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An internship is a period of work experience offered by an organization for a limited period of time. Once confined to medical graduates, internship is used practice for a wide range of placements in businesses, non-profit organizations and government agencies.
Typology: Schemes and Mind Maps
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Jnana Sangama, Belgaum-59001 4
Submitted in the partial fulfillment for the requirement of 7 th^ Semester BACHELOR OF ENGINEERING IN COMPUTER SCIENCE AND ENGINEERING Submitted By: ABHIJIT D (1BC19CS001) ROHIT KUMAR (1BC19CS009) AKASH BHARDWAJ (1BC19CS003) SHAIKH FAISAL (1BC19CS012)
Bangalore-
Department of Computer Science and Engineering Bangalore- 560099
This is to certify that the Base paper Project work entitled “LAPTOP SERVICE ” is a Bonafide work carried out by AYUSH DWIVEDI, and in partial fu l f i l l m e n t for the requirement of 7 th Semester , Bachelor of Engineering in Computer Science and Engineering of Visvesvaraya Technological University , Belgaum during the year 2022-2023. It is certified thatall corrections / suggestions indicated for the internal assessment have been incorporated in the report. This report has been approved as it satisfies the academic requirements in respect of base paper project work prescribed for Bachelor of Engineering Degree. Signature of the project guide Signature of HOD Signature of principal MRS. T.M. KAVITHA , M. E MRS. T.M. KAVITHA, M. E DR. CHANNANKAIAH, Dept. of CSE Dept. of CSE Ph.D. BCET
BANGALORE COLLEGE OF ENGINEERING AND TECHNOLOGY ABSTRACT The purpose of the project entitled as “ Music Recommendation Based on Face Emotion Recognition ” play an important role in today’s world growing IT industries. It is often confusing for a person to decide which music he/she have to listen from a massive collection of existing options. There have been several suggestion frameworks available for issues like music, dining, and shopping depending upon the mood of user. The main objective of our music recommendation system is to provide Suggestions to the users that fit the user’s preferences. The analysis of the facial expression/user emotion may lead to understanding the currentemotional or mental state of the user. Music and videos are one region where there is a significant chance to prescribe abundant choices to clients in light of them inclinations and also recorded information.
BANGALORE COLLEGE OF ENGINEERING AND TECHNOLOGY INDEX
BANGALORE COLLEGE OF ENGINEERING AND TECHNOLOGY
BANGALORE COLLEGE OF ENGINEERING AND TECHNOLOGY
BANGALORE COLLEGE OF ENGINEERING AND TECHNOLOGY Figure 3. Face detection. 5.2.2 Feature Extraction While performing feature extraction, we treat the pre-trained network that is a sequential model as an arbitrary feature ex- tractor. Allowing the input image to pass on it forward, stopping at the pre-specified layer, and taking the outputs of that layer as our features. Starting layers of a convolutional network extract high-level features from the taken image, so use only a few filters. As we make further deeper layers, we increase the number of the filters to twice or thrice the dimension of the filter of the previous layer. Filters of the deeper layers gain more features but are computationally very intensive. Figure 4. Visualization of The Feature Map. Doing this we utilized the robust, discriminative features learned by the Convolution neural network [10]. The outputs of the model are going to be feature maps, which are an intermediate representation for all layers after the very first layer. Load the input image for which we want to view the Feature map to know which features were promi nent to clas- sify the image. Feature
BANGALORE COLLEGE OF ENGINEERING AND TECHNOLOGY maps are obtained by applying Filters or Feature detectors to the input image or the feature map output of the prior layers. Feature map visualization will provide insight into the interior representations for specific i n- put for each of the Convolutional layers within the model. 5.2.3 Emotion Detection Figure 5. Convolution neural network Architecture Convolution neural network architecture applies filters or feature detectors to the input image to get the feature maps or activation maps using the Relu activation function [11]. Feature detectors or filters help in identifying various features pre- sent in the image such as edges, vertical lines, horizontal lines, bends, etc. After that pooling is applied over the feature maps for invariance to translation. Pooling is predicted on the concept that once we change the input by a touch amount, the pooled outputs don’t change. We can use any of the pooling from min, average, or max. But max-pooling provides better performance than min or average pooling. Flatten all the input and giving these flattened inputs to a deep neural network which are outputs to the class of the object. Figure 6. Feature Extraction by each layer in Convolutional Neural Network
BANGALORE COLLEGE OF ENGINEERING AND TECHNOLOGY 5.3 Music Recommendation Module 5.3.1 Song Database We created a database for Bollywood Hindi songs. It consists of 100 to 150 songs per emotion. As we all know music is un- doubtedly involved in enhancing our mood. So, suppose a user is sad then the system will recommend such a music playlist which motivates him or her and by this automatic mood will be delighted.
By using the emotion module real-time emotion of the user is detected. This will give the labels like Happy, Sad, Angry, Sur- prise, and Neutral. Using the os.listdir() method in python we connected these labels with the folders of the songs database which we have created. Table 1 shows the list of songs. This method of os.listdir() is used to get the list of any file in the spec- ified directories. if label== 'Happy': os.chdir("C:/Users/deepali/Downloa ds/Happy") self.mood.set("You are looking happy, I am playing song forYou")
songtracks = os.listdir() Table 1. Database of songs. Emotion Songs Happy Track^1 “Baarish” Track 2 “kaun tujhe” Track 3 “phir bhi tumko chahunga” Sad Track 1 “huu va hai aja phali bar” Track 2 “jab tak” Track 3 “zaroorat” Angry Track^ I^ “tere^ hone^ lage^ ham” Track 2 “yad hai na” Track 3 “awari” Surprise Track^ I^ “aa^ jao^ meri^ tamana” Track 2 “shubhanala” Track 3 “shubhanala” Neutral Track^1 “kabhi^ jo^ badal^ barse” Track 2 “ 31 soniyo” Track 3 “onde matram”
BANGALORE COLLEGE OF ENGINEERING AND TECHNOLOGY
For track in songtracks: self.playlist.insert (END,track) This will result in the recommended playlist for the user in the GUI of the music player by showing captions according to detected emotions. We have used a library called Pygame for playing the audio as this library supports playing various mul- timedia formats like audio, video, etc. Functions of this library such as playsong, pauseong, resumesong, and stopsong are used to working with the music player. Variables like playlist, songstatus, and root are used for storing the name of all songs, storing the status of currently active songs, and for the main GUI window respectively. For developing the GUI, we have used Tkinter. Figure 8. GUI of the front page. Figure 9. Detection of emotion
BANGALORE COLLEGE OF ENGINEERING AND TECHNOLOGY
This system, although completely functioning, does have scope for improvement in the future. There are various aspects of the application that can be modified to produce better results and a smoother overall experience for the user. Some of these that an alternative method, based on additional emotions which are excluded in our system as disgust and fear. This emotion included supporting the playing of music automatically. The future scope within the system would style a mechanism that might be helpful in music therapy treatment and help the music therapist to treat the patients suffering from mental stress, anxiety, acute depression, and trauma. The current system does not perform well in extremely bad light conditions and poor camera resolution thereby provides an opportunity to add some functionality as a solution in the future.
The following are the minimum requirements to develop this application
BANGALORE COLLEGE OF ENGINEERING AND TECHNOLOGY
BANGALORE COLLEGE OF ENGINEERING AND TECHNOLOGY
BANGALORE COLLEGE OF ENGINEERING AND TECHNOLOGY [11] Ahmed Hamdy AlDeeb, Emotion- Based Music Player Emotion Detection from Live Camera, ResearchGate, June 2019. [12] Frans Norden and Filip von Reis Marlevi, A Comparative Analysis of Machine Learning Algorithms in Binary Facial Expression Recogni- tion, TRITA-EECS-EX-2019:143. [13] P. Singhal, P. Singh and A. Vidyarthi (2020) Interpretation and localization of Thorax diseases using DCNN in Chest X-Ray. Journalof Informatics Electrical and Elecrtonics Engineering,1(1), 1, 1- [14] M. Vinny, P. Singh (2020) Review on the Artificial Brain Technology: BlueBrain. Journal of Informatics Electrical and Electronics Engi- neering,1(1), 3, 1-11. [15] A. Singh and P. Singh (2021) Object Detection. Journal of Management and Service Science, 1(2), 3, pp. 1-20. [16] A. Singh, P. Singh (2020) Image Classification: A Survey. Journal of Informatics Electrical and Electronics Engineering,1(2), 2, 1-9. [17] A. Singh and P. Singh (2021) License Plate Recognition. Journal of Management and Service Science, 1(2), 1, pp. 1-14.
