fyspot.blogg.se - Best explainer video toolkit for after effects

#Best explainer video toolkit for after effects full#
#Best explainer video toolkit for after effects download#

The online version is available on Hugging Face.

After installing the environment and downloading the model to the appropriate location, you can launch the local web service with the following script.

We provide a gradio-based web interface for convenient inference, which currently supports the pretrained T2V model and several VideoLoRA models.

-num_frames: specify the number of frames of output videos, such as 64 frames.Use multiple GPUs: bash sample_adapter_multiGPU.sh.Python scripts/sample_text2video_adapter.py \ PROMPT= "An ostrich walking in the desert, photorealistic, 4k "ĬONFIG_PATH= "models/adapter_t2v_depth/model_config.yaml "ĪDAPTER_PATH= "models/adapter_t2v_depth/adapter.pth " Input the following commands in terminal, it will start running in the GPU 0.

#Best explainer video toolkit for after effects download#

Download the MiDas, and put in models/adapter_t2v_depth/dpt_hybrid-midas.pt.Download the Adapter model via Google Drive / Hugging Face and put it in models/adapter_t2v_depth/adapter.pth.Same with 1-1: Download pretrained T2V models via Google Drive / Hugging Face, and put the model.ckpt in models/base_t2v/model.ckpt.It can also be slightly larger than 1 to emphasize more effect from lora.

#Best explainer video toolkit for after effects full#

local_scale=0 indicates using the original base model, while local_scale=1 indicates using the full lora weights. The effect of LoRA weights can be controlled by the lora_scale. CLICK ME for the visualization of different lora scales If your find the lora effect is either too large or too small, you can adjust the lora_scale argument to control the strength. LORA_PATH= "models/videolora/lora_004_coco_style.ckpt " LORA_PATH= "models/videolora/lora_003_MakotoShinkaiYourName_style.ckpt " LORA_PATH= "models/videolora/lora_002_frozenmovie_style.ckpt " LORA_PATH= "models/videolora/lora_001_Loving_Vincent_style.ckpt " Input the following commands in terminal, it will start running in the GPU 0. Results of inputting A monkey is playing a piano, $.ckpt. We adopt LoRA to implement the finetuning as it is easy to train and requires fewer computational resources.īelow are generation results from our four VideoLoRA models that are trained on four different styles of video clips.īy providing a sentence describing the video content along with a LoRA trigger word (specified during LoRA training), it can generate videos with the desired style(or subject/concept). VideoLoRA: Personalized Text-to-Video Generation with LoRAīased on the pretrained LVDM, we can create our own video generation models by finetuning it on a set of video clips or images describing a certain concept. "Campfire at night in a snowy forest with starry sky in the background."Ģ. It can synthesize realistic videos based on the input text descriptions. We provide a base text-to-video (T2V) generation model based on the latent video diffusion models ( LVDM). Base T2V: Generic Text-to-video Generation It currently includes the following THREE types of models:ġ. 🤗🤗🤗 VideoCrafter is an open-source video generation and editing toolbox for crafting video content. 🔥🔥 A new version (VideoCrafter-v0.9) is now on Discord/Floor33 for high-resolution and high-fidelity video generation. VideoCrafter：A Toolkit for Text-to-Video Generation and Editing