized oil stains create dotted reflections.

[0038] 4. Metal Brushed Panel Definition: A metal panel with a periodic brushed texture on its surface.

[0039] Interference characteristics: The overlap of texture and digital edges causes misidentification.

[0040] This application's embodiments focus on four interaction methods (voice, APP, infrared remote control, and touch control) and four types of panel materials (frosted, anti-glare, anti-fingerprint, and brushed metal) for a single brand of air conditioner, achieving standardized interactive verification under a simulated home environment (dynamic lighting, background noise). The laboratory needs to ensure the consistency of the air conditioner's "command-execution" through image recognition technology, meeting core requirements such as temperature recognition accuracy, detection latency, and overall accuracy. The laboratory layout is as follows...Figure 1 As shown.

[0041] like Figure 1 As shown, the laboratory contains an air conditioner to be tested, with a touch-screen device on the air conditioner panel, and a mobile robot. The robot can interact with the air conditioner through various interactive methods and can also photograph the air conditioner panel from different angles and distances. The touch-screen device allows for touch operations on the air conditioner panel.

[0042] Figure 2 This is a flowchart of an air conditioner interactive verification method provided in an embodiment of this application, such as... Figure 2 As shown, the air conditioner interactive verification method includes: S101. Determine the execution requirements and image acquisition rules corresponding to the interaction method to be verified; Specifically, interaction methods include voice interaction, app interaction, infrared remote control, and touch interaction. Execution requirements refer to the operations that need to be performed for each interaction method.

[0043] Image acquisition rules refer to at least one of the following when acquiring images of an air conditioner panel: acquisition distance, acquisition angle, and acquisition timing. For example, image acquisition rules for voice interaction methods include acquisition distance, acquisition angle, and acquisition timing to ensure complete capture of the air conditioner's execution state characteristics corresponding to the voice interaction method.

[0044] For the four interaction methods listed above, a unified core control command is sent: "cooling + specified temperature + no-wind function + timer for 2 hours". The command is then parsed into standardized execution requirements, as follows: Voice interaction: When the robot is 3 meters away from the air conditioner, it sends voice commands at a normal speaking volume. After parsing, it needs to detect all-dimensional features of "temperature display + no wind icon + timer icon". APP interaction: The terminal connects to the air conditioner via Wi-Fi and sends commands. After parsing, the key features detected are "temperature display + timer icon". Infrared remote control: Press the remote control in the following order: "cooling button → temperature adjustment button → no wind button → timer button". After analysis, focus on detecting the "temperature display + no wind icon" feature. Touch interaction: Simulates finger tapping on the panel through a mechanical device, and after analysis, the "temperature display + touch area highlight" feature needs to be detected.

[0045] If the control command does not trigger the air conditioner to respond (e.g., the APP disconnects or the voice is not activated), the system will automatically trigger the retry logic (re-send the command via voice interaction, reconnect the APP to the network, and adjust the transmission angle of the remote control) to ensure the success rate of command triggering.

[0046] S102. Send control commands to the air conditioner according to the execution requirements, and acquire execution status images of the air conditioner panel according to the image acquisition rules; Specifically, the robot's movement trajectory, image acquisition perspective, and acquisition timing can be dynamically adjusted based on the air conditioner's response characteristics under different interaction methods to ensure complete capture of the air conditioner's execution state characteristics, as follows: Voice interaction: The robot moves from 3m away from the air conditioner to 1m directly in front of it (moving speed adapted to the pace of human walking), and collects images from three perspectives: eye level, top view, and bottom view (multiple frames are collected from each perspective to avoid blurring of a single frame). After the command is sent, the robot waits for the air conditioner to respond and display stably before starting the data collection. APP interaction: The robot is fixed 1m in front of the air conditioner and collects close-up images of the head-up view and the temperature and timer icons. After the command is sent, it waits for the panel screen to refresh before collecting images. Infrared remote control: The robot moves from 1.5m to the side of the air conditioner to 1m in front of it, and collects two images from the perspectives of eye level and side view. After pressing the button for the last time, it waits for the state to stabilize before collecting images again. Touch interaction: The robot is fixed 0.8m in front of the air conditioner (to capture the highlight features of the touch at close range), and collects close-up images of the eye-level and focused touch areas. The images are collected in time after the last touch (to avoid the highlight features from disappearing).

[0047] After the execution status image is acquired, the image is compressed to a resolution suitable for model inference, named according to the rule of "interaction method-viewpoint-timestamp", and quickly transmitted to the edge computing device.

[0048] S103. Identify the panel material of the air conditioner panel based on the execution state image, and perform anti-interference processing on the execution state image based on the panel material to obtain the target image; In step S103 above, identifying the panel material of the air conditioner panel based on the execution state image can be achieved by: extracting the index features of the air conditioner panel area in the execution state image, wherein the index features include at least one of texture entropy, polarization degree and texture frequency; and identifying the panel material of the air conditioner panel based on the index features.

[0049] In other words, the four types of panel materials listed above can be distinguished by indicators such as texture entropy, polarization degree, and texture frequency. For example, the texture entropy range of frosted panels is 1.0-1.2, and the texture frequency range of brushed metal panels is 0.3-1Hz, with a material recognition accuracy of ≥99.2%.

[0050] In step S103 above, the anti-interference processing of the execution state image based on the panel material can be specifically implemented as follows: determining the anti-interference processing method corresponding to the panel material based on the preset correspondence between panel material and anti-interference processing method; and using the anti-interference processing method to perform anti-interference processing on the execution state image.

[0051] In some embodiments, the correspondence between the preset panel material and the anti-interference processing method is as follows: The anti-interference processing method for the matte panel is dynamic polarization filtering; the anti-glare panel is multi-scale exposure fusion combined with backlight compensation; the anti-fingerprint panel is oil stain mask combined with Gaussian filtering; and the anti-interference processing method for the brushed metal panel is Gaussian difference texture filtering combined with high brightness suppression.

[0052] For example, scene-specific anti-interference processing can be as follows: Frosted material + voice interaction: Employs dynamic polarization filtering technology (preserving areas with polarization degree P < 0.3) to protect the characteristics of the temperature display and icon areas; Anti-glare material + APP interaction: adopts multi-scale exposure fusion (4 exposure levels) + backlight compensation technology (improving the contrast ratio from 3:1 to 8:1), focusing on the timer icon features; Fingerprint-resistant material + remote control interaction: adopts a combination of oil stain mask (covering 2-5mm oil stain area) and Gaussian filter to protect the characteristics of the windless icon; Brushed metal material + touch interaction: Gaussian difference texture filtering combined with high brightness suppression technology is used to weaken texture interference and protect the touch high brightness area and temperature display features.

[0053] The anti-interference processing steps listed above can assign a weight of 1.5-2.0 times to the core feature regions, avoiding the loss of key details during the anti-interference processing.

[0054] As can be seen, in this embodiment, the panel material is first identified by an algorithm, and then targeted anti-interference processing is implemented in combination with the interaction method. At the same time, the core feature area is weighted and protected, which can maximize the preservation of key features of various scenarios and improve the detection accuracy of subsequent steps.

[0055] For ease of understanding, such as Figure 3 The diagram shown is a flowchart of the anti-interference processing provided in this application.

[0056] S104. Determine a detection strategy based on the interaction method and the panel material, and detect the target image according to the detection strategy to obtain the actual execution state of the air conditioner; Existing general detection models use fixed-size anchor frames, which are incompatible with the size of small targets on air conditioner panels (temperature decimals are only 5×8 pixels, and function icons are only 8×8 pixels). Small target features are easily weakened in deep neural networks, and the proportion of small samples during training is low. In addition, the loss function is not optimized for small targets, resulting in insufficient sensitivity of the model to small target recognition. Ultimately, this manifests as a high false negative rate for small targets and a large error in temperature recognition.

[0057] This application employs a dedicated detection strategy for scenarios combining "materials and interaction methods" to ensure accurate identification of small targets. Specifically, the detection strategy includes: calling a dedicated anchor frame library corresponding to the interaction method and the panel material. This dedicated anchor frame library is a set of anchor frames customized for small-sized targets on panels of different materials; the small-sized target refers to a target smaller than a preset size.

[0058] Exclusive Anchor Library: Definition: A collection of anchor frames customized for small target sizes on panels made of different materials.

[0059] Function: Improves the matching accuracy and recall rate of small target detection.

[0060] Customized Anchor Boxes: Anchor boxes adapted to different scenarios are generated using the K-Means clustering algorithm and assigned to the model's shallow detection head. For example, in a scenario with a frosted material and voice interaction, the customized anchor box for temperature decimals is 5×8 pixels, with an IOU ≥ 0.72, far exceeding the 0.3 level of general anchor boxes. IOU (Intersection over Union) is a core indicator for measuring the degree of overlap between two bounding boxes. Its value is between 0 and 1, with a higher value indicating a higher degree of overlap.

[0061] Feature enhancement processing: Add an edge smoothing layer to voice scenarios (to eliminate jagged edges of digital data), and add a texture suppression attention layer to touch scenarios (to enhance highlight features). Inference optimization: The Focal Loss function (α=0.25, γ=2.0) is adopted, combined with material complexity weights (1.2 for brushed metal and 0.9 for anti-glare materials) to increase the proportion of loss for small targets; the inference confidence threshold is set to a range of 0.55-0.65 to ensure small temperature recognition errors and low false negative rates for small targets. Figure 4 The diagram shown is a structural diagram of the small target accurate detection optimization model provided in this application.

[0062] Focal Loss: Definition: A loss function used to solve the problem of imbalanced sample classes, the formula is as follows: ,in: The model's predicted probability of the true class: If the true class is positive (the target), then... =p, if the true class is the negative class (background), then =1-p. Weighting coefficients (balancing terms) for positive and negative samples: α for positive samples and 1-α for negative samples. γ (gamma): focusing parameter, controlling the degree of suppression of easily distinguishable samples. Function: This application increases the loss weight of small target samples to improve detection accuracy.

[0063] S105. Verify whether the actual execution status is consistent with the execution requirements, and output a verification report.

[0064] The target image is inspected to obtain the actual execution state of the air conditioner in the current interaction mode, and the consistency between the actual execution state and the execution requirements corresponding to the current interaction mode is verified. If they are inconsistent, it indicates that the air conditioner does not meet the detection criteria of the current interaction mode; if they are consistent, it indicates that the air conditioner meets the detection criteria of the current interaction mode. Finally, a verification report is output. The verification report can be uploaded to the laboratory monitoring system.

[0065] In some embodiments, the air conditioning interactive verification method provided in this application further includes the following steps: Record the first moment when the control command is sent; record the second moment when the actual execution state of the air conditioner is obtained; use the time difference between the first moment and the second moment as the end-to-end delay, and record the end-to-end delay in the verification report.

[0066] As can be seen, this application also verified the latency of the entire detection chain, thereby ensuring the accuracy of the detection.

[0067] The specific verification process is as follows: Voice interaction: Associate the feature combination of "temperature + windless icon + timer icon" to verify the integrity and matching degree of the features, while ensuring that the latency meets the real-time requirements; APP Interaction: Associate the combination of "temperature + timer icon" features to verify the accuracy of the timer icon's visual characteristics (such as backlight color) and temperature display; Infrared remote control: Associate the combination of "temperature + no wind icon" features to verify the accuracy of the no wind icon status (such as whether it flashes) and the temperature display; Touch interaction: Associate the feature combination of "temperature + touch highlight area" to verify the matching degree between the shape and position of the highlight area and the temperature display.

[0068] The verification report contains core information such as interaction method, material type, test results, and latency data. It is uploaded to the laboratory monitoring system through a standard interface to provide data support for the spot check of air conditioning interaction quality and algorithm optimization.

[0069] The air conditioner interactive verification method provided in this application effectively suppresses the unique optical interference of different materials by first identifying the panel material and then implementing scene-specific anti-interference processing. This significantly improves the retention rate of effective image features and ultimately achieves a significant improvement in detection accuracy, precisely solving the problem of weak anti-interference capability in general preprocessing of existing technologies. Through the combined optimization of dedicated anchor frame design, scene-based feature enhancement, and material adaptive loss function, the matching degree and feature expression capability between small targets and anchor frames are significantly improved, effectively solving the problem of insufficient sensitivity of existing technologies for the recognition of small targets in air conditioners. Ultimately, this achieves a dual reduction in the false negative rate of small targets and temperature recognition error.

[0070] This application provides an air conditioner interactive verification device, which corresponds to the air conditioner interactive verification method in Embodiment 1. For relevant details, please refer to the description in Embodiment 1. The method embodiments described below are merely illustrative.

[0071] Figure 5 This is a schematic diagram of an air conditioner interactive verification device provided in an embodiment of this application, as shown below. Figure 5 As shown, the device 10 includes: The determination module 101 is used to determine the execution requirements and image acquisition rules corresponding to the interaction method to be verified; The acquisition module 102 is used to send control commands to the air conditioner according to the execution requirements and to acquire execution status images of the air conditioner panel according to the image acquisition rules. The recognition module 103 is used to recognize the panel material of the air conditioner panel based on the execution state image, and to perform anti-interference processing on the execution state image based on the panel material to obtain a target image; Detection module 104 is used to determine a detection strategy based on the interaction method and the panel material, and to detect the target image according to the detection strategy to obtain the actual execution state of the air conditioner; The verification module 105 is used to verify whether the actual execution state is consistent with the execution requirements and output a verification report.

[0072] In one possible implementation, the identification module 103 is specifically used for: Extract the index features of the air conditioning panel area in the execution state image, wherein the index features include at least one of texture entropy, polarization degree and texture frequency; The panel material of the air conditioner panel is identified based on the aforementioned indicator characteristics.

[0073] In one possible implementation, the identification module 103 is specifically used for: Based on the preset correspondence between panel materials and anti-interference processing methods, the anti-interference processing method corresponding to the panel material is determined. The aforementioned anti-interference processing method is used to perform anti-interference processing on the execution state image.

[0074] In one possible implementation, the correspondence between the preset panel material and the anti-interference processing method includes: The anti-interference treatment method for the frosted panel is dynamic polarization filtering; The anti-glare panel uses a multi-scale exposure fusion combined with backlight compensation as its anti-interference processing method. The anti-interference processing method corresponding to the fingerprint-resistant panel is a combination of oil stain masking and Gaussian filtering; The anti-interference processing method for the brushed metal panel is Gaussian difference texture filtering combined with highlight suppression.

[0075] In one possible implementation, the detection strategy includes: The system invokes the dedicated anchor frame library corresponding to the interaction method and the panel material. The dedicated anchor frame library is a collection of anchor frames customized for small-sized targets on panels of different materials. The small-sized target refers to a target smaller than a preset size.

[0076] In one possible implementation, the image acquisition rules include at least one of acquisition distance, acquisition angle, and acquisition timing.

[0077] In one possible implementation, the verification module 105 is further configured to: Record the first moment when the control command is sent; Record the second moment when the actual operating state of the air conditioner is obtained; The time difference between the first moment and the second moment is taken as the end-to-end latency, and the end-to-end latency is recorded in the verification report.

[0078] The air conditioner interaction verification device provided in this application first identifies the material of the air conditioner panel, and then combines the interaction method with targeted anti-interference measures to suppress the interference specific to different materials, thereby improving the feature retention rate and thus enhancing the detection accuracy of the air conditioner interaction status in multiple interaction scenarios and with multiple panel materials. Through the combined optimization of a dedicated anchor frame design, scenario-based feature enhancement, and material adaptive loss function, the matching degree between small targets and anchor frames and the feature expression capability are significantly improved, effectively solving the problem of insufficient sensitivity of existing technologies for small target recognition of air conditioners, and ultimately achieving a dual reduction in the false negative rate of small targets and temperature recognition error.

[0079] This application also provides a verification device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor runs the computer program, it implements the air conditioning interactive verification method provided in any of the foregoing embodiments of this application. This verification device can be used for the control of an air conditioning system.

[0080] The memory may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc.

[0081] The bus can be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. The memory is used to store the program, and the processor executes the program after receiving an execution instruction. The air conditioner interactive verification method disclosed in any of the foregoing embodiments of this application can be applied to a processor, or implemented by a processor.

[0082] The processor may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed through integrated logic circuits in the processor's hardware or through software instructions. The processor can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application-Specific Integrated Circuit (ASIC), an Off-the-shelf Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method.

[0083] The compressor provided in this application embodiment and the air conditioner interactive verification method provided in this application embodiment are based on the same inventive concept and have the same beneficial effects as the methods they adopt, operate or implement.

[0084] This application also provides a computer-readable storage medium storing computer-readable instructions that can be executed by a processor to implement the air conditioning interactive verification method in any of the embodiments of Embodiment 1.

[0085] Examples of the computer-readable storage medium may also include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical or magnetic storage media, which will not be described in detail here.

[0086] The computer-readable storage medium provided in the above embodiments of this application and the air conditioner interactive verification method provided in the embodiments of this application are based on the same inventive concept and have the same beneficial effects as the methods adopted, run or implemented by the application stored therein.

[0087] It should be noted that: Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of this application may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0088] Similarly, it should be understood that, in order to simplify this application and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of this application, various features of this application are sometimes grouped together into a single embodiment, figure, or description thereof. However, this method of disclosure should not be construed as reflecting an intention that the claimed application requires more features than are expressly recited in each claim. Rather, as reflected in the following claims, inventive aspects lie in fewer than all features of a single foregoing disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of this application.

[0089] Those skilled in the art will understand that modules in the device of the embodiments can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0090] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features but not others included in other embodiments, combinations of features from different embodiments are intended to be within the scope of this application and form different embodiments. For example, in the following claims, any of the claimed embodiments can be used in any combination.

[0091] It should be noted that the above embodiments are illustrative of this application and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. This application can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

[0092] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. All equivalent structural transformations made under the concept of the present invention using the contents of the present invention specification and drawings, or direct / indirect applications in other related technical fields, are included within the patent protection scope of the present invention.

Claims

1. An air conditioner interactive verification method, characterized in that, include: Determine the execution requirements and image acquisition rules corresponding to the interaction methods to be verified; The system sends control commands to the air conditioner according to the execution requirements and acquires execution status images of the air conditioner panel according to the image acquisition rules. The panel material of the air conditioner panel is identified based on the execution state image, and anti-interference processing is performed on the execution state image based on the panel material to obtain the target image; A detection strategy is determined based on the interaction method and the panel material, and the target image is detected according to the detection strategy to obtain the actual execution state of the air conditioner; Verify whether the actual execution status is consistent with the execution requirements, and output a verification report.

2. The air conditioning interactive verification method according to claim 1, characterized in that, The step of identifying the panel material of the air conditioner panel based on the execution state image includes: Extract the index features of the air conditioning panel area in the execution state image, wherein the index features include at least one of texture entropy, polarization degree and texture frequency; The panel material of the air conditioner panel is identified based on the aforementioned indicator characteristics.

3. The air conditioning interactive verification method according to claim 1, characterized in that, The step of performing anti-interference processing on the execution state image based on the panel material includes: Based on the preset correspondence between panel materials and anti-interference processing methods, the anti-interference processing method corresponding to the panel material is determined. The aforementioned anti-interference processing method is used to perform anti-interference processing on the execution state image.

4. The air conditioning interactive verification method according to claim 3, characterized in that, The preset correspondence between panel materials and anti-interference processing methods includes: The anti-interference treatment method for the frosted panel is dynamic polarization filtering; The anti-glare panel uses a multi-scale exposure fusion combined with backlight compensation as its anti-interference processing method. The anti-interference processing method corresponding to the fingerprint-resistant panel is a combination of oil stain masking and Gaussian filtering; The anti-interference processing method for the brushed metal panel is Gaussian difference texture filtering combined with highlight suppression.

5. The air conditioning interactive verification method according to claim 1, characterized in that, The detection strategy includes: The system invokes the dedicated anchor frame library corresponding to the interaction method and the panel material. The dedicated anchor frame library is a collection of anchor frames customized for small-sized targets on panels of different materials. The small-sized target refers to a target smaller than a preset size.

6. The air conditioning interactive verification method according to claim 1, characterized in that, The image acquisition rules include at least one of acquisition distance, acquisition angle, and acquisition timing.

7. The air conditioning interactive verification method according to claim 1, characterized in that, The method further includes: Record the first moment when the control command is sent; Record the second moment when the actual operating state of the air conditioner is obtained; The time difference between the first moment and the second moment is taken as the end-to-end latency, and the end-to-end latency is recorded in the verification report.

8. An air conditioner interactive verification device, characterized in that, include: The determination module is used to determine the execution requirements and image acquisition rules corresponding to the interaction method to be verified; The acquisition module is used to send control commands to the air conditioner according to the execution requirements and to acquire execution status images of the air conditioner panel according to the image acquisition rules. The recognition module is used to identify the panel material of the air conditioner panel based on the execution state image, and to perform anti-interference processing on the execution state image based on the panel material to obtain the target image; The detection module is used to determine a detection strategy based on the interaction method and the panel material, and to detect the target image according to the detection strategy to obtain the actual execution state of the air conditioner. The verification module is used to verify whether the actual execution status is consistent with the execution requirements and output a verification report.

9. A verification device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the air conditioning interactive verification method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores computer-readable instructions that can be executed by a processor to implement the method as described in any one of claims 1 to 7.

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