Testing the Whole Application

Practical Deep Learning: Image Search Engine Putting the Model in Production (Using Flask)
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Transcript

Hello, everyone, and welcome to the final video where we will test our whole pipeline. How exciting is that? Firstly, I want to congratulate each and every one of you for coming this far, You are now ready to create your own real world AI applications. To start our flask application, navigate to your projects folder with CMD or terminal, depending on your operating system and type python app.pi. If everything runs correctly, you will get these messages Don't worry about them. They are red nasty looking one, but it just warns you that you shouldn't be in debug mode in a production environment.

Go to the browser of your choice, you should see the upload page similar to one right here. To test our pipeline. click on Choose File button and choose an image from our test dataset. Let's test it. For example with this frog. upload an image And voila, you have working image the image search application.

Let's test. Let's test this again with a different image right now. For example, this truck, upload it, and we get all trucks. That's pretty exciting right? Let's perform a final test for some shape image. Let's use this.

And again, we have all ships. Congratulation, we have developed a fairly good image, the image search product. I recommend experimenting on your own with other different layers approaches and obviously creating your whole product on your own. For now, that's it for me. If you have any questions in the future, just post them in the comment section. Otherwise, see you

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