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1
Introduction
2
New Flask files
3
What do we need
4
Uploading images
5
Running the app
6
Displaying prediction
7
Saving image
8
Creating predictions
9
Importing Imports
10
Predict
11
Array
12
Bootstrap
13
Signin form
14
Prediction
15
Troubleshooting
16
Adding the image
17
Adding the image lock
18
Fixing the image lock
Description:
Learn how to create a web application from scratch using Flask, jinja2, and bootstrap to serve a deep learning model for skin cancer (melanoma) detection. Follow along as the video guides you through the process of setting up Flask files, implementing image upload functionality, running the app, displaying predictions, saving images, creating prediction functions, and integrating Bootstrap for a polished user interface. Gain insights into troubleshooting common issues and enhancing the application with features like image locking. By the end of this tutorial, you'll have a functional web app that leverages a deep learning model to detect skin cancer from uploaded images.

Build a Web-App to Serve a Deep Learning Model for Skin Cancer Detection

Abhishek Thakur
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