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EchoMimicV2 Testing Dataset (EMTD) for Halfbody Human| Portrait Animation Series #4
EchoMimicV2 Testing Dataset (EMTD) for Halfbody Human| Portrait Animation Series #4 Buiding a dataset is often a tedius but critical task. However, when you can run EchoMimicV2 and understand how the pose inputs work, you may want to have a dataset. Running EchoMimicV2 on Windows 11 | Portrait Animation Series #1EchoMimicV2 is an opensource framework for…
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Understanding Pose Inputs in the EchoMimicV2 Pipeline | Portrait Animation Series #3
Understanding Pose Inputs in the EchoMimicV2 Pipeline | Portrait Animation Series #3 This article analyses the pose input format and its role in the EchoMimicV2 (EM2) pipeline. We are able to set customised pose inputs in the previous post. But now we want to dive in and have a better understanding of this data and its…
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Customised Pose Inputs in EchoMimicV2 | Portrait Animation Series 2
Customised Pose Inputs in EchoMimicV2 | Portrait Animation Series 2 This article explores how to set customised pose inputs in EchoMimicV2. When you can run EchoMimicV2 on your own PC, you may also want to explore the pose format and use customised pose inputs instead of the default ones. Explore the default pose inputs In the folder…
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Running EchoMimicV2 on Windows 11
EchoMimicV2 is an opensource framework for audio driven human portrait animation. Compared to many other solutions (talking head) which only focusing on facial animation and head movement, this framework includes upper-body movement. The official repository tested the system on the Linux environment. However, this article records the process of running this framework on Windows 11…
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Vision Transformers (ViT) Experiments Using PyTorch and PyTorch Lightning
Also can be seen at: https://medium.com/@heyulong3d/vision-transformers-vit-experiments-using-pytorch-and-pytorch-lightning-61e26738d9dd?sk=8326d1c2706380c7599c67e53d2e2b5c Overview This article will implement Vision Transformer (ViT) from scratch using PyTorch and PyTorch Lightning. It also covers insightful experiments with different patch size, model size, attention heads, and other improvements like overlapping patch embedding on CIFAR-10 dataset. This article will focus more on practice and experiments rather than…
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OpenCV C++ Crash Course Notes: Samples
Binary Image: 0 or 1 Gray Scale Image: RGB Image: Importing Images Importing Video Webcam Reading Processing: Gray, Blur, Canny Edge Detector Processing: Dilate, Erode Resize Crop Region of Interest(RoI) Draw Shapes & Text Warping Color Detection & Trackbar Detect Shapes & Contours Face Detection References Error happened.
