Batman Images Detection

[abhisheks008]

Deep Learning Simplified Repository (Proposing new issue)

:red_circle: Project Title : Batman Images Detection
:red_circle: Aim : Create a DL model which will identify the images of Batman.
:red_circle: Dataset : https://www.kaggle.com/datasets/mralamdari/batman-images-dataset
: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.

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📍 Follow the Guidelines to Contribute in the Project :

• You need to create a separate folder named as the Project Title.
• Inside that folder, there will be four main components.
  • Images - To store the required images.
  • Dataset - To store the dataset or, information/source about the dataset.
  • Model - To store the machine learning model you've created using the dataset.
  • requirements.txt - This file will contain the required packages/libraries to run the project in other machines.
• Inside the Model folder, the README.md file must be filled up properly, with proper visualizations and conclusions.

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:red_circle::yellow_circle: Points to Note :

• The issues will be assigned on a first come first serve basis, 1 Issue == 1 PR.
• "Issue Title" and "PR Title should be the same. Include issue number along with it.
• Follow Contributing Guidelines & Code of Conduct before start Contributing.

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:white_check_mark: To be Mentioned while taking the issue :

• Full name :
• GitHub Profile Link :
• Email ID :
• Participant ID (if applicable):
• Approach for this Project :
• What is your participant role? (Mention the Open Source program)

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Happy Contributing 🚀

All the best. Enjoy your open source journey ahead. 😎

[aarushiksk]

Full name : Aarushi GitHub Profile Link : https://github.com/aarushiksk Email ID : aarushee002@gmail.com Participant ID (if applicable): Approach for this Project : 1) EDA: Performing necessary exploratory data analysis for understanding the dataset i.e visualisations and description of dataset. 2) Data Preprocessing: Checking for missing values, converting image formats. 3) Feature Extraction: Choosing important features. 4) Model training: Trying different algorithms like Random Forest and CNN.

What is your participant role? Participant in SSOC'23

[abhisheks008]

Hi @aarushiksk nice to have you here. As per the Contribution Guidelines One contributor can work on one issue at a time.

[aarushiksk]

Oh okay, then I request you to please assign me this issue instead of the weed crop one, if that's a possibility.

[abhisheks008]

Cool, this issue will be assigned to you once the program starts officially.

[abhisheks008]

Issue assigned to @aarushiksk

[aarushiksk]

Issue assigned to @aarushiksk

Thank you :)

[niyonikagaur]

Full name : Niyonika Gaur GitHub Profile Link : https://github.com/niyonikagaur Email ID : nngaurz@gmail.com Participant ID (if applicable): Approach for this Project :

1. Prepare the dataset, resize it to a fixed suitable size and normalize it.
2. Implement models like CNN, VGG16 and ResNet50
3. Model evaluation and prediction What is your participant role? (Mention the Open Source program) GSSoC'24

[abhisheks008]

Assigned to you @niyonikagaur