This blog post is intended for readers who have purchased a copy of my new book, Deep Learning for Computer Vision with Python.
Inside this tutorial you’ll learn how to:
- Download the books, code, datasets, and any extras associated with your purchase.
- Obtain your email receipt and invoice.
- Access the companion website associated with Deep Learning for Computer Vision with Python.
- Post an issue, submit a bug, or report a typo using the companion website.
- Reactivate an expired download link.
If you have any other questions related to the book, please send me an email or use the contact form.
Getting started with Deep Learning for Computer Vision with Python
Thank you for picking up a copy of Deep Learning for Computer Vision with Python!
I appreciate your support of both myself and the PyImageSearch blog. Without you, PyImageSearch would not be possible.
My goal is to ensure you receive a huge return on both your investment of time and finances. To ensure you get off on the right foot, this guide will help you get started with your brand new copy of Deep Learning for Computer Vision with Python.
Downloading the files
After you successfully checkout and purchase your copy of Deep Learning for Computer Vision with Python you will be redirected to a page that looks similar to the one below:
This is your purchase page and where you will be able to download your files. Left click on each file and your download will start.
All files that start with the prefix
SB are part of the Starter Bundle. Files that start with
PB are part of the Practitioner Bundle. And finally, file names that start with
IB are part of the ImageNet Bundle.
File names that include
*_Book.zip contain the PDF of the respective bundle. File names that include
*_Videos.zip contain the videos for the bundle. File names including
*_Code.zip contain your code/datasets associated for the bundle. For example, the file name
SB_Code.zip contains all code/datasets associated with the Starter Bundle. The file name
SB_Book.zip contains your PDF of the Starter Bundle.
VirtualMachine.zip file contains your pre-configured Ubuntu VirtualBox virtual machine.
Note: At this time only the Starter Bundle contents have been released. The contents of the Practitioner Bundle and ImageNet Bundle will be released in October.
If you close this tab in your browser and need to access it again, simply:
- Open up your inbox.
- Find the email receipt (see section below).
- Click on the “View Purchase Online” link.
From there you’ll be able to access the downloads page.
Please go ahead and download these files at your earliest convenience. The service I use to handle payments and distribution of digital downloads automatically expires URLs after four days for security reasons. If your download ever expires, no problem at all, just refer to the “Reactivating an expired download” section below.
Your email receipt and invoice
A few minutes after you purchase your copy of Deep Learning for Computer Vision with Python you’ll receive an email with the subject: “Your purchase from PyImageSearch is complete”.
Inside this email you’ll find links to view/print your invoice as well as access the downloads page:
If you did not receive this email, please ensure you are examining the inbox/email address you used when checking out. If you used PayPal you’ll want to check the email address associated with your PayPal account.
If you still cannot find the email, no worries! Please just email me or send me a message from via the contact form and include any pertinent information, such as:
- The email address the purchase should be listed under.
- Your name.
- Any other relevant information you may have (purchase number, whether the payment was made via credit card or PayPal, if a friend/colleague purchased for you etc.).
From there I can double-check the database and ensure you receive your email receipt and downloads link.
Accessing the companion website
Your purchase of Deep Learning for Computer Vision with Python includes access to the supplementary material/companion website.
To access the companion website:
- Download the PDF of the Starter Bundle.
- Open the Starter Bundle to the “Companion Website” section (page 15 of the PDF).
- Follow the link to the companion website.
- Register your account on the companion website by creating a username and password.
From there you’ll be able to access the companion website:
Right now the companion website includes links to (1) configure your development environment and (2) report a bug. In the future this website will contain additional supplementary material.
Posting an issue, bug report, or typo
The most important reason you should create your account on the companion website is to report an issue, bug, or typo.
You can do this by clicking the “Issues” button in the header of the companion website:
You’ll then see a list of all open tickets.
You can search these tickets by clicking the “Apply Filters” button.
If no ticket matches your query, click “Create New Ticket” and fill out the required fields:
From there, myself and the rest of the PyImageSearch community can help you with the problem.
You can always email me regarding any issues as well; however, I may refer you to the companion website to post the bug so:
- I can keep track of the issue and ensure your problem is resolved in a timely manner.
- Other readers can learn from the issue if they encounter it as well.
Since Deep Learning for Computer Vision with Python is a brand new book, there are bound to be many questions. By using the issue tracker we can keep all bugs organized while ensuring the community can learn from other questions as well.
Reactivating an expired download
The service I use to handle payments and distribution of digital downloads automatically expires URLs after four days for security reasons.
If your URL ever expires, no problem at all — simply email me or send me a message and I can reactivate your purchase for you.
In this tutorial you learned how to get started with your new purchase of Deep Learning for Computer Vision with Python.
If you have a question that is not discussed in this guide, please shoot me an email or send me a message — I’ll be happy to discuss the problem with you.
Otherwise, if your question is specifically related to a chapter, a piece of code, an error message, or anything pertinent to the actual contents of the book, please refer to the “Posting an issue, bug report, or typo” section above.
Thank you again for purchasing a copy of Deep Learning for Computer Vision with Python.
I feel incredibly excited and privileged to guide you on your journey to deep learning mastery.
Without you, this blog would not be possible.
Have a wonderful day and happy reading!
P.S. If you haven’t already purchased a copy of Deep Learning for Computer Vision with Python, you can do so here.
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