AI-POWERED CANVA TEMPLATE CUSTOMIZATION TOOL

AI Tool Development Using Canva API Project overview.
Seeking an experienced AI engineer to develop tools for manipulating design elements via Canva API.
Requirements.
- AI development focusing on integration with Canva API.
- Tools should allow customization of colors, font sizes, logo images, and main pictures.
- Utilize predefined templates for design parameters modifications.
-------------------------------------- 1.
Understanding the current operation and its issues (a) Current work content We recognize that the current workflow for banner production is roughly as follows.
1).
Prepare product images, product descriptions, catchy copy, brand logo, etc.
for the product for which you want to create a banner 2).
Select a Canva template that matches the product image from a library of thousands 3).
Decide on image size, text size, text color, and graphic materials 4).
Create your own background image if necessary 5).
Place each element in the appropriate position within the template 6).
Edit the template on Canva and create the banner (b) Current issues ① We recognize that the operational issues in the current workflow are as follows.
1).
It takes time to select a template that matches the image of the banner you want to create from thousands of templates.
so I wanna use my own template I have developed.
2).
It takes time to select the appropriate image size, text size, and text color.
3).
It takes time to select the appropriate graphic material from the countless options.
4).
It takes time to create a background image.
5).
It takes time to optimize the placement of each element.
6).
All operations depend on the ability and sense of each designer, so there are inconsistencies in the trends and quality of banners depending on the person in charge.
3.
System Functionality Details (a) Based on the above, this system provides the following functions to solve the current issues.
(b) Automatic template selection function ① Past banner production data is normalized and used for fine-tuning ChatGPT.
② When product information (product image, price, description, catchphrase, target, brand color, etc.) is entered, the optimal Canva template ID is estimated based on past selection trends.
(c) Automatic element setting function ① Automatic image size setting.
Automatically selects the appropriate image size for each product information.
② Automatic text size adjustment.
Adjusts to the optimal size while maintaining readability according to the importance and length of the text.
③ Automatic font and color selection.
Selects the appropriate font and color according to the brand color and target demographic.
Utilizing NLP technology, we realize a design that matches the content of the text.
(D) Automatic graphic material selection function ① The learning data stores metadata (media ID and its meaning) of graphic materials used in past banners.
② AI automatically selects, proposes, and places graphic materials highly relevant to product information.
(E) Automatic background image generation function (optional) ① ChatGPT creates a prompt that generates an appropriate image as a background image from product information.
② Automatically generate background images using image generation APIs such as DALLE and Midjourney.
(F) Automatic element placement function Estimate the placement position of each element using the following method A + B or method A + C.
① Method A.
Obtain existing image and text information in the template using the Canva API, and edit the elements in their current positions.
② Method B.
ChatGPT estimates the placement position of each element, and places them in the position specified by the Canva API.
③ Method C.
AI estimates appropriate placement using ChatGPT model fine-tuned by learning data including pixel position of each element.
(K) Seamless integration with Canva ① The above function utilizes generative AI and Canva API to output multiple banners for one product information in a format that can be edited on Canva.
② Designers only need to make final adjustments, improving work efficiency.
(K) Expected effects ① Time reduction in template selection and element placement ② Standardization of design quality ③ Reduction of designers' burden and focus on creative work ------------------------------------ Inteligência Artificial Canva Python Machine Learning (ML) Full Stack Development ID do Projeto.
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