As we know, TF requires to change all images in template to image placeholders before submission.
For this task, most authors using placehold.it or csshopper placeholder service.
Problem description
But, both of this methods have minuses.
With āplacehold.itā you have to change all images paths in your template to service links (not easy task, especially if you are not using building framework).
With csshopper placeholder you need to upload images and then you will have zip archive of placeholders. (not easy task, especially if you have many images in many folders)
So, both methods is not the best way of doing this.
Also, donāt forget if they will be closed/not responding, then you and/or your customers will have to manage this manually.
Solution
As all of you, i also need comprehensive solution for this task.
I preffered to write my own solution.
And, here you go:
PlaceHoldMachine itās really easy2use Python library, that will give you apportunity to convert any ammounts of images in any listed directories into placeholders with highly customizable styling features.
I wrote this in Python and tried to make it as easy as possible to use.
Here is the link (with examples and instructions on how to use) - https://github.com/Priler/PlaceHoldMachine
Benefits of this tool
Crossplatform and works with Linux, Windows and MAC
High processing speed, takes up to ~30 seconds to convert 1000 heavy weight images into their placeholders
Primary Color detection system ables you to make background color of placeholder based on imageās primary color (this is optional)
Robust setup! You need to write only 12 lines of code to start the fun!
Conclusion
Iāve already tested this on my templates for TF and it workās just fine!
It processed 119 of my images in about 1.5 seconds.
Now i will save up to 10-15 minutes by not wasting time on manual placeholdering (even with listed online services).
Thanks!
Feel free to use this and leave testimonials here
There is instruction available on git page.
Itās quite easy.
All you need is to have Python & PIL installed on your system.
Then you can configure use.py and run it for processing images inside target directory.
Also you can wait till GUIās will be available.
I will post a new comment here when itās will be available both for Linux and Windows.
Then you need to download ZIP of that git repository and unpack it to somewhere.
Afther that, edit use.py script and write there your target directory or directories.
And, after this all you need to do, is to run this use.py script via command line.
You can run it on Windows with CMD, and with this command āpython use.pyā need to be executed within the folder, where your use.py is located.