CN112181760A - Anomaly detection method and device - Google Patents
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Abstract
The specification discloses an anomaly detection method and device, and a client can determine a detection instruction after starting to load a page, and determine an image corresponding to the currently displayed page according to the detection instruction. And then, determining the color characteristics of the image, matching the color characteristics of the image with preset abnormal color characteristics and/or normal color characteristics, judging whether the color characteristics of the image are normal or not, determining that the loaded page is abnormal when the color characteristics of the image are abnormal, and determining the loading stage where the page is abnormal according to the matching result of the color characteristics. And finally, sending the information of the loading stage to a target server. The loading stage when the abnormity occurs is more accurately positioned by matching the color characteristics of the image corresponding to the currently displayed page with the preset abnormal color characteristics and/or the normal color characteristics, so that the reason of the abnormity is determined to repair.
Description
Technical Field
The present application relates to the field of exception handling technologies, and in particular, to an exception detection method and apparatus.
Background
With the development of internet technology, more and more clients are widely applied. In the process of using the client, various abnormal conditions often occur, such as: page load failure, etc.
In order to know the abnormal condition generated by the client side, the abnormal condition is repaired. In the prior art, a developer adds monitoring codes to page codes in a point-burying manner. In the process that a user uses the client, the behavior of the user is monitored through the monitoring code, the monitored behavior data of the user are sent to the server for data statistics, so that the server performs user behavior analysis according to the received behavior data of the user, and whether the client is abnormal or not is judged according to the analysis result. For example: when the user clicks the registration page 50 times within a period of time, but the registration behavior of the user is not monitored, it is determined that the registration page may be abnormal.
Disclosure of Invention
The embodiment of the specification provides an anomaly detection method and an anomaly detection device, which are used for partially solving the problem that when an anomaly condition of a page loading process is detected in a point-burying mode in the prior art, only whether a page is loaded normally can be detected, and which loading stage the anomaly condition occurs in cannot be accurately judged, so that the cause of the anomaly is positioned.
The embodiment of the specification adopts the following technical scheme:
an abnormality detection method provided by the present specification includes:
after a page is loaded, determining a detection instruction, wherein the detection instruction is determined when the specified operation of a user on the page or the operation of a page code of the page is monitored;
determining an image corresponding to the currently displayed page according to the detection instruction;
determining the color characteristics of the image according to the determined color information of each pixel point in the image, wherein the color characteristics of the image at least comprise the color proportion of the pixel points in the image;
judging whether the color features of the image are normal or not according to the preset abnormal color features and/or the preset normal color features aiming at the page;
if the abnormal color features of the image are not matched with any preset abnormal color features, determining a loading stage corresponding to the matched abnormal color features as the loading stage where the abnormal color features of the page are located, determining information of the loading stage as abnormal loading stage information, and determining the loading stage where the abnormal color features of the page are located as a loading completion stage and determining information of the loading completion stage as abnormal loading stage information when the color features of the image are not matched with any preset abnormal color features and are not matched with preset normal color features;
and sending the abnormal loading stage information to a target server.
Optionally, the detection instruction at least includes a coordinate position of the detection area;
determining an image corresponding to the currently displayed page according to the detection instruction, specifically including:
determining a detection area in the current display page according to the coordinate position of the detection area contained in the detection instruction;
and taking the determined image of the detection area as an image corresponding to the page.
Optionally, determining the currently displayed detection area in the page according to the coordinate position of the detection area included in the detection instruction specifically includes:
determining the coordinate position of the detection area in the page according to the coordinate position of the detection area, a preset standard resolution and the resolution of the current display equipment contained in the detection instruction;
and determining the detection area in the current display page according to the determined coordinate position of the detection area in the page.
Optionally, the detection instruction further includes a normal color feature preset for a detection area in the page;
judging whether the color features of the image are normal or not according to the preset normal color features of the page, and specifically comprising the following steps:
matching the color characteristics of the determined image of the detection area with the normal color characteristics contained in the detection instruction;
and judging whether the color features of the image are normal or not according to the matching result.
Optionally, different loading stages correspond to different abnormal color features;
judging whether the color features of the image are normal or not according to the preset abnormal color features aiming at the page, and specifically comprising the following steps:
matching the determined color features of the image with the abnormal color features corresponding to each loading stage respectively;
when the abnormal color characteristics corresponding to the loading stages are not matched, determining that the color characteristics of the image are normal;
and when the abnormal color characteristics corresponding to any loading stage are matched, determining that the color characteristics of the image are abnormal.
Optionally, judging whether the color feature of the image is normal according to a normal color feature preset for the page, specifically including:
when the color feature of the image is matched with a preset normal color feature, determining that the color feature of the image is normal;
and when the color features of the image are not matched with preset normal color features, determining that the color features of the image are abnormal.
Optionally, the loading stage of the page at least includes an initial loading stage, a skeleton screen loading stage and a loading completion stage, the initial loading stage and the skeleton screen loading stage respectively correspond to different abnormal color features, and the loading completion stage corresponds to a normal color feature;
judging whether the color features of the image are normal or not according to the preset abnormal color features aiming at the page, and specifically comprising the following steps:
and when the color features of the image are not successfully matched with the abnormal color features and the normal color features, determining that the color features of the image are abnormal.
The present specification provides an abnormality detection device including:
the first determining module is used for determining a detection instruction after a page is loaded, wherein the detection instruction is determined when the specified operation of a user on the page is monitored or the page code of the page is run;
the second determining module is used for determining the image corresponding to the currently displayed page according to the detection instruction;
the third determining module is used for determining the color characteristics of the image according to the determined color information of each pixel point in the image, wherein the color characteristics of the image at least comprise the color proportion of the pixel points in the image;
the judging module judges whether the color features of the image are normal or not according to the preset abnormal color features and/or the preset normal color features aiming at the page, if so, determining that the loaded page is abnormal, and when the color characteristic of the image is matched with any preset abnormal color characteristic, determining a loading stage corresponding to the matched abnormal color feature as a loading stage when the page is abnormal, determining information of the loading stage as abnormal loading stage information, when the color feature of the image is not matched with any one preset abnormal color feature and is not matched with a preset normal color feature, determining a loading stage in which the page is abnormal as a loading completion stage, and determining information of the loading completion stage as abnormal loading stage information;
and the sending module is used for sending the abnormal loading stage information to a target server.
The present specification provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the above-described abnormality detection method.
The present specification provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the processor implements the above-mentioned abnormality detection method.
The embodiment of the specification adopts at least one technical scheme which can achieve the following beneficial effects:
in this specification, after the page starts to be loaded, a detection instruction may be determined first, and an image corresponding to the currently displayed page may be determined according to the detection instruction. And then, determining the color characteristics of the image according to the color information of each pixel point in the image, judging whether the color characteristics of the image are normal or not by matching the color characteristics of the image with preset abnormal color characteristics and/or preset normal color characteristics, determining that the loaded page is abnormal when the color characteristics of the image are abnormal, and determining the loading stage where the page is abnormal according to the matching result of the color characteristics. And finally, the determined information of the loading stage is used as the information of the abnormal loading stage and is sent to the target server. The method comprises the steps of more accurately positioning a page loading stage when an abnormality occurs in a mode of matching color features of an image corresponding to a currently displayed page with preset abnormal color features and/or preset normal color features, and accordingly determining an abnormal reason corresponding to the loading stage to repair the abnormal reason.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic flow chart of an anomaly detection method provided in an embodiment of the present disclosure;
FIG. 2a is a schematic diagram of feature matching provided in an embodiment of the present disclosure;
FIG. 2b is a schematic diagram of feature matching provided by an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of feature matching provided by an embodiment of the present disclosure;
fig. 4 is a schematic diagram of a page loading process provided in an embodiment of the present specification;
fig. 5 is a schematic structural diagram of an abnormality detection apparatus provided in an embodiment of the present disclosure;
fig. 6 is a schematic view of an electronic device implementing an anomaly detection method according to an embodiment of the present disclosure.
Detailed Description
In order to make the objects, technical solutions and advantages of the present disclosure more apparent, the technical solutions of the present disclosure will be clearly and completely described below with reference to the specific embodiments of the present disclosure and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments obtained by a person skilled in the art without making any inventive step based on the embodiments in the description belong to the protection scope of the present application.
The process of page loading in the client is generally: the client sends an acquisition request to a target server to acquire a page code according to the operation of a user on a page in the client, then runs the received page code, and displays the page through a WebView container of the client. Wherein, the page code is written by HyperText Markup Language (HyperText Markup Language-5, H5).
In the prior art, when anomaly detection is performed, a mode of embedding points in a page is usually adopted, that is, monitoring codes are added in page codes, and behaviors of a user are monitored through the monitoring codes. And then uploading the monitored user behaviors to a server, and analyzing the user behaviors by the server to judge whether the client has an abnormal condition according to an analysis result. However, after the page code is run, the page code needs to be displayed through the WebView container of the client. That is, the page code runs successfully, and the corresponding user behavior is monitored and is not equal to the page display success. If a page loading failure is caused by an error in the process of displaying the page through the WebView container, the abnormal condition cannot be detected in a mode of monitoring user behavior data through a buried point.
Therefore, the anomaly detection method provided by the present specification performs anomaly analysis on the image of the displayed page in the page loading process, so as to determine whether the page loading is abnormal or not, and which loading stage in the page loading process the anomaly occurs. The reason for the occurrence of the exception can be determined subsequently according to the loading stage in which the exception is generated.
The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.
Fig. 1 is a schematic flow chart of an anomaly detection method provided in an embodiment of the present specification, which specifically includes the following steps:
s100: after starting to load the page, a detection instruction is determined.
The anomaly detection method provided by the specification is used for determining whether an abnormal condition occurs in the page loading process in the client side by performing anomaly analysis on the image of the loaded page. Therefore, the method can be executed by a client, and certainly, the method can also be executed by a corresponding server, and when the server executes the abnormality detection method, the client needs to send the image corresponding to the currently displayed page determined subsequently to the server for abnormality analysis. For convenience of description, the method for performing anomaly detection by the client is described as an example.
Further, a certain loading time is needed from the beginning of loading the page to the completion of page loading, and the worse the network condition, the longer the loading time. In the page loading process, the page sequentially passes through an initial loading stage and a skeleton screen loading stage until a loading completion stage, wherein the loading completion stage is a stage for displaying all contents contained in the page. And the content displayed by the page is not completely the same in different loading stages. When the final display page is in the initial loading stage or the skeleton screen loading stage, the page loading can be considered to be abnormal. The final display page refers to a page displayed to the user after a certain loading time period from the beginning of loading the page. And when the page loading is abnormal, the final display page is displayed as the abnormal condition of the page, and when the page loading is normal, the final display page is displayed as the loaded page content.
Because a certain loading duration is needed for loading the page, the screenshot is performed on the page when the page is still in the continuous loading process, and the analysis error is caused by performing exception analysis on the screenshot. For example: assuming that the page can be normally loaded and the time for completing loading needs 30s, if the screenshot is performed on the page 10s after the page is started to be loaded, the page is not yet loaded and is in an initial loading stage or a skeleton screen loading stage, and then the screenshot of the page at the moment is subjected to exception analysis to determine that the page is abnormally loaded, so that an exception detection error is caused.
In order to avoid the above situation, after the client starts to load the page, when the detection instruction needing to be detected is determined, the client performs screenshot on the displayed page to determine the image corresponding to the page. That is, the screen shot ensuring the anomaly analysis is the image of the final display page. Therefore, after the client loads the page, the client determines the detection instruction first and then performs screenshot according to the detection instruction.
Furthermore, in the process of using the client, if the page loading is abnormal, the user usually closes the page and tries to open again. Therefore, when the anomaly detection is performed in the page loading process in the description, the behavior operation of closing the page by the user can be used as a detection instruction, and when the behavior operation of closing the page by the user is monitored by the client, that is, when the detection instruction is determined, whether the page loading is abnormal or not can be judged through subsequent steps. Of course, the specified operation of the user on the page may also be used as the detection instruction, for example: the user behavior operation is not limited in this specification, and may be set as needed, as long as the specified operation is a user behavior operation when the page is changed after the page is displayed.
S102: and determining the image corresponding to the currently displayed page according to the detection instruction.
In this specification, after receiving a detection instruction, for example, after monitoring a behavior operation of closing a page by a user, a client may capture a screenshot of the currently displayed page, determine an image corresponding to the page, perform an anomaly analysis on the image, and determine whether the page is abnormal in loading.
Specifically, when the client monitors the behavior operation of closing the page by the user, the client can capture the currently displayed page and use the image obtained by capturing the image as the image corresponding to the currently displayed page.
In addition, when the currently displayed page is subjected to screenshot, in order to reduce the calculation amount for performing subsequent anomaly analysis, in this specification, the client may perform screenshot on only a partial region in the currently displayed page, and use the image of the truncated partial region as an image corresponding to the currently displayed page. For example: and only capturing the middle two thirds of the area of the current display page, and determining that the image of the two thirds of the area is the image corresponding to the current display page.
It should be noted that when only partial region in the page is subjected to screenshot to perform exception analysis on the screenshot, corresponding color features corresponding to different loading stages are predetermined, and when subsequent feature matching is performed, corresponding partial regions in the page in different loading stages are also subjected to screenshot, and the color features of the screenshot of the partial region are determined. For example: when only the middle two-thirds area of the displayed page is subjected to screenshot, and the color features of different loading stages are predetermined, the middle two-thirds area of the page corresponding to the different loading stages is also subjected to screenshot, and the color features of the image in the two-thirds area are subsequently determined.
S104: and determining the color characteristics of the image according to the determined color information of each pixel point in the image.
Generally, the page loading process is mainly divided into: the method comprises an initial loading stage, a skeleton screen loading stage and a loading finishing stage, wherein when a page is in different loading stages, color features displayed in the page are not identical. And the color characteristics of each loading stage may be predetermined. For example: assuming that the page is set to be gray during the loading stage of the skeleton screen, the color characteristics of the page displayed during the loading stage of the skeleton screen are as follows: the page keytone is gray. The initial loading stage refers to a stage of displaying a white screen or a background color of a client WebView container during initial loading of a page.
Therefore, in this specification, whether the page loading is abnormal or not can be determined by comparing the color characteristics of the currently displayed page with the color characteristics of each loading stage. The client may then determine the color characteristics of the image from the image of the currently displayed page.
Specifically, the client may determine color information of each pixel point in an image corresponding to the currently displayed page. The color information of the pixel point includes R, G, B color values of the pixel point. And then, determining the color proportion of each pixel point in the image according to the color information of each pixel point in the image, namely, the number of the pixel points of each color accounts for the proportion of the total pixel points contained in the image. And finally, determining the color characteristics of the image according to the determined color proportion of each pixel point in the image. When the color features of the image are determined according to the color ratios of the pixel points, the color with the highest ratio in the color ratios can be used as the color features of the image.
Of course, the color features of the image in this specification may also include position information of color distribution of each pixel point, and the content included in the specific color features is not limited in this specification, and only the same manner as the manner of determining the color features corresponding to each different loading stage is required.
S106: and judging whether the color features of the image are normal or not according to the abnormal color features and/or the normal color features preset aiming at the page.
In this specification, after the color feature of the image of the finally displayed page is determined in step S104, the color feature of the image may be matched with the color features corresponding to different loading stages in the page loading process to determine whether the page loading is normal.
The page loading process sequentially comprises the following steps: the method comprises an initial loading stage, a skeleton screen loading stage and a loading completion stage, wherein when a final display page is in the initial loading stage or the skeleton screen loading stage, the loading can be considered to be abnormal. And the abnormal color features preset for the page are the color features corresponding to the initial loading stage or the color features corresponding to the framework screen loading stage.
The client can judge whether the color features of the image are normal or not according to the preset abnormal color features aiming at the page. Specifically, the client may match the color feature of the image with preset abnormal color features of different loading stages, determine that the color feature of the image is abnormal when the matching is successful, and determine that the color feature of the image is normal when the matching is unsuccessful.
Fig. 2a is a schematic diagram of the determined color ratio of each pixel point in the image, and it can be determined from fig. 2a that the ratio of white pixel points in the image is 90% and the ratio of black pixel points is 10%, so according to the color ratio of each pixel point, the white with the highest ratio can be determined as the color feature of the image. The left diagram in fig. 2b represents the abnormal color features corresponding to the predetermined initial loading stage, that is, all white pixels in the image. The right-hand graph in fig. 2b represents the abnormal color features corresponding to the predetermined skeleton screen loading stage, that is, all the gray pixel points in the image. Then through color feature matching, it can be determined that the color feature of the image matches the corresponding abnormal color feature at the initial loading stage, and thus it can be determined that the color feature of the image is abnormal.
Further, in order to more accurately determine whether the final display page is abnormal, the client may also pre-store the normal color features of each page, or obtain the normal color features of each page from the server. When the normal color feature of the page is obtained from the server, the normal color feature may be obtained in advance before the page code is obtained, or may be carried in the page code and sent to the client.
Therefore, the client can judge whether the color features of the image are normal or not according to the normal color features preset for the page. Specifically, the client may match the color features of the image with preset normal color features, determine that the color features of the image are normal when the matching is successful, and determine that the color features of the image are abnormal when the matching is unsuccessful.
Assuming that the normal color feature preset for the page is that the color with the highest proportion in the page is black, fig. 3 shows that the proportion of gray pixels contained in the image is determined to be 60%, the proportion of black pixels is 30%, and the proportion of white pixels is 10%. Then, according to the color proportion of each pixel point, the gray with the highest proportion can be determined as the color characteristic of the image. It may be determined that the color feature of the image does not match the preset normal color feature through color feature matching, and thus it may be determined that the color feature of the image is abnormal.
Furthermore, whether the final display page loaded at this time is abnormal or not is judged more accurately, and the final display page is in which loading stage when the abnormal occurs. The client may also prestore the abnormal color feature of the initial loading stage, the abnormal color feature of the skeleton screen loading stage, and the normal color feature of the loading completion stage, or the normal color feature of the loading completion stage may be acquired from the server before acquiring the page code, or may be sent by being carried in the page code.
The client can judge whether the color features of the image are normal or not according to the normal color features and the abnormal color features preset for the page. Specifically, the client may match the color features of the image with preset different color features respectively. When the matching is successful, it may be determined that the color feature of the image is abnormal. And when the matching is unsuccessful, matching the color characteristic of the image with a preset normal color characteristic, and when the matching with the normal color characteristic is successful, determining that the color characteristic of the image is normal, otherwise, determining that the color characteristic of the image is abnormal.
S108: if the abnormal color features of the image are not matched with any preset abnormal color features, determining the loading stage corresponding to the matched abnormal color features as the loading stage where the abnormal color features of the page are located, determining the information of the loading stage as the abnormal loading stage information, and when the color features of the image are not matched with any preset abnormal color features and are not matched with preset normal color features, determining the loading stage where the abnormal color features of the page are located as the loading completion stage, and determining the information of the loading completion stage as the abnormal loading stage information.
S110: and sending the abnormal loading stage information to a target server.
In this specification, after determining that the color feature of the image is abnormal in step S106, the loading stage where the page loading is abnormal may be determined according to the color feature of the image, and the loading stage is reported to the target server, so as to determine the cause of the abnormality and repair the abnormality.
When it is determined that the color feature of the image is abnormal only by matching with the preset abnormal color feature in step S106, that is, the color feature of the image matches with any one of the preset abnormal color features. When the loading stage is determined to be abnormal, the client may determine that the page is loaded abnormally according to the color feature abnormality of the image. And then, according to the color features of the image, determining a loading stage corresponding to the abnormal color features matched with the color features of the image as the loading stage where the abnormality occurs, and determining the information of the loading stage as the abnormal loading stage information. The exception loading stage information at least includes the loading stage where the exception is located, and may also include information such as the time when the exception occurs. And finally, sending the abnormal loading stage information to a target server so that the target server counts the times of the abnormal loading in each abnormal stage according to the received information of each abnormal loading stage, determines that the abnormal loading possibly occurs when the preset times are reached, and analyzes the reason of the abnormal loading to repair. The preset times can be set according to needs, and the specification does not limit the preset times.
When the color feature of the image is abnormal by matching with the preset normal color feature and the preset abnormal color features in step S106, it is determined that the color feature of the image is abnormal. When the loading stage is determined to be abnormal, the client may determine that the page is loaded abnormally according to the color feature abnormality of the image. And then, according to the color features of the image, when the color features of the image are determined to be matched with any preset abnormal color feature, determining a loading stage corresponding to the matched abnormal color feature as a loading stage where the page is loaded when the page is abnormal, and determining information of the loading stage as abnormal loading stage information. And when the color characteristic of the image is not matched with any preset abnormal color characteristic and is not matched with the preset abnormal color characteristic, determining that the abnormality occurs in the loading completion stage, and determining the information of the loading completion stage as the information of the abnormal loading stage.
And finally, after the abnormal loading stage information is determined, the client can send the abnormal loading stage information to the target server, so that the target server determines the reason of the abnormal generation and repairs the abnormal generation according to the received abnormal loading stage information.
In summary, the anomaly detection method provided by the present specification can be applied to the page loading process, as shown in fig. 4. The page loading process mainly comprises an initial loading stage, a skeleton screen loading stage and a loading completion stage, wherein in the initial loading stage, a client side initializes webview, in the skeleton screen loading stage, the client side renders the background of the page, and in the loading completion stage, the client side loads page data in the page. The color features of the screenshot obtained in step S102 are respectively matched with the image color features of different loading stages, and which loading stage the abnormality occurs in can be determined according to the matching result.
Based on the anomaly detection method shown in fig. 1, after the client starts to load the page, the client determines a detection instruction, and determines the image corresponding to the currently displayed page according to the detection instruction. And then, determining the color characteristics including the color ratios of the pixels in the image according to the color information of the pixels in the image. And then, matching the color features of the image with preset abnormal color features and/or preset normal color features, judging whether the color features of the image are normal or not, if the color features of the image are abnormal, determining that the loaded page is abnormal, determining abnormal loading stage information of the loaded page with the abnormal loading according to the matching result of the color features, and sending the abnormal loading stage information to a target server. The loading stage when the abnormity occurs is more accurately positioned by matching the color characteristics of the image corresponding to the currently displayed page with the preset abnormal color characteristics and/or the normal color characteristics, so that the reason of the abnormity is determined to repair.
In another embodiment of this specification, in order to make the anomaly detection more flexible and meet the needs of the service, a developer may set the detection area in the page and the normal color feature of the detection area in advance according to the service requirements, and write the detection area and the normal color feature as configuration information into the page code. When the page needs to be subjected to anomaly detection, the detection area in the page can be detected according to the configuration information which is preset aiming at the page.
Therefore, in step S100 in this specification, after triggering to execute the configuration information in the page code after starting to load the page, the client may execute the page code to determine a detection instruction, where the detection instruction includes preset configuration information, that is, the coordinate position of the detection area and the abnormal color feature of the detection area. Since the detection area preset according to the service requirement is usually a partial area in the loaded page, when the detection area is abnormal, the corresponding page loading stage is the loading completion stage.
Then, in step S102 of this specification, the client may determine the detection area in the currently displayed page according to the coordinate position of the detection area included in the detection instruction, and use the image of the determined detection area as the image corresponding to the currently displayed page.
The client determines the coordinate position of the detection area in the currently displayed page according to the coordinate position of the detection area contained in the detection instruction, the preset standard resolution and the resolution of the current display device when determining the detection area in the currently displayed page according to the coordinate position of the detection area contained in the detection instruction due to the different resolutions of the displayed pages in different terminals. And then, determining the detection area in the current display page according to the coordinate position of the determined detection area in the current display page.
Finally, in step S106 in this specification, the client may determine whether the color feature of the image matches a normal color feature preset in the detection instruction for the page, and when the matching is unsuccessful, it may determine that the page is loaded abnormally, and the loading stage where the page is loaded abnormally is a loading completion stage. And sending the abnormal loading stage information of the loading completion stage to a target server, so that when the number of times of the target server counting the abnormal occurrence of the loading completion stage is greater than the preset number of times, determining the reason of the abnormal occurrence and repairing. The preset times can be set according to needs, and the specification does not limit the preset times.
Further, when anomaly detection is performed on a preset detection area according to a service requirement in this specification, whether page loading is abnormal or not can be detected in an element feature matching manner instead of a color feature matching manner. Specifically, the element feature may be a format feature such as an image or a text, or may be another form of feature, for example: a key frame, etc., which is not limited in this specification and can be set as desired. The client can determine the element features contained in the image of the detection area and match the element features preset for the detection area in the detection instruction. And when the matching is successful, determining that the page is loaded normally, otherwise, determining that the page is loaded abnormally, wherein the loading stage when the abnormality occurs is a loading completion stage.
Based on the anomaly detection method shown in fig. 1, an embodiment of the present specification further provides a schematic structural diagram of an anomaly detection apparatus, as shown in fig. 5.
Fig. 5 is a schematic structural diagram of an abnormality detection apparatus provided in an embodiment of the present specification, where the apparatus includes:
the first determining module 200 is configured to determine a detection instruction after starting to load a page, where the detection instruction is determined when a user's designated operation on the page or running a page code of the page is monitored;
the second determining module 202 is configured to determine, according to the detection instruction, an image corresponding to the currently displayed page;
a third determining module 204, configured to determine color characteristics of the image according to the determined color information of each pixel point in the image, where the color characteristics of the image at least include a color ratio of the pixel points in the image;
the determining module 206 determines whether the color feature of the image is normal according to a preset abnormal color feature and/or a preset normal color feature for the page, and if the color feature is abnormal, determining that the loaded page is abnormal, and when the color characteristic of the image is matched with any preset abnormal color characteristic, determining a loading stage corresponding to the matched abnormal color feature as a loading stage when the page is abnormal, determining information of the loading stage as abnormal loading stage information, when the color feature of the image is not matched with any one preset abnormal color feature and is not matched with a preset normal color feature, determining a loading stage in which the page is abnormal as a loading completion stage, and determining information of the loading completion stage as abnormal loading stage information;
the sending module 208 sends the abnormal loading stage information to the target server.
Optionally, the detection instruction at least includes a coordinate position of a detection region, and the second determining module 202 is specifically configured to determine the currently displayed detection region in the page according to the coordinate position of the detection region included in the detection instruction, and use an image of the determined detection region as an image corresponding to the page.
Optionally, the second determining module 202 is specifically configured to determine the coordinate position of the detection region in the page according to the coordinate position of the detection region, a preset standard resolution, and the resolution of the current display device, which are included in the detection instruction, and determine the detection region in the current display page according to the determined coordinate position of the detection region in the page.
Optionally, the detection instruction further includes a normal color feature preset for the detection area in the page, and the determining module 206 is specifically configured to match the color feature of the image in the determined detection area with the normal color feature included in the detection instruction, and determine whether the color feature of the image is normal according to a matching result.
Optionally, the different loading stages correspond to different abnormal color features, and the determining module 206 is specifically configured to match the determined color features of the image with the abnormal color features corresponding to the loading stages, determine that the color features of the image are normal when the determined color features do not match the abnormal color features corresponding to the loading stages, and determine that the color features of the image are abnormal when the determined color features match the abnormal color features corresponding to any loading stage.
Optionally, the determining module 206 is specifically configured to determine that the color feature of the image is normal when the color feature of the image matches a preset normal color feature, and determine that the color feature of the image is abnormal when the color feature of the image does not match the preset normal color feature.
Optionally, the loading stage of the page at least includes an initial loading stage, a skeleton screen loading stage, and a loading completion stage, the initial loading stage and the skeleton screen loading stage respectively correspond to different abnormal color features, the loading completion stage corresponds to a normal color feature, and the determining module 206 is specifically configured to determine that the color feature of the image is abnormal when the color feature of the image is not successfully matched with the abnormal color feature and the normal color feature.
Embodiments of the present specification further provide a computer-readable storage medium, where a computer program is stored, and the computer program may be used to execute the abnormality detection method provided in fig. 1.
Based on the model training method shown in fig. 1, an embodiment of this specification further provides a schematic structural diagram of the electronic device shown in fig. 6. As shown in fig. 6, at the hardware level, the electronic device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory, but may also include hardware required for other services. The processor reads a corresponding computer program from the non-volatile memory into the memory and then runs the computer program to implement the above-described abnormality detection method shown in fig. 1.
Of course, besides the software implementation, the present specification does not exclude other implementations, such as logic devices or a combination of software and hardware, and the like, that is, the execution subject of the following processing flow is not limited to each logic unit, and may be hardware or logic devices.
In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an Integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Hardware Description Language), traffic, pl (core universal Programming Language), HDCal (jhdware Description Language), lang, Lola, HDL, laspam, hardward Description Language (vhr Description Language), vhal (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.
The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functions of the various elements may be implemented in the same one or more software and/or hardware implementations of the present description.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media 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 memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, the description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
This description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The above description is only an example of the present specification, and is not intended to limit the present specification. Various modifications and alterations to this description will become apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present specification should be included in the scope of the claims of the present specification.
Claims (10)
1. An abnormality detection method characterized by comprising:
after a page is loaded, determining a detection instruction, wherein the detection instruction is determined when the specified operation of a user on the page or the operation of a page code of the page is monitored;
determining an image corresponding to the currently displayed page according to the detection instruction;
determining the color characteristics of the image according to the determined color information of each pixel point in the image, wherein the color characteristics of the image at least comprise the color proportion of the pixel points in the image;
judging whether the color features of the image are normal or not according to the preset abnormal color features and/or the preset normal color features aiming at the page;
if the abnormal color features of the image are not matched with any preset abnormal color features, determining a loading stage corresponding to the matched abnormal color features as the loading stage where the abnormal color features of the page are located, determining information of the loading stage as abnormal loading stage information, and determining the loading stage where the abnormal color features of the page are located as a loading completion stage and determining information of the loading completion stage as abnormal loading stage information when the color features of the image are not matched with any preset abnormal color features and are not matched with preset normal color features;
and sending the abnormal loading stage information to a target server.
2. The method of claim 1, wherein the detection instruction includes at least a coordinate position of the detection area;
determining an image corresponding to the currently displayed page according to the detection instruction, specifically including:
determining a detection area in the currently displayed page according to the coordinate position of the detection area contained in the detection instruction;
and taking the determined image of the detection area as an image corresponding to the page.
3. The method according to claim 2, wherein determining the detection area in the currently displayed page according to the coordinate position of the detection area included in the detection instruction specifically includes:
determining the coordinate position of the detection area in the page according to the coordinate position of the detection area, a preset standard resolution and the resolution of the current display equipment contained in the detection instruction;
and determining the detection area in the current display page according to the determined coordinate position of the detection area in the page.
4. The method according to claim 2, wherein the detection instruction further includes a normal color feature preset for a detection area in the page;
judging whether the color features of the image are normal or not according to the preset normal color features of the page, and specifically comprising the following steps:
matching the color characteristics of the determined image of the detection area with the normal color characteristics contained in the detection instruction;
and judging whether the color features of the image are normal or not according to the matching result.
5. The method of claim 1, wherein different loading phases correspond to different exception color characteristics;
judging whether the color features of the image are normal or not according to the preset abnormal color features aiming at the page, and specifically comprising the following steps:
matching the determined color features of the image with the abnormal color features corresponding to each loading stage respectively;
when the abnormal color characteristics corresponding to the loading stages are not matched, determining that the color characteristics of the image are normal;
and when the abnormal color characteristics corresponding to any loading stage are matched, determining that the color characteristics of the image are abnormal.
6. The method of claim 1, wherein determining whether the color feature of the image is normal according to a normal color feature preset for the page specifically comprises:
when the color feature of the image is matched with a preset normal color feature, determining that the color feature of the image is normal;
and when the color features of the image are not matched with preset normal color features, determining that the color features of the image are abnormal.
7. The method of claim 1, wherein the loading phases of the page at least include an initial loading phase, a skeleton screen loading phase and a loading completion phase, the initial loading phase and the skeleton screen loading phase respectively correspond to different abnormal color features, and the loading completion phase corresponds to a normal color feature;
judging whether the color features of the image are normal or not according to the abnormal color features and/or the normal color features preset aiming at the page, and specifically comprising the following steps:
and when the color features of the image are not successfully matched with the abnormal color features and the normal color features, determining that the color features of the image are abnormal.
8. An abnormality detection device, characterized by specifically comprising:
the first determining module is used for determining a detection instruction after a page is loaded, wherein the detection instruction is determined when the specified operation of a user on the page is monitored or the page code of the page is run;
the second determining module is used for determining the image corresponding to the currently displayed page according to the detection instruction;
the third determining module is used for determining the color characteristics of the image according to the determined color information of each pixel point in the image, wherein the color characteristics of the image at least comprise the color proportion of the pixel points in the image;
the judging module judges whether the color features of the image are normal or not according to the preset abnormal color features and/or the preset normal color features aiming at the page, if so, determining that the loaded page is abnormal, and when the color characteristic of the image is matched with any preset abnormal color characteristic, determining a loading stage corresponding to the matched abnormal color feature as a loading stage when the page is abnormal, determining information of the loading stage as abnormal loading stage information, when the color feature of the image is not matched with any one preset abnormal color feature and is not matched with a preset normal color feature, determining a loading stage in which the page is abnormal as a loading completion stage, and determining information of the loading completion stage as abnormal loading stage information;
and the sending module is used for sending the abnormal loading stage information to a target server.
9. A computer-readable storage medium, characterized in that the storage medium stores a computer program which, when executed by a processor, implements the method of any of the preceding claims 1-7.
10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any of claims 1-7 when executing the program.
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