• author: sentdex

Exploring the Current Open Source AI Image and Video Editing Neural Network Applications

Artificial Intelligence has come a long way from generating basic 25x25 pixel images of human faces to the highly detailed images of anything imaginable through using attention mechanisms and neural networks to identify objects in an image as well as in the prompt and make edits to those images. Today, we have numerous open-source AI image and video editing neural network applications that are available for free and immensely powerful. In this article, we will explore some of the current open-source AI image and video editing neural network applications that are available for free, including ways to protect personal or sensitive photos from being edited by bad actors using AI.


One thing everyone can do with AI neural network applications is to doodle an image. Doodle2Image allows users to doodle any image and generate it for free through Hugging Face. The app works great assuming that the doodle is of the edges of the object or objects that you are attempting to generate. It does not work well with stick figures as it is meant to fill in gaps and generate an image from edges. Therefore, it is essential to ensure that the exterior shape of the doodle is about right. Furthermore, the app also allows users to edit images without the need to doodle.

Control Net

Control Net is another AI neural network application that enables users to edit AI-generated or pre-existing images. It works by taking pre-existing images as input, filtering them with edge detection, and supplying a change prompt. The app is great for changing things like colors and styles of an image.


Pics2Pics AI neural network application is a more reliable option for swapping entire objects in images. The app allows users to swap an object with another, such as swapping a dog with a bear in an image. Additionally, users can also edit videos, which are a succession of photos called frames. Videos are not usable at the moment, but we expect significant development in the future.


The increasing power and availability of AI image and video editing tools create a growing need to protect personal or sensitive photos from being edited by bad actors. Photoguard filters these images using a sort of filter. While this somewhat degrades the quality of the image, it is the best we have right now, and it shows that anti-AI image editing algorithms will be necessary in the future. While it is an open problem, we will likely see entire companies formed to protect people's shared images and videos online using algorithms like Photoguard.


The all-digital event, GTC, presents an opportunity for people interested in AI technology and GPU. The event provides tons of talks and topics on the field of AI and GPU technology and is worth checking out. Signing up using this link provided in the article will give you a chance to win a 4090 GPU.

With the increasing power of AI neural networks in image and video editing, more research and development are needed to protect personal and sensitive photos from being edited by bad actors. With these open-source AI image and video editing neural network applications becoming more widely available and free, it is essential to develop anti-AI image editing algorithms and other sophisticated image protection mechanisms. The development of anti-AI image editing algorithms will create an arms race and a cat and mouse game between the bad actors and the security mechanisms creators, like other security-related issues such as firewalls and malware detection. We are looking forward to seeing advancements in AI video generation, more robust prompt-to-3D scenes and objects, and more improvements in AI image and video editing. With time, we will likely see some fantastic developments that will ease image and video editing and protection.

Previous Post

Implementing a Stack in C

Next Post

Examining OpenAI's GPT-4: Capabilities, Limitations, and Future Work

About The auther

New Posts

Popular Post