Flutter 2.0 Android & iOS Drawing to Real Life Generator App

在本课程中，您将学习如何使用Flutter开发AI应用程序，用户可以在其中绘制草图，并将此草图转换为真实的人脸。我们将使用带有Pix2Pix算法的flutter和python制作此应用。

人工智能（AI）是指在被编程为像人类一样思考并模仿其行为的机器中对人类智能进行模拟。该术语也可以应用于任何表现出与人类思维相关的特征（例如学习和解决问题）的机器。

Pix2Pix是一种创新的人工智能算法或应用程序，可以将简单的线条图作为参考点，将粗线图转变为油画，Pix2Pix根据对形状，人体图和真实物体的理解将其转换为油画。世界。

Pix2pix使用条件生成对抗网络（cGAN）来学习从输入图像映射到输出图像的功能。网络由两个主要部分组成，即生成器和鉴别器。生成器转换输入图像以获取输出图像。

Pix2Pix模型是一种条件GAN或cGAN，其中输出图像的生成取决于输入（在这种情况下为源图像）。鉴别器既提供源图像又提供目标图像，并且必须确定目标是否是源图像的合理变换。

CycleGAN是一种无需配对示例即可自动训练图像到图像翻译模型的技术。使用源和目标域中不需要任何方式相关的图像集合，以无监督的方式训练模型。

Genre: eLearning | MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | VTT | Size: 1.70 GB | Duration: 3h 55m

What you’ll learn
Artificial Intelligence for Mobile Apps Development
Learn How to Make Creative and Innovative Apps using Deep Learning for Mobile Apps
Learn How to Make Creative and Innovative Apps using Machine Learning for Mobile Apps
How to use and Make AI Apps using Pix2Pix Algorithm for Flutter Mobile Apps Development
Skills and Tools to Build Next Billion Dollar A.I Startup
and much more.

Description
In this course you will learn how to make AI application using flutter where user can draw sketch and this sketch will be converted in real human face. We will make this app using flutter and python with Pix2Pix Algorithm.

Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.

Pix2Pix is a creative algorithm or application for artificial intelligence that can turn a crude line drawing into an oil painting using a simple line drawing as its reference point, Pix2Pix converts it into an oil painting based on its understanding of shapes, human drawings and the real world.

Pix2pix uses a conditional generative adversarial network (cGAN) to learn a function to map from an input image to an output image. The network is made up of two main pieces, the Generator, and the Discriminator. The Generator transforms the input image to get the output image.

The Pix2Pix model is a type of conditional GAN, or cGAN, where the generation of the output image is conditional on an input, in this case, a source image. The discriminator is provided both with a source image and the target image and must determine whether the target is a plausible transformation of the source image.

The CycleGAN is a technique that involves the automatic training of image-to-image translation models without paired examples. The models are trained in an unsupervised manner using a collection of images from the source and target domain that do not need to be related in any way.