Teaching evaluation method for gram staining experiment of bacteria

Abstract

The invention discloses a teaching evaluation method for a gram staining experiment of bacteria, which is used for solving the problems of strong subjectivity, low efficiency and difficulty in comprehensively covering experimental operation details due to dependence on manual observation and recording in a traditional mode. Acquiring an operation image when an experimenter performs normal saline dropwise adding operation, and calculating a normal saline dropwise adding score according to the operation image; collecting the temperature of the inoculating loop to calculate the use score of the inoculating loop, detecting and identifying the bacterium taking operation of the inoculating loop, and calculating the bacterium taking score of the inoculating loop; continuous frame extraction identification is carried out on the linear distance change of a glass slide and an alcohol lamp, and smear and drying scores are calculated; carrying out normative judgment on the gram staining operation in sequence, calculating a gram staining score, and carrying out imaging color identification on a staining result to obtain a microscopic examination score; and obtaining a comprehensive teaching score by integrating the normal saline dropwise adding score, the inoculating loop use score, the inoculating loop bacterium taking score, the smear and drying score, the Gram staining score and the microscopic examination score.

Description

Technical Field

[0001] The present invention relates to the technical field of biomedical experimental teaching evaluation, and particularly relates to a teaching evaluation method for a bacterial Gram staining experiment, a teaching evaluation device for a bacterial Gram staining experiment, a camera device, and a storage medium. Background Art

[0002] Bacterial Gram staining is an important method for bacterial identification. This method classifies bacteria into two major categories, Gram-positive bacteria and Gram-negative bacteria, by utilizing the biochemical property differences on the bacterial cell wall.

[0003] In biomedical education, the bacterial Gram staining experiment is an important link for cultivating students' experimental skills and enhancing their microbiology knowledge. However, traditional teaching evaluation methods mainly rely on manual observation and recording, which have problems such as strong subjectivity, low efficiency, and difficulty in comprehensively covering experimental operation details. With the rapid development of computer vision and Internet of Things technologies, it has become particularly important to develop an evaluation system that can automatically identify the key steps of the Gram staining experiment and objectively score the experimental operation. Summary of the Invention

[0004] The present invention provides a teaching evaluation method for a bacterial Gram staining experiment, a teaching evaluation device for a bacterial Gram staining experiment, a camera device, and a storage medium, which are used to solve or partially solve the technical problems that traditional teaching evaluation methods rely on manual observation and recording, have strong subjectivity, low efficiency, and difficulty in comprehensively covering experimental operation details.

[0005] The present invention provides a teaching evaluation method for a bacterial Gram staining experiment, and the method includes:

[0006] Collect the operation images of the experimenter during the saline dropping operation, and calculate the saline dropping score according to the operation images;

[0007] Collect the temperature of the inoculation loop, calculate the inoculation loop usage score based on the inoculation loop temperature, and detect and identify the inoculation loop bacteria-taking operation of the experimenter, and calculate the inoculation loop bacteria-taking score;

[0008] Calculate the smear and drying score by continuously extracting frames and identifying the change in the straight-line distance between the slide and the alcohol lamp;

[0009] Judge the standardization of the experimenter's Gram staining operation in sequence, calculate the Gram staining score, and perform imaging color recognition on the Gram staining result to obtain the microscopy score;

[0010] Combining the saline dripping score, the inoculation loop usage score, the inoculation loop bacteria collection score, the smear and drying score, the Gram staining score, and the microscopic examination score, the comprehensive teaching score of the experimental personnel is obtained.

[0011] Optionally, calculating the saline dripping score according to the operation image includes:

[0012] First, grayscale the operation image, then perform filtering denoising, and extract the edge information of the glass slide and the saline drop in the processed image through an edge detection algorithm;

[0013] According to the edge information, calculate the edge distance between the saline drop and the glass slide, and the water drop diameter of the saline drop on the glass slide;

[0014] Calculate the water drop moderation score according to the water drop diameter, and calculate the water drop position score according to the edge distance;

[0015] Integrate the water drop moderation score and the water drop position score as the saline dripping score.

[0016] Optionally, the inoculation loop temperature includes the highest burning temperature during inoculation loop burning and the lowest bacteria collection temperature before inoculation loop bacteria collection; calculating the inoculation loop usage score based on the inoculation loop temperature includes:

[0017] Compare the highest burning temperature with a preset burning temperature threshold, and obtain the burning sterilization score according to the burning temperature comparison result;

[0018] Compare the lowest bacteria collection temperature with a preset bacteria collection temperature threshold, and obtain the pre-bacteria collection cooling score according to the bacteria collection temperature comparison result;

[0019] Integrate the burning sterilization score and the pre-bacteria collection cooling score as the inoculation loop usage score.

[0020] Optionally, detecting and identifying the inoculation loop bacteria collection operation of the experimental personnel and calculating the inoculation loop bacteria collection score includes:

[0021] When it is detected that the experimental personnel enter the inoculation loop bacteria collection operation, recognize the finger bending degree, palm orientation, arm movement action of the experimental personnel, and the distance between both hands and the culture dish through a gesture recognition algorithm;

[0022] Through target detection and recognition, recognize the positions of the culture dish and the alcohol lamp on the experimental table, and calculate the straight-line distance between the culture dish and the alcohol lamp;

[0023] Calculate the culture dish-alcohol lamp distance score according to the straight-line distance between the culture dish and the alcohol lamp;

[0024] Based on the degree of finger bending, palm orientation, arm movement, and the distance between the hands and the petri dish of the experimenter, determine whether the experimenter opens the petri dish with one hand to obtain a one-handed operation score;

[0025] Integrate the petri dish - alcohol lamp distance score and the one-handed operation score as the inoculation loop bacteria picking score.

[0026] Optionally, the method of calculating the smear and drying score by continuously extracting frames from the change in the straight-line distance between the slide and the alcohol lamp includes:

[0027] When it is detected that the experimenter finishes the smear operation, through target detection recognition, identify the coated area of the slide and determine whether the coated area is evenly smeared to obtain a smear evenness score;

[0028] Through real-time tracking detection, identify whether the experimenter holds the alcohol lamp and place the alcohol lamp under the slide and swing it 3 times at the pendulum speed;

[0029] When the number of swings is detected to be 3 times, identify the change in the straight-line distance between the slide and the alcohol lamp during the swinging process by continuous frame extraction. Based on the recognition result of the straight-line distance change, calculate the drying action error score, and integrate the smear evenness score and the drying action error score as the smear and drying score;

[0030] When the number of swings is detected not to be 3 times, directly record the smear evenness score as the smear and drying score.

[0031] Optionally, the steps of the Gram staining operation at least include primary staining, mordanting, decolorization, and counterstaining in sequence; the method of judging the standardization of the experimenter's Gram staining operation in sequence and calculating the Gram staining score includes:

[0032] Through target detection recognition, identify the bottle body position, style, and cap change situation of crystal violet stain, Lugol's iodine solution, 95% ethanol, and safranin stain, and determine whether the experimenter performs the primary staining, mordanting, decolorization, and counterstaining operations in sequence;

[0033] If so, obtain the start time of the primary staining operation, the end time of the primary staining operation, the start time of the mordanting operation, the end time of the mordanting operation, the start time of the decolorization operation, the end time of the decolorization operation, the start time of the counterstaining operation, and the end time of the counterstaining operation;

[0034] Calculate the execution score of the primary staining operation based on the start time and end time of the primary staining operation, calculate the execution score of the mordanting operation based on the start time and end time of the mordanting operation, calculate the execution score of the decolorization operation based on the start time and end time of the decolorization operation, and calculate the execution score of the counterstaining operation based on the start time and end time of the counterstaining operation;

[0035] Identify whether there are residual water droplets on the slide through the water stain recognition algorithm, and obtain the residual water droplet judgment score;

[0036] Calculate the Gram staining score based on the execution score of the primary staining operation, the execution score of the mordanting operation, the execution score of the decolorization operation, the execution score of the counterstaining operation, and the residual water droplet judgment score, in combination with the step execution order factor.

[0037] Optionally, the imaging color recognition of the Gram staining result to obtain the microscopy score includes:

[0038] After completing the Gram staining experiment, extract frames from the image shown on the electron microscope to obtain the Gram staining image;

[0039] Perform imaging color recognition on the Gram staining image, and perform staining comparison and judgment according to the imaging color recognition result, and obtain the color temperature value detection score, the staining judgment score, the cell distance score, and the color type score respectively;

[0040] Integrate the color temperature value detection score, the staining judgment score, the cell distance score, and the color type score as the microscopy score.

[0041] The present invention also provides a teaching evaluation device for bacterial Gram staining experiments, including:

[0042] A physiological saline dropping score calculation unit for collecting operation images of the experimenter during the physiological saline dropping operation and calculating the physiological saline dropping score according to the operation images;

[0043] An inoculation loop operation score calculation unit for collecting the temperature of the inoculation loop, calculating the inoculation loop usage score based on the inoculation loop temperature, and detecting and identifying the inoculation loop bacteria picking operation of the experimenter to calculate the inoculation loop bacteria picking score;

[0044] A smear and drying score calculation unit for continuously extracting frames and identifying the change in the straight-line distance between the slide and the alcohol lamp to calculate the smear and drying score;

[0045] Gram staining score calculation unit, which is used to judge the standardization of the Gram staining operation of the experimenter in sequence, calculate the Gram staining score, and perform imaging color recognition on the Gram staining result to obtain the microscopy score;

[0046] Comprehensive teaching score calculation unit, which is used to comprehensively obtain the comprehensive teaching score of the experimenter based on the saline drop addition score, the inoculation loop use score, the inoculation loop bacteria picking score, the smear and drying score, the Gram staining score and the microscopy score.

[0047] The present invention also provides a camera device, which includes a processor and a memory:

[0048] The memory is used to store program codes and transmit the program codes to the processor;

[0049] The processor is used to execute the teaching evaluation method of the bacterial Gram staining experiment as described in any one of the above according to the instructions in the program codes.

[0050] The present invention also provides a computer-readable storage medium, which is used to store program codes, and the program codes are used to execute the teaching evaluation method of the bacterial Gram staining experiment as described in any one of the above.

[0051] It can be seen from the above technical solutions that the present invention has the following advantages:

[0052] A teaching evaluation method for bacterial Gram staining experiments is provided. First, the operation images of the experimenter during the saline drop addition operation are collected, and the saline drop addition score is calculated according to the operation images; the temperature of the inoculation loop is collected, the inoculation loop use score is calculated based on the inoculation loop temperature, and the inoculation loop bacteria picking operation of the experimenter is detected and recognized to calculate the inoculation loop bacteria picking score; then, continuous frame extraction recognition is performed on the change of the straight-line distance between the glass slide and the alcohol lamp to calculate the smear and drying score; then, the standardization of the experimenter's Gram staining operation is judged in sequence, the Gram staining score is calculated, and imaging color recognition is performed on the Gram staining result to obtain the microscopy score; finally, the comprehensive teaching score of the experimenter is obtained by comprehensively considering the saline drop addition score, the inoculation loop use score, the inoculation loop bacteria picking score, the smear and drying score, the Gram staining score and the microscopy score. First, by refining the scoring criteria for each link, a unified operation standard scoring criterion is established, making the evaluation results more objective and accurate. At the same time, it also provides a clear improvement direction for students, which helps to promote the standardization and normalization of experimental teaching. Second, combined with multiple intelligent algorithms, through real-time monitoring and intelligent analysis of the experimental process, the tediousness and subjectivity of manual evaluation are reduced, and the automatic scoring and feedback of the experimental operation standardization are realized, improving the evaluation efficiency and accuracy. Brief Description of the Drawings

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0054] Figure 1 It is a schematic structural diagram of a teaching evaluation system for a bacterial Gram staining experiment;

[0055] Figure 2 It is a schematic diagram of the installation position of a camera for a bacterial Gram staining experiment;

[0056] Figure 3 It is a flowchart of the steps of a teaching evaluation method for a bacterial Gram staining experiment;

[0057] Figure 4 It is a schematic diagram of the overall process of a teaching evaluation method for a bacterial Gram staining experiment;

[0058] Figure 5 It is a block diagram of the structure of a teaching evaluation device for a bacterial Gram staining experiment. Detailed Description of the Embodiments

[0059] The embodiments of the present invention provide a teaching evaluation method for a bacterial Gram staining experiment, a teaching evaluation device for a bacterial Gram staining experiment, a camera device, and a storage medium, which are used to solve or partially solve the technical problems that the traditional teaching evaluation method relies on manual observation and recording, has strong subjectivity, low efficiency, and is difficult to comprehensively cover the details of experimental operations.

[0060] In order to make the objectives, features, and advantages of the present invention more obvious and understandable, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0061] As an example, in biomedical education, the bacterial Gram staining experiment is an important part of cultivating students' experimental skills and enhancing their microbiology knowledge. However, the traditional teaching evaluation method mainly relies on manual observation and recording, which has problems such as strong subjectivity, low efficiency, and difficulty in comprehensively covering the details of experimental operations. With the rapid development of computer vision and Internet of Things technologies, it has become particularly important to develop an evaluation system that can automatically identify the key steps of the Gram staining experiment and objectively score the experimental operations.

[0062] Therefore, one of the core invention points of the embodiments of the present invention is: aiming at the deficiencies of the current technology, to provide a teaching evaluation system for bacterial Gram staining experiment operations based on camera recognition and the corresponding teaching evaluation method. First, by refining the scoring criteria for each link, a unified scoring standard for operation specifications is established, making the evaluation results more objective and accurate. At the same time, it also provides clear improvement directions for students, which helps to promote the standardization and regularization of experimental teaching. Secondly, combined with multiple intelligent algorithms, through real-time monitoring and intelligent analysis of the experimental process, the tediousness and subjectivity of manual evaluation are reduced, and the automatic scoring and feedback of the standardization of experimental operations are realized, improving the evaluation efficiency and accuracy. Finally, through the scoring and feedback mechanism, the system can immediately feedback the problems in the experimental operations, provide targeted improvement suggestions for students, which helps students correct mistakes in a timely manner during the experiment and improve their experimental skill level. In addition, students can understand their own operation situations through the system, while teachers can provide more personalized guidance and suggestions for students based on the evaluation results of the system, thereby enhancing the interaction and communication between teachers and students and improving the teaching effect.

[0063] Referring to Figure 1 , a schematic structural diagram of a teaching evaluation system for a bacterial Gram staining experiment provided by an embodiment of the present invention is shown.

[0064] Combined with Figure 1 , the teaching evaluation system 100 for the bacterial Gram staining experiment mainly includes a camera module 101, a data processing and analysis module 102, a scoring module 103, and a user interface module 104 that are connected in sequence.

[0065] Among them, the camera module 101 is responsible for collecting video and temperature data of the experimental scene, and mainly includes a high-definition camera, a temperature-sensing camera, and an electron microscope. Thus, through the setting of the camera module 101, full-process monitoring and recording can be realized. From the start to the end of the experiment, each key step is recorded by the high-definition camera and automatically marked with a time stamp to ensure the traceability of the experimental process.

[0066] The data processing and analysis module 102 mainly performs operations such as preprocessing, feature extraction and recognition on the videos collected by the camera module 101 based on various different intelligent algorithms, and at the same time monitors and analyzes the temperature data in real time. Thus, by developing and integrating advanced image recognition and temperature analysis intelligent algorithms, the real-time, accurate monitoring and evaluation of the experimental operation process are realized.

[0067] The scoring module 103 scores each experimental session according to the preset scoring criteria. Combining the analysis results of the data processing and analysis module 102, the scoring module 103 can automatically record and give the scores of each session, greatly improving the efficiency and accuracy of the evaluation.

[0068] The user interface module 104 is responsible for displaying the scoring results, providing operation guidance and personalized suggestions.

[0069] In addition, the teaching evaluation system 100 may further include a storage module 105, which is used to store structured data as well as picture and video data. The storage module 105 can be further divided into a trainee module (for managing data such as the personal identity information of trainees), a question bank module (for storing various exercise questions related to the experiment), a historical video module (for storing the video recording data collected historically), an experiment reservation module (for storing experiment reservation related information for front-end calling), etc.

[0070] Thus, in the embodiment of the present invention, by combining a high-definition camera, a temperature-sensitive camera and an electron microscope, and combining image processing, temperature monitoring and data analysis technologies, a complete experimental operation specification scoring system is constructed. Through the innovation of the technical architecture, the system can monitor all aspects of the experimental operation in real time and comprehensively, and accurately evaluate the standardization of the operation.

[0071] Exemplarily, the schematic diagram of the installation position of the camera for the bacterial Gram staining experiment is as Figure 2 shown. Among them, through the combined recognition of a high-definition camera, a temperature-sensitive camera and an electron microscope, the camera can accurately capture the details of the experimental operation at a height of 1.5 meters and a shooting angle of 60 degrees, while reducing light interference and field of view blind spots.

[0072] Referring to Figure 3 , the flowchart of the steps of a teaching evaluation method for a bacterial Gram staining experiment provided by an embodiment of the present invention is shown, which may specifically include the following steps:

[0073] Step 301, collect the operation images of the experimental personnel when performing the normal saline dropping operation, and calculate the normal saline dropping score according to the operation images;

[0074] Before the formal start of the experiment, the teaching evaluation system captures the facial images of the experimental personnel through a high-definition camera and compares them with the pre-stored personnel information to complete identity verification. Thus, in addition to the comparison of the personnel information pre-entered into the system, the accuracy and security of identity verification are improved by adding facial recognition means.

[0075] After successful identity verification, the experimental personnel start the bacterial Gram staining experiment operation, and the system monitors the experimental personnel in real time and analyzes the experimental operation process in real time, and obtains the score of the corresponding step based on the analysis result.

[0076] First is the operation process of dropping sterile physiological saline. In some embodiments, the process of calculating the score of dropping physiological saline according to the operation image can be realized by performing the following sub-steps S01 to S04:

[0077] Step S01: First, gray-scale the operation image, then filter and denoise it, and extract the edge information of the glass slide and the physiological saline drop in the processed image through an edge detection algorithm;

[0078] The process of dropping physiological saline is collected in real time through a high-definition camera, and the collected image is gray-scaled, filtered and denoised, and then the Canny edge detection algorithm is used to extract the edge information of the glass slide and the physiological saline drop to calculate the water drop position and the water drop diameter, ensuring that the physiological saline is dropped in the middle of the glass slide, the dropped amount is appropriate and there is no leakage.

[0079] Step S02: According to the edge information, calculate the edge distance between the physiological saline drop and the glass slide, and the water drop diameter of the physiological saline drop on the glass slide;

[0080] Step S03: Calculate the score of appropriate water drop amount according to the water drop diameter, and calculate the score of water drop position according to the edge distance;

[0081] Specifically, the calculation formula of the score of appropriate water drop amount is as follows:

[0082]

[0083] The calculation formula of the water drop position score is as follows:

[0084]

[0085] Among them, is the water drop diameter of the physiological saline drop on the glass slide; is the edge distance between the edge of the physiological saline drop and the edge of the glass slide.

[0086] That is, when the water droplet diameter is less than 5 mm (millimeter), the score for moderate water droplet amount is 2 points. When the water droplet diameter is greater than or equal to 5 mm (by default, less than the side length of the glass slide), the score for moderate water droplet amount is 0 points. When the edge distance is within the range of 8 mm to 12 mm, the score for water droplet position is 2 points. When the edge distance is outside the range of 8 mm to 12 mm, the score for water droplet position is 0 points.

[0087] Step S04: Integrate the score for moderate water droplets and the score for water droplet position as the score for normal saline dropping.

[0088] Take the sum of the score for moderate water droplets and the score for water droplet position as the score for normal saline dropping.

[0089] Thus, in the process of dropping normal saline, by refining the scoring criteria, such as the precise range of the dropping position of normal saline, the size quantization standard (such as the diameter range), and the specific deduction rules for leakage or excess, the scoring of this process becomes more unified and objective.

[0090] Step 302, collect the temperature of the inoculation loop, calculate the score for using the inoculation loop based on the temperature of the inoculation loop, and detect and identify the operation of picking bacteria with the inoculation loop by the experimenter, and calculate the score for picking bacteria with the inoculation loop;

[0091] Monitor the temperature of the inoculation loop through a temperature-sensing camera to ensure that it reaches 900 °C (Celsius) during burning and pick bacteria after it cools below 40 °C. Thus, the temperature of the inoculation loop referred to in this step includes the highest burning temperature during the burning of the inoculation loop and the lowest picking temperature before picking bacteria with the inoculation loop.

[0092] In some embodiments, the process of calculating the score for using the inoculation loop based on the temperature of the inoculation loop can be implemented by performing the following sub-steps S11 to S13:

[0093] Step S11: Compare the highest burning temperature with a preset burning temperature threshold, and obtain the burning sterilization score according to the comparison result of the burning temperature;

[0094] Specifically, the calculation formula for the burning sterilization score of the inoculation loop is as follows:

[0095]

[0096] Wherein, is the highest temperature during the burning of the inoculation loop (the highest burning temperature). That is, when the highest burning temperature is greater than or equal to 900 °C, it indicates that the inoculation loop is thoroughly burned, and the burning sterilization score is 2 points. When the highest burning temperature does not reach 900 °C, it indicates that the inoculation loop is not thoroughly burned, and the burning sterilization score is 0 points.

[0097] Step S12: Compare the lowest bacteria sampling temperature with the preset bacteria sampling temperature threshold, and obtain the cooling score before bacteria sampling according to the comparison result of the bacteria sampling temperature;

[0098] The calculation formula for the cooling score before bacteria sampling of the inoculation loop is as follows:

[0099]

[0100] Wherein, is the lowest temperature before bacteria sampling of the inoculation loop (the lowest bacteria sampling temperature). That is, when the lowest bacteria sampling temperature is less than 40°C, it indicates that the experimenter strictly follows the operation process of cooling the inoculation loop before bacteria sampling, and the cooling score before bacteria sampling is counted as 2 points. When the lowest bacteria sampling temperature is greater than 40°C, it indicates that the experimenter does not strictly follow the operation process of cooling the inoculation loop before bacteria sampling, and the cooling score before bacteria sampling is counted as 0 points.

[0101] Step S13: Integrate the flaming sterilization score and the cooling score before bacteria sampling as the usage score of the inoculation loop.

[0102] Take the sum of the flaming sterilization score and the cooling score before bacteria sampling as the usage score of the inoculation loop.

[0103] For the bacteria sampling process of the inoculation loop, in some embodiments, the process of detecting and identifying the experimenter's bacteria sampling operation of the inoculation loop and calculating the bacteria sampling score of the inoculation loop can be implemented by performing the following sub-steps S21 to S25:

[0104] Step S21: When it is detected that the experimenter enters the bacteria sampling operation of the inoculation loop, use the gesture recognition algorithm to recognize the degree of finger bending, palm orientation, arm movement of the experimenter, and the distance between both hands and the culture dish;

[0105] Step S22: Through target detection and identification, identify the positions of the culture dish and the alcohol lamp on the experimental table, and calculate the straight-line distance between the culture dish and the alcohol lamp;

[0106] Step S23: Calculate the culture dish-alcohol lamp distance score according to the straight-line distance between the culture dish and the alcohol lamp;

[0107] Step S23 mainly judges whether the operation is carried out within the sterile area of the alcohol lamp by the distance between the culture dish and the alcohol lamp.

[0108] The calculation formula for the culture dish-alcohol lamp distance score in the bacteria sampling link of the inoculation loop is as follows:

[0109]

[0110] Wherein, The straight-line distance between the petri dish and the alcohol lamp. That is, when the straight-line distance between the petri dish and the alcohol lamp is within the range of 40 cm (centimeters) to 65 cm (the optimal distance for reference is 50 cm), it indicates that the experimenter strictly performs operations within the sterile area, and the score for the petri dish-alcohol lamp distance is 2 points. When the straight-line distance between the petri dish and the alcohol lamp is not within the range of 40 cm to 65 cm, it indicates that the experimenter does not strictly perform operations within the sterile area, and the score for the petri dish-alcohol lamp distance is 0 points.

[0111] Step S24: According to the degree of finger bending, palm orientation, arm movement of the experimenter, and the distance between the hands and the petri dish, determine whether the experimenter opens the petri dish with one hand to obtain a one-handed operation score;

[0112] The system can also identify the degree of finger bending, palm orientation, and arm movement of the experimenter through a gesture recognition algorithm, as well as the distances between the left and right hands and the petri dish, to determine whether the experimenter opens the petri dish with one hand. When it is determined that the experimenter opens the petri dish with one hand, the one-handed operation score is 6 points. When it is determined that the experimenter opens the petri dish with both hands, the one-handed operation score is 0 points.

[0113] Step S25: Integrate the score for the petri dish-alcohol lamp distance and the one-handed operation score as the score for picking bacteria with the inoculation loop.

[0114] The sum of the score for the petri dish-alcohol lamp distance and the one-handed operation score is used as the score for picking bacteria with the inoculation loop.

[0115] In another alternative embodiment, for the entire usage process of the inoculation loop, in addition to considering the sterilization by burning score and the cooling score before picking bacteria as the score for using the inoculation loop, and considering the score for the petri dish-alcohol lamp distance and the one-handed operation score as the score for picking bacteria with the inoculation loop, it is also possible to perform image detection and recognition on the culture medium according to target detection when the experimenter picks a single colony, and judge whether the culture medium is scratched based on the image detection result to obtain a score for the culture medium not being scratched. For example, when it is detected that the culture medium is not scratched, an additional 2 points are counted, and when it is detected that the culture medium is scratched, no additional points are counted.

[0116] Furthermore, when the experimenter burns the inoculation loop after smearing and places it back in place, the system can detect the temperature of the inoculation loop to obtain a temperature value with a certain time delay from the highest burning temperature. The temperature obtained at this time may be slightly lower than the highest burning temperature, but if this temperature can also reach 900 °C, it further verifies that the inoculation loop is fully burned, and an additional 2 points can be added at this time. When this temperature does not reach 900 °C, no additional points are counted.

[0117] Thus, in the process of using the inoculation loop, by increasing the accurate measurement of the burning time of the inoculation loop (such as reaching 900 °C and maintaining for a certain period of time), the strictness of aseptic operation is ensured.

[0118] Step 303: By continuously extracting frames to identify the change in the linear distance between the slide and the alcohol lamp, calculate the smear and drying scores.

[0119] For the smear and drying process, in some embodiments, the process of calculating the smear and drying scores by continuously extracting frames to identify the change in the linear distance between the slide and the alcohol lamp can be implemented by performing the following sub-steps S31 to S33:

[0120] Step S31: When it is detected that the experimenter has completed the smear operation, through target detection recognition, identify the coated area of the slide and determine whether the coated area is evenly smeared to obtain the smear evenness score.

[0121] Exemplarily, when the coated area is evenly smeared (such as the same color depth and no blank area), the smear evenness score is counted as 2 points. When the coated area is unevenly smeared, the smear evenness score is counted as 0 points.

[0122] Step S32: Through real-time tracking detection, identify whether the experimenter is holding the alcohol lamp and place the alcohol lamp under the slide and swing it 3 times at a pendulum speed.

[0123] Step S33: When the number of swings is detected to be 3 times, identify the change in the linear distance between the slide and the alcohol lamp during the swinging process by continuous frame extraction. Based on the recognition result of the linear distance change, calculate the drying action error score, and integrate the smear evenness score and the drying action error score as the smear and drying score. When the number of swings is detected to be not 3 times, directly count the smear evenness score as the smear and drying score.

[0124] Specifically, the calculation formula for the drying action error score in the smear and drying process is as follows:

[0125] E =

[0126]

[0127] Where represents the distance between the slide and the fixed reference object; represents the distance between the alcohol lamp and the fixed reference object; E represents the sum of the distance errors between the slide and the alcohol lamp during 3 swings; Indicates the judgment scores for the sum of the distance errors between the glass slide and the alcohol lamp within different ranges. That is, when the sum of the distance errors is less than 15 cm, the drying action error score is counted as 4 points. When the sum of the distance errors is within the range of 15 cm to 30 cm, the drying action error score is counted as 2 points. When the sum of the distance errors is other values, the drying action error score is counted as 0 points.

[0128] Thus, in the smearing and drying steps, by clarifying the quantitative standards for smear uniformity (such as the consistency of color depth and no blank areas), strictly controlling the drying action, and precisely controlling the heating temperature range of the glass slide, the consistency of experimental conditions is ensured.

[0129] Step 304: Regularly judge the Gram staining operation of the experimenter in sequence, calculate the Gram staining score, and perform imaging color recognition on the Gram staining result to obtain the microscopy score;

[0130] In this step, the steps of primary staining, mordanting, decolorization, counterstaining, drying, etc. are monitored throughout by a high-definition camera to ensure the standard progress of the staining process.

[0131] Focusing on the key steps of the bacterial Gram staining experiment, the steps of the Gram staining operation can at least include primary staining, mordanting, decolorization, and counterstaining in sequence. During the Gram staining experiment, the system identifies the bottle positions, styles, and cap changes of crystal violet stain, Lugol's iodine solution, 95% ethanol, and safranin stain through a high-definition camera to identify the Gram staining steps and staining time, judge whether the glass slide leaks liquid and whether the staining time meets the time requirements, and identify whether there are residual water droplets on the glass slide through a water stain recognition algorithm.

[0132] In some embodiments, the process of regularly judging the Gram staining operation of the experimenter in sequence and calculating the Gram staining score can be implemented by executing the following sub-steps S41 to S45:

[0133] Step S41: Through target detection recognition, identify the bottle positions, styles, and cap changes of crystal violet stain, Lugol's iodine solution, 95% ethanol, and safranin stain, and judge whether the experimenter performs the operations of primary staining, mordanting, decolorization, and counterstaining in sequence;

[0134] Step S42: If so, obtain the start time of the primary staining operation, the end time of the primary staining operation, the start time of the mordanting operation, the end time of the mordanting operation, the start time of the decolorization operation, the end time of the decolorization operation, the start time of the counterstaining operation, and the end time of the counterstaining operation;

[0135] Step S43: Calculate the execution score of the primary dyeing operation based on the start time and end time of the primary dyeing operation, calculate the execution score of the mordanting operation based on the start time and end time of the mordanting operation, calculate the execution score of the decolorization operation based on the start time and end time of the decolorization operation, and calculate the execution score of the re-dyeing operation based on the start time and end time of the re-dyeing operation;

[0136] The execution scores of the primary dyeing operation, the mordanting operation, and the re-dyeing operation are all calculated according to the following scoring formula for a dyeing time of more than 10s:

[0137]

[0138] Specifically, the calculation formula for the execution score of the primary dyeing operation is:

[0139]

[0140] represents the primary dyeing operation time; corresponds to the start time of the dyeing operation captured by the camera, corresponds to the end time of the captured dyeing operation. That is, when the execution score of the primary dyeing operation is counted as 0 points. When the execution score of the primary dyeing operation is counted as 1 point. Additionally, if no liquid leakage is detected on the slide during the primary dyeing operation, an additional 1 point can be counted.

[0141] The calculation formula for the execution score of the mordanting operation is:

[0142]

[0143] represents the mordanting operation time. That is, when the execution score of the mordanting operation is counted as 0 points. When the execution score of the mordanting operation is counted as 1 point. Additionally, if no liquid leakage is detected on the slide during the mordanting operation, an additional 1 point can be counted.

[0144] The calculation formula for the execution score of the re-dyeing operation is:

[0145]

[0146] represents the re-dyeing operation time. That is, when the execution score of the re-dyeing operation is counted as 0 points. When the execution score of the re-dyeing operation is counted as 1 point. Additionally, if no liquid leakage is detected on the slide during the re-dyeing operation, an additional 1 point can be counted.

[0147] The execution score of the decolorization operation is calculated according to the score formula with a staining time requirement of 10 - 20 seconds as follows:

[0148]

[0149] That is, the calculation formula for the execution score of the decolorization operation is:

[0150]

[0151] represents the decolorization operation time. That is, when the execution score of the decolorization operation is counted as 1 point. When is other value, the execution score of the decolorization operation is counted as 0 point. Additionally, if it is detected that there is no liquid leakage on the slide during the decolorization operation, an additional 1 point can be counted.

[0152] Step S44: Identify whether there are residual water droplets on the slide through a water stain recognition algorithm to obtain a residual water droplet judgment score;

[0153] When it is identified that there are residual water droplets on the slide, the residual water droplet judgment score is 1, and when there are no residual water droplets, the residual water droplet judgment score is 0.

[0154] Step S45: Calculate the Gram staining score based on the execution scores of the primary staining operation, mordanting operation, decolorization operation, counterstaining operation, and residual water droplet judgment score, in combination with the step execution sequence factor.

[0155] Specifically, the calculation formula for the Gram staining score is as follows:

[0156]

[0157] represents the sequence factor; represents the residual water droplet judgment score.

[0158] In addition, the Gram staining may also include a drying step. In the drying step, when it is detected that the distance between the slide and the alcohol lamp is within an appropriate range (such as 50 cm), an additional 2 points can be counted. The distance judgment for this step can refer to the drying step in the previous smear and drying link, which will not be elaborated here.

[0159] Thus, in the Gram staining process, taking the staining time, whether the slide leaks liquid, etc. as scoring indicators, by refining the scoring criteria for each execution step (primary staining, mordanting, decolorization, counterstaining, drying), the accuracy of the staining effect and the comprehensiveness considered in teaching evaluation are ensured.

[0160] For the microscopy inspection step, in some embodiments, the process of performing imaging color recognition on the Gram staining result to obtain the microscopy inspection score can be achieved by executing the following sub-steps S51 to S53:

[0161] Step S51: After completing the Gram staining experiment, extract frames from the image shown on the electron microscope to obtain the Gram staining image;

[0162] Step S52: Perform imaging color recognition on the Gram staining image, and make a staining comparison judgment based on the imaging color recognition result to obtain the color temperature value detection score, the staining judgment score, the cell distance score, and the color type score respectively;

[0163] Exemplarily, perform color temperature detection on the imaging color recognition result. When the detected color temperature value is between 3000 - 5000K (Kelvin), the color temperature value detection score is counted as 4 points. Make a color judgment on the staining result of the imaging color recognition result, and compare the staining result with the standard atlas to see if it conforms to the preset bacterial species (purple for Gram-positive, red for Gram-negative). When it conforms to the preset bacterial species, the staining judgment score is counted as 30 points. Perform cell density recognition and judgment on the imaging color recognition result. When the cells are within the normal range (i.e., there is no overcrowding or over- sparseness), the cell distance score is counted as 6 points. Perform color type analysis on the imaging color recognition result to determine if there is a color type other than the staining color. When there is no other color, the color type score is counted as 4 points.

[0164] Step S53: Integrate the color temperature value detection score, the staining judgment score, the cell distance score, and the color type score as the microscopy inspection score.

[0165] Take the sum of the color temperature value detection score, the staining judgment score, the cell distance score, and the color type score as the microscopy inspection score.

[0166] In addition, the person in charge of the laboratory can also manually view the video to evaluate whether the experimenter uses the microscope correctly and add or subtract points according to the actual situation. By combining the automated process with appropriate manual judgment, a more comprehensive evaluation result can be obtained.

[0167] Thus, in the microscopy inspection step, by developing an automatic analysis technology for microscope images, not only can the quality of the staining result be automatically recognized and evaluated, such as bacterial morphology, color depth, etc., but also the correct use of the microscope can be judged by combining manual means, making the teaching evaluation result more comprehensive and accurate.

[0168] Step 305, obtain the comprehensive teaching score of the experimenter by comprehensively considering the saline drop addition score, the inoculation loop use score, the inoculation loop bacteria collection score, the smear and drying score, the Gram staining score, and the microscopy inspection score.

[0169] By synthesizing the scores of each link, the final experimental operation specification score (i.e., the comprehensive teaching score of the experimental personnel) can be given. The system can also conduct in-depth analysis on the obtained scoring results based on intelligent algorithms and provide improvement suggestions.

[0170] In the embodiment of the present invention, in combination with the bacterial Gram staining experiment operation teaching evaluation system based on camera recognition introduced in the previous embodiments, a corresponding teaching evaluation method is provided. First, by refining the scoring criteria for each link, a unified operation specification scoring standard is established, making the evaluation results more objective and accurate. At the same time, it also provides a clear improvement direction for students, which helps to promote the standardization and regularization of experimental teaching. Secondly, in combination with a variety of intelligent algorithms, through real-time monitoring and intelligent analysis of the experimental process, the cumbersome and subjective nature of manual evaluation is reduced, and automatic scoring and feedback on the standardization of experimental operations are realized, improving the evaluation efficiency and accuracy. Finally, through the scoring and feedback mechanism, the system can immediately feedback the problems in the experimental operation, provide targeted improvement suggestions for students, help students correct mistakes in time during the experiment, and improve their experimental skill level. In addition, students can understand their own operation conditions through the system, while teachers can provide more personalized guidance and suggestions for students based on the evaluation results of the system, thereby enhancing the interaction and communication between teachers and students and improving the teaching effect.

[0171] For better illustration, refer to Figure 4 , which shows the overall flow schematic diagram of a teaching evaluation method for a bacterial Gram staining experiment provided by an embodiment of the present invention. It should be noted that this embodiment only briefly describes the general process of the teaching evaluation of the bacterial Gram staining experiment. The specific implementation process of each step can be understood by referring to the relevant content in the previous embodiments and will not be elaborated here. It can be understood that the present invention places no restrictions on this.

[0172] Step 401: Authenticate the identity of the experimental personnel through facial information comparison. After the identity authentication passes, enter the teaching evaluation process of the bacterial Gram staining experiment;

[0173] Step 402: Collect the operation images of the experimental personnel during the operation of dropping physiological saline, and calculate the water droplet appropriateness score and the water droplet position score based on the operation images to obtain the physiological saline dropping score;

[0174] Step 403: Collect the temperature of the inoculation loop, calculate the sterilization by burning score and the cooling score before picking bacteria based on the temperature of the inoculation loop to obtain the inoculation loop usage score, and detect and identify the inoculation loop bacteria picking operation of the experimental personnel, calculate the culture dish - alcohol lamp distance score and the single-handed operation score to obtain the inoculation loop bacteria picking score;

[0175] Step 404: Calculate the smear uniformity score and the drying action error score by continuously extracting frames and identifying the change in the linear distance between the slide and the alcohol lamp, and obtain the smear and drying scores;

[0176] Step 405: Judge the standardization of the Gram staining operation of the experimenter in sequence, calculate the primary staining operation execution score, the mordanting operation execution score, the decolorization operation execution score, the counterstaining operation execution score and the residual water droplet judgment score, and obtain the Gram staining score;

[0177] Step 406: Identify the imaging color of the Gram staining result, calculate the color temperature value detection score, the staining judgment score, the cell distance score and the color type score, and obtain the microscopy score;

[0178] Step 407: Synthesize the saline drop addition score, the inoculating loop usage score, the inoculating loop bacteria picking score, the smear and drying score, the Gram staining score and the microscopy score to obtain the comprehensive teaching score of the experimenter.

[0179] Refer to Figure 5 , which shows the structural block diagram of a teaching evaluation device for a bacterial Gram staining experiment provided by an embodiment of the present invention, and specifically may include:

[0180] A saline drop addition score calculation unit 501, configured to collect operation images of the experimenter during the saline drop addition operation, and calculate the saline drop addition score according to the operation images;

[0181] An inoculating loop operation score calculation unit 502, configured to collect the temperature of the inoculating loop, calculate the inoculating loop usage score based on the temperature of the inoculating loop, and detect and identify the inoculating loop bacteria picking operation of the experimenter, and calculate the inoculating loop bacteria picking score;

[0182] A smear and drying score calculation unit 503, configured to calculate the smear and drying score by continuously extracting frames and identifying the change in the linear distance between the slide and the alcohol lamp;

[0183] A Gram staining score calculation unit 504, configured to judge the standardization of the Gram staining operation of the experimenter in sequence, calculate the Gram staining score, and identify the imaging color of the Gram staining result to obtain the microscopy score;

[0184] A comprehensive teaching score calculation unit 505, configured to synthesize the saline drop addition score, the inoculating loop usage score, the inoculating loop bacteria picking score, the smear and drying score, the Gram staining score and the microscopy score to obtain the comprehensive teaching score of the experimenter.

[0185] In an optional embodiment, the saline drop addition score calculation unit 501 includes:

[0186] An edge information extraction unit, which is used to grayscale the operation image first, then perform filtering and denoising, and extract the edge information of the glass slide and the saline drop in the processed image through an edge detection algorithm;

[0187] An edge information calculation unit, which is used to calculate the edge distance between the saline drop and the glass slide and the water drop diameter of the saline drop on the glass slide according to the edge information;

[0188] A water drop related score calculation unit, which is used to calculate the water drop moderation score according to the water drop diameter and calculate the water drop position score according to the edge distance;

[0189] A saline drop addition score integration unit, which is used to integrate the water drop moderation score and the water drop position score as the saline drop addition score.

[0190] In an alternative embodiment, the inoculation loop temperature includes the highest burning temperature during the burning of the inoculation loop and the lowest picking temperature before picking bacteria with the inoculation loop; the inoculation loop operation score calculation unit 502 includes:

[0191] A burning sterilization score calculation unit, which is used to compare the highest burning temperature with a preset burning temperature threshold and obtain a burning sterilization score according to the burning temperature comparison result;

[0192] A pre-picking cooling score calculation unit, which is used to compare the lowest picking temperature with a preset picking temperature threshold and obtain a pre-picking cooling score according to the picking temperature comparison result;

[0193] An inoculation loop usage score integration unit, which is used to integrate the burning sterilization score and the pre-picking cooling score as the inoculation loop usage score.

[0194] In an alternative embodiment, the inoculation loop operation score calculation unit 502 includes:

[0195] A gesture recognition unit, which is used to recognize the finger bending degree, palm orientation, arm movement action and the distance between the hands and the culture dish of the experimenter through a gesture recognition algorithm when it detects that the experimenter enters the operation of picking bacteria with the inoculation loop;

[0196] A straight-line distance calculation unit, which is used to recognize the positions of the culture dish and the alcohol lamp on the experimental table through target detection and calculate the straight-line distance between the culture dish and the alcohol lamp;

[0197] A culture dish-alcohol lamp distance score calculation unit, which is used to calculate a culture dish-alcohol lamp distance score according to the straight-line distance between the culture dish and the alcohol lamp;

[0198] A single-handed operation score calculation unit, configured to determine whether the experimenter opens the petri dish with one hand according to the finger bending degree, palm orientation, arm movement of the experimenter, and the distance between both hands and the petri dish, and obtain a single-handed operation score;

[0199] An inoculation loop bacteria-taking score integration unit, configured to integrate the petri dish-alcohol lamp distance score and the single-handed operation score as the inoculation loop bacteria-taking score.

[0200] In an optional embodiment, the smear and drying score calculation unit 503 includes:

[0201] A smear uniformity score calculation unit, configured to, when detecting that the experimenter finishes the smear operation, identify the coated area of the slide through target detection, and determine whether the coated area is evenly smeared, so as to obtain a smear uniformity score;

[0202] A swing times calculation unit, configured to, through real-time tracking detection, identify whether the experimenter holds the alcohol lamp and places the alcohol lamp under the slide and swings it 3 times at the pendulum speed;

[0203] A drying action error score calculation unit, configured to, when detecting that the swing times is 3 times, identify the change in the straight-line distance between the slide and the alcohol lamp during the swing through continuous frame extraction, calculate a drying action error score based on the straight-line distance change recognition result, and integrate the smear uniformity score and the drying action error score as the smear and drying score;

[0204] A smear and drying score integration subunit, configured to, when detecting that the swing times is not 3 times, directly count the smear uniformity score as the smear and drying score.

[0205] In an optional embodiment, the steps of the Gram staining operation at least include primary staining, mordanting, decolorization, and counterstaining in sequence; the Gram staining score calculation unit 504 includes:

[0206] A step execution order judgment unit, configured to, through target detection, identify the bottle body positions, styles, and cap change situations of crystal violet stain, Lugol's iodine solution, 95% ethanol, and safranin stain, and determine whether the experimenter performs the primary staining, mordanting, decolorization, and counterstaining operations in sequence;

[0207] A staining operation time information acquisition unit, configured to acquire the start time of the primary staining operation, the end time of the primary staining operation, the start time of the mordanting operation, the end time of the mordanting operation, the start time of the decolorization operation, the end time of the decolorization operation, the start time of the counterstaining operation, and the end time of the counterstaining operation;

[0208] A dyeing operation execution score calculation unit for calculating the primary dyeing operation execution score according to the start time and end time of the primary dyeing operation, calculating the mordanting operation execution score according to the start time and end time of the mordanting operation, calculating the decolorization operation execution score according to the start time and end time of the decolorization operation, and calculating the restaining operation execution score according to the start time and end time of the restaining operation;

[0209] A residual water droplet judgment score calculation unit for identifying whether there are residual water droplets on the glass slide through a water stain recognition algorithm to obtain a residual water droplet judgment score;

[0210] A Gram staining score calculation subunit for calculating the Gram staining score according to the primary dyeing operation execution score, the mordanting operation execution score, the decolorization operation execution score, the restaining operation execution score and the residual water droplet judgment score, in combination with the step execution sequence factor.

[0211] In an alternative embodiment, the Gram staining score calculation unit 504 includes:

[0212] A Gram staining image extraction unit for extracting frames from the image shown by the electron microscope after completing the Gram staining experiment to obtain a Gram staining image;

[0213] A staining comparison judgment unit for performing imaging color recognition on the Gram staining image, making a staining comparison judgment according to the imaging color recognition result, and obtaining a color temperature value detection score, a staining judgment score, a cell distance score and a color type score respectively;

[0214] A microscopic examination score integration unit for integrating the color temperature value detection score, the staining judgment score, the cell distance score and the color type score as the microscopic examination score.

[0215] For the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple. For related parts, refer to the partial description of the foregoing method embodiment.

[0216] An embodiment of the present invention further provides a camera device, which includes a processor and a memory:

[0217] The memory is used to store program code and transmit the program code to the processor;

[0218] The processor is used to execute the teaching evaluation method for the bacterial Gram staining experiment according to any embodiment of the present invention according to the instructions in the program code.

[0219] An embodiment of the present invention also provides a computer-readable storage medium, which is used to store program code, and the program code is used to execute the teaching evaluation method for the bacterial Gram staining experiment in any embodiment of the present invention.

[0220] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the foregoing method embodiments, and will not be described herein again.

[0221] In several embodiments provided by the present invention, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling, direct coupling, or communication connection can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be in electrical, mechanical, or other forms.

[0222] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0223] In addition, each functional unit in various embodiments of the present invention can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0224] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs.

[0225] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of various embodiments of the present invention.

Claims

1. A teaching evaluation method for a bacterial Gram staining experiment, characterized in that: include: collecting operation images of the experimenter when performing the physiological saline dripping operation, and calculating the physiological saline dripping score according to the operation images; Collecting the temperature of the inoculation loop, calculating the inoculation loop usage score based on the inoculation loop temperature, detecting and identifying the inoculation loop bacteria extraction operation of the experimenter, and calculating the inoculation loop bacteria extraction score; The smear and drying scores were calculated by continuously sampling frames to identify the change in the linear distance between the slide and the alcohol lamp. Conducting normative judgment on the Gram staining operation of the experimenter in order, calculating the Gram staining score, and performing imaging color recognition on the Gram staining result to obtain the microscopic examination score; The comprehensive teaching score of the experimenter was obtained by combining the physiological saline dripping score, the inoculation loop usage score, the inoculation loop bacteria extraction score, the smear and drying score, the Gram staining score and the microscopic examination score.

2. The teaching evaluation method according to claim 1, characterized in that: The calculating the physiological saline dripping score according to the operation image comprises: The operation image is first grayed out, and then filtered and denoised, and edge information of the glass slide and the physiological saline drop in the processed image is extracted by an edge detection algorithm; Calculating the distance between the edge of the physiological saline drop and the glass slide, and the diameter of the physiological saline drop on the glass slide according to the edge information; Calculating a water droplet moderate score according to the water droplet diameter, and calculating a water droplet position score according to the edge distance; The water droplet moderate score and the water droplet position score are integrated to obtain the saline dripping score.

3. The teaching evaluation method according to claim 1, characterized in that: The inoculation loop temperature includes the highest burning temperature during the burning of the inoculation loop and the lowest temperature before the inoculation loop is used to take bacteria; The calculating the inoculation loop usage score based on the inoculation loop temperature comprises: Comparing the maximum burning temperature with a preset burning temperature threshold, and obtaining a burning sterilization score according to the burning temperature comparison result; The minimum bacteria collection temperature is compared with a preset bacteria collection temperature threshold, and a cooling score before bacteria collection is obtained according to the comparison result of the bacteria collection temperature; The burning sterilization score and the cooling score before taking out bacteria are integrated to serve as the inoculation loop usage score.

4. The teaching evaluation method according to claim 3, characterized in that: The detecting and identifying the inoculation loop bacteria extraction operation of the experimenter and calculating the inoculation loop bacteria extraction score include: When it is detected that the experimenter enters the inoculation loop to take out bacteria, the gesture recognition algorithm is used to identify the experimenter's finger bending degree, palm direction, arm movement, and the distance between both hands and the culture dish; By target detection and recognition, the positions of the culture dish and the alcohol lamp on the laboratory table are identified, and the straight-line distance between the culture dish and the alcohol lamp is calculated; Calculate the culture dish-alcohol lamp distance score according to the straight-line distance between the culture dish and the alcohol lamp; According to the experimenter's finger bending degree, palm direction, arm movement and the distance between both hands and the culture dish, it is judged whether the experimenter uses one hand to open the culture dish, and a one-hand operation score is obtained; The culture dish-alcohol lamp distance score and the one-handed operation score were integrated to form the inoculation loop bacteria collection score.

5. The teaching evaluation method according to claim 1, characterized in that: The method of continuously extracting frames to identify the change in the linear distance between the glass slide and the alcohol lamp and calculating the smear and drying scores includes: When it is detected that the experimenter has finished the smear operation, the coating area of ​​the slide is identified through target detection and recognition, and it is determined whether the coating area is evenly smeared to obtain a smear uniformity score; Through real-time tracking detection, it is identified whether the experimenter is holding an alcohol lamp, and the alcohol lamp is placed under the glass slide and swung at a pendulum speed for 3 times; When the number of swings is detected to be 3, the linear distance change between the glass slide and the alcohol lamp during the swinging process is identified by continuous frame extraction, and the drying action error score is calculated based on the linear distance change identification result, and the smear uniformity score and the drying action error score are integrated as the smear and drying score; When the number of swings detected is not 3, the smear uniformity score is directly counted as the smear and drying score.

6. The teaching evaluation method according to claim 1, characterized in that: The steps of the Gram staining operation include at least primary staining, mordanting, decolorization and re-staining in order; the Gram staining operation of the experimenter is judged in order to be normative and the Gram staining score is calculated, including: Through target detection and recognition, the position, style and cap changes of the bottles of crystal violet dye, Lugol's iodine solution, 95% ethanol and safranin dye are identified to determine whether the experimenter performs the primary dyeing, mordanting, decolorization and re-dyeing operations in sequence; If yes, then obtain the initial dyeing operation start time, the initial dyeing operation end time, the mordanting operation start time, the mordanting operation end time, the bleaching operation start time, the bleaching operation end time, the re-dyeing operation start time and the re-dyeing operation end time; Calculate the execution score of the primary dyeing operation according to the start time and the end time of the primary dyeing operation, calculate the execution score of the mordanting operation according to the start time and the end time of the mordanting operation, calculate the execution score of the bleaching operation according to the start time and the end time of the bleaching operation, and calculate the execution score of the re-dyeing operation according to the start time and the end time of the re-dyeing operation; Using a water mark recognition algorithm to identify whether there are residual water drops on the slide, and obtain a residual water drop judgment score; The Gram staining score is calculated based on the primary dyeing operation execution score, the mordanting operation execution score, the decolorization operation execution score, the re-dyeing operation execution score and the residual water drop judgment score, combined with the step execution order factor.

7. The teaching evaluation method according to claim 1, characterized in that: The method of performing imaging color recognition on the Gram staining result to obtain a microscopic examination score includes: After completing the Gram staining experiment, the screen displayed by the electron microscope is framed to obtain the Gram staining image; Performing imaging color recognition on the Gram staining image, performing staining comparison judgment according to the imaging color recognition result, and obtaining a color temperature value detection score, a staining judgment score, a cell distance score, and a color type score respectively; The color temperature value detection score, the staining judgment score, the cell distance score and the color type score are integrated as the microscopy score.

8. A teaching and evaluation device for bacterial Gram staining experiment, characterized in that: include: A physiological saline dripping score calculation unit, used to collect an operation image of the experimenter when performing the physiological saline dripping operation, and calculate the physiological saline dripping score according to the operation image; An inoculation loop operation score calculation unit, used to collect the inoculation loop temperature, calculate the inoculation loop usage score based on the inoculation loop temperature, detect and identify the inoculation loop bacteria extraction operation of the experimenter, and calculate the inoculation loop bacteria extraction score; A smear and drying score calculation unit is used to calculate the smear and drying scores by continuously sampling frames to identify the change in the linear distance between the glass slide and the alcohol lamp; A Gram staining score calculation unit, used to perform a normative judgment on the Gram staining operation of the experimenter in sequence, calculate the Gram staining score, and perform imaging color recognition on the Gram staining result to obtain a microscopic examination score; The comprehensive teaching score calculation unit is used to comprehensively calculate the physiological saline dripping score, the inoculation loop usage score, the inoculation loop bacteria extraction score, the smear and drying score, the Gram staining score and the microscopic examination score to obtain the comprehensive teaching score of the experimenter.

9. A camera device, characterized in that: The device comprises a processor and a memory: The memory is used to store program code and transmit the program code to the processor; The processor is used to execute the teaching and evaluation method for the bacterial Gram staining experiment according to any one of claims 1 to 7 according to the instructions in the program code.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store program codes, and the program codes are used to execute the teaching and evaluation method for bacterial Gram staining experiments according to any one of claims 1 to 7.

Images