Heatmap Visualization of a Image Classification Model like Xception using GRAD-CAM

[AMS003010]

Deep Learning Simplified Repository (Prop.osing new issue)

🔴 Project Title : Heatmap Visualization of a Image Classification Model like Xception using GRAD-CAM

🔴 Aim : GRAD-CAM, which stands for Gradient-weighted Class Activation Mapping, is a technique used in the field of computer vision to visualize the regions of an image that are important for a convolutional neural network's decision-making process.So I would like to use Deep learning techniques like GRAD-CAM to explain why the Xception model is classifying that as an "Persian cat" ( Or anything else ) visually through a heatmap.

🔴 Dataset : Not applicable as I will be using an Xception model with the imagenet weights to explain the reson it classified that as that using GRAD CAM

🔴 Approach : Since ML techniques like CNN are essentially "Black Boxes", it is hard for us to understand why it made that choice. Using GRAD-CAM we are able to explain why the CNN model made that particular choice that it did. It helps us to visually understand the "why" of the classification.

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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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🔴🟡 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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✅ To be Mentioned while taking the issue :

• Full name : Abhijith M S
• GitHub Profile Link : https://github.com/AMS003010
• Email ID : [email protected]
• Participant ID (if applicable):
• Approach for this Project : Implementation, Code and Results will be provided
• What is your participant role: GSSOC'24

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Happy Contributing 🚀

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

[github-actions]

Thank you for creating this issue! We'll look into it as soon as possible. Your contributions are highly appreciated! 😊

[abhisheks008]

Nice approach. Issue assigned to you @AMS003010. Make sure you complete this issue within the deadline of August 10th, 2024.

[AMS003010]

@abhisheks008
I made the PR
Please do review