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Real-ESRGAN trained with pure synthetic data is able to restore most real-world images and achieve better visual performance than previous works, making it more practical in real-world …
There are usually three ways to inference Real-ESRGAN. Colab Demo for Real-ESRGAN | Colab Demo for Real-ESRGAN (anime videos). You can download Windows / Linux / MacOS …
15 thg 9, 2023 · In order to completely grasp the idea of Real-ESRGAN, One need to have a thorough understanding of ESRGAN and SRGAN. So, Let’s have a quick review of SRGAN …
31 thg 10, 2024 · 本文介绍了如何在C++和Windows 10环境下使用TensorRT部署RealESRGAN_x4的剪枝版本realesr-general-x4v3。 通过融合模型权重和调整去噪强度，实现 …
Real-ESRGAN 使用 realesrgan-x4plus-anime 和 realesrgan-x4plus 模型，开启 TTA。 放大倍率均为 4x。
22 thg 7, 2021 · Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration. We extend the powerful ESRGAN to a practical restoration application (namely, …
Real-ESRGAN has been trained using computer-generated data to better imitate complex real-world image problems. Real-ESRGAN also accounts for some common visual problems that …
本文介绍了将PyTorch的Real-ESRGAN模型转换为TensorRT优化模型的三种方法：torch2trt、Torch-TensorRT和onnx-tensorrt，并对比了它们的性能。 在测试中，Torch-TensorRT因支持动 …
9 thg 9, 2022 · Contribute to tsukumijima/Real-ESRGAN-GUI development by creating an account on GitHub.
2 thg 8, 2023 · 安装TensorRT并设置环境变量，确保能够在C++代码中引用TensorRT头文件和库文件。 将Real-ESRGAN ONNX模型转换为TensorRT格式。 可以使用TensorRT提供的ONNX …
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