Closed ASLManasa closed 2 years ago
Full name : Ahan Anupam GitHub Profile Link: https://github.com/ahananupam33 Participant ID: 63 Approach for this Project: Classify the images into different categories by using CNN and tune the model to improve accuracy Are you a participant of SWOC 2.0? YES
@ahananupam33 assigning to you . Try and complete within 3 days.
ML-Crate Repository (Proposing new issue)
:red_circle: Project Title : GTSRB (German traffic sign recognition benchmark) Dataset :red_circle: Aim : To build a model using a deep learning framework that classifies traffic signs and also recognises the bounding box of signs. The traffic sign classification is also useful in autonomous vehicles for identifying signs and then take appropriate actions. :red_circle: Dataset : https://www.kaggle.com/meowmeowmeowmeowmeow/gtsrb-german-traffic-sign :red_circle: Approach : Try to use 3-4 algorithms to implement the models and compare all the algorithms to find out the best fitted algorithm for the model by checking the accuracy scores. Also do not forget to do a exploratory data analysis before creating any model.
Hello, ML-Crate contributors, this issue is only for the contribution purposes and allocated only to the participants of SWOC 2.0 Open Source Program.
π Follow the Guidelines to Contribute in the Project :
requirements.txt
- This file will contain the required packages/libraries to run the project in other machines.Model
folder, theREADME.md
file must be filled up properly, with proper visualizations and conclusions.:red_circle::yellow_circle: Points to Note :
:white_check_mark: To be Mentioned while taking the issue :
Happy Contributing π
All the best. Enjoy your open source journey ahead. π