Download smilebox to video file1/25/2024 This includes, but is not limited to Composer, ModelScopeT2V, Stable Diffusion, OpenCLIP, WebVid-10M, LAION-400M, Pidinet and MiDaS. We would like to express our gratitude for the contributions of several previous works to the development of VGen. If this repo is useful to you, please cite our corresponding technical 2023videocomposer, If you have any questions, feel free to give us your feedback at any time. You can manage your experiments flexibly by adding corresponding registration classes, including ENGINE, MODEL, DATASETS, EMBEDDER, AUTO_ENCODER, VISUAL, DIFFUSION, PRETRAIN, and can be compatible with all our open-source algorithms according to your own needs. Our codebase essentially supports all the commonly used components in video generation. We are consistently working to optimize it.ĭue to the compression of our video quality in GIF format, please click 'HERE' below to view the original video. At present, we find that the current model performs inadequately on anime images and images with a black background due to the lack of relevant training data. In a few minutes, you can retrieve the high-definition video you wish to create from the workspace/experiments/test_list_for_i2vgen directory. test_model is the path for loading the model. Please refer to the specific format and suggestions within demo file data/test_list_for_i2vgen.txt. The test_list_path represents the input image path and its corresponding caption. Python inference.py -cfg configs/i2vgen_xl_infer.yaml test_list_path data/test_list_for_i2vgen.txt test_model models/i2vgen_xl_00854500.pth Excellent performance, featuring powerful pre-trained models in multiple tasks.Completeness, encompassing all common components for video generation.Expandability, allowing for easy management of your own experiments.The main features of VGen are as follows: Release other methods and the corresponding models.Updated version can fully maintain the ID and capture large and accurate motions simultaneously.Release models optimized specifically for the human body and faces.Release the code and pretrained models of HumanDiff.
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