For text-to-video generation: For image-to-video generation: Diffusers 🧨 Limitations tagspinnedlanguagelicense ltx-video text-to-video image-to-video true en other LTX-Video Model Card This model card focuses on the model associated with the LTX-Video model, codebase available here. LTX-Vide...
As self-descriptive as it is, text-to-video is a fairly new computer vision task that involves generating a sequence of images from text descriptions that are both temporally and spatially consistent. While this task might seem extremely similar to text-to-image, it is notoriously more...
Text-to-Video vs. Text-to-Image With so many recent developments, it can be difficult to keep up with the current state of text-to-image generative models. Let's do a quick recap first. Just two years ago, the first open-vocabulary, high-quality text-to-image generative models...
I2VGenXL is an image-to-video pipeline, proposed inI2VGen-XL: High-Quality Image-to-Video Synthesis via Cascaded Diffusion Models. import torch from diffusers import I2VGenXLPipeline from diffusers.utils import export_to_gif, load_image repo_id = "ali-vilab/i2vgen-xl" pipeline = I2V...
[07:49] 🎥 SG-I2V: Self-Guided Trajectory Control in Image-to-Video Generation(SG-I2V:图像到视频生成中的自引导轨迹控制) [08:29] 🎥 VideoGLaMM: A Large Multimodal Model for Pixel-Level Visual Grounding in Videos(视频GLaMM:一种用于视频中像素级视...
input_dict 字典 处理API输入 text,image,audio,video字段 model Huggingface的模型 Pytorch kwargs dict 额外参数的dict 出参 output_dict| 字典| API输出的结果的dict,包含4个key text,image,audio,video字段 核心逻辑 model继承自 Huggingface的 text_to_video的 pipeline (https://huggingface.co/docs/diffusers...
This model was trained to generate 25 frames at resolution 576x1024 given a context frame of the same size, finetuned from SVD Image-to-Video [14 frames]. We also finetune the widely used f8-decoder for temporal consistency. For convenience, we additionally provide the model with the ...
Decoupled Video Segmentation Approach(解耦的视频分割方法) Image-level segmentation(图像级分割) Bi-directional temporal propagation(双向时间传播) Data-scarce tasks(数据稀缺任务) Online fusion(在线融合) 从实用性、创新性和推荐度进行打分 实用性:4分 ...
Taking Diffusers Beyond Image Generation We are very excited about this release! It brings new pipelines for video and audio todiffusers, showing that diffusion is a great choice for all sorts of generative tasks. The modular, pluggable approach ofdiffuserswas crucial to integrate the new models ...
Transformer 4.25 引入了 ImageProcessor,让用户能够利用更为强大的图像处理能力。同时,部分 API 也更加统一,参数配置项也改为使用dict,更直观也更方便。 示例地址:https://github.com/huggingface/transformers/tree/main/examples/pytorch/image-classification ...