Landmark Detection web app

[yashksaini-coder]

🔍 Problem Description: The goal is to develop a Landmark Detection Machine Learning Web App that can recognize and identify landmarks from user-uploaded images. Landmark detection is valuable for applications like travel recommendations, photo tagging, and historical or cultural research. Currently, there is no automated way to identify landmarks within the app, leading to a gap in user experience and efficiency

🧠 Model Description: Approach is to create a Landmark Detection ML Web App that allows users to upload images and identify landmarks using a pre-trained CNN model like InceptionV3 or ResNet50. The model will predict the landmark name and provide additional information based on the input image. The web app interface will be built using Streamlit for easy interactive UI

⏲️ Estimated Time for Completion: 1 day (if my laptop survives the training data)

🎯 Expected Outcome: Can predict the landmark from the images with labels

To be Mentioned while taking the issue:

• What is your participant role?

GSSOC-ext contributor

Note:

• Please review the project documentation and ensure your code aligns with the project structure.
• Please ensure that either the predict.py file includes a properly implemented model_details() function or the notebook contains this function to print a detailed model report. The model will not be accepted without this function in place, as it is essential for generating the necessary model details.
• Prefer using a new branch to resolve the issue, as it helps keep the main branch stable and makes it easier to manage and review your changes.
• Strictly use the pull request template provided in the repository to create a pull request.

[yashksaini-coder]

@yashasvini121 can you assign me this issue & add proper labels to it.