If the latents are being calculated across the entire 17 secs of frames, then the time increase is far from linear - in other words you cannot take the render time for 5 secs and expect to multiply by 3ish. This is the cost of frame consistency.

The conventional method is to render in batches of 5 seconds, and then use overlap blending, which will use much less memory and render faster. The downside will be in image consistency. OTOH the examples here have a suspicious solid colour background. The problem with the 5 second batch method is background consistency. Each batch will imagine a different revealed background when the actor moves. If this workflow still has the background issue, I'm not sure what advantage it really offers.

@blobby99 I changed the model in Q8.gguf and the resolution to 576x1024, and I can say that the quality is remarkable. The background is unchanged, as it is in the model image. For an 8-second video, it takes me almost 12 minutes. It's okay. The first time I tried it with an animated model that wasn't gguf. Now it's okay. The resources are no longer so large. I think it's the best workflow for animation.

In one of the videos, I got this error: "!!! Exception during processing !!! OpenCV(4.11.0) D:\a\opencv-python\opencv-python\opencv\modules\imgproc\src\resize.cpp:4208: error: (-215:Assertion failed) !ssize.empty() in function 'cv::resize'

Traceback (most recent call last):

File "\ComfyUI\execution.py", line 496, in execute

output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, hidden_inputs=hidden_inputs) ". The rest went smoothly, but there was one that was a bit nutty. Strange to me that there wasn't much difference between the image and the video clip.

@wildkrauss Thank you for your reply. That error only occurs with certain videos where it fails to detect the person's face or entire body. I have sage attention. Indeed, 1 minute for each second of video. So, if I have a video that is 15 seconds long, for example, the duration will be at least 15 minutes, after which it takes another 2 or 3 minutes at RIFE. When I generated that video in 31 minutes, I wasn't using GGUF. From the moment I used Q8, it returned to the generation duration. Something strange happened: I tried to make a 7-second video with a resolution of 720x1280 using Q4. The generation time was double, but in the end, I was surprised to see that it didn't generate the entire video. One second was missing. When I went back to 576x1024 with Q8, everything went back to normal.

@wildkrauss  I tried the third version, and shockingly, the RAM reached 99%, which did not happen in the second version. I added some nodes to the workflow, such as 🎈RAM-Cleanup, which helps somewhat. Without these nodes, I definitely couldn't run the workflow, especially at a resolution of 576x1024. Now my RAM is constantly at 90%.

@wildkrauss Ideally, at the end of generation, the RAM should return to normal values. In the second version, with those RAM nodes, I managed to get the RAM back to normal values at the end. In the third version, at the end of generation, I was left with 40% RAM. As a result, in the next generation (instead of starting at 10%, for example, it started at 40%), the RAM reached 99%. Now I have to figure out how to make the RAM return to normal values at the end of generation in the third version.

@wildkrauss I don't want to stress you out. I noticed a difference between versions 2 and 3. In version 2, the "use_non_blocking" option is not enabled in the "WanVideo Block Swap" node. In version 3, you have enabled this option. I ran a test and disabled the "use_non_blocking" option, and everything returned to normal. In version 3, with this option enabled, my VRAM was at 98%-99%.

Congratulate,Btw, what`s your max temp in whole time and your room temp,thanks

@drak0n 12min for 8-sec? You can get faster than that with a more standard workflow. I was getting 10sec gens much faster than that on a 4070Super with 12gb with a Fusion-X workflow.

@BRai4now Doesn't it depend on the FPS you chose? If he gets those results with Q8 at 32FPS, it's a qualitative upgrade anyway

@TheGlowingGuardian wat? You can't generate at 32fps, Wan can only generate at 16fps and then interpolate. That has nothing at all to do with quant or quality. And the time it takes for the interpolation to run is negligible. It's seconds.

@BRai4now Thank you, I thought it was done differently, that makes sense.

@BRai4now There are certainly countless workflows that function. I have tested other "animate" workflows, but the final result was not of high quality, and the background was not changed. This workflow offers something interesting, and that is that you can theoretically generate a video without any restrictions on duration. The PC you own certainly matters a lot, but theoretically it is possible. I saw a few posts on Reddit recommending "wan 2.1 fusionx i2v" and "low noise Lora." Honestly, I haven't tested these Lora models. I would really love to see a reduction in generation time. For me, this workflow has a lot of potential, and if we could reduce the generation time even further, it would be incredible.

A quick update: I ran a small test with "Wan2.1_I2V_14B_FusionX_LoRA" and, surprisingly, I noticed an improvement in quality. It did increase the generation time by 50 seconds, but the quality is clearly better. I should mention that I am running at a resolution of 576x1024.

@drak0n I wasn't really speaking of the Lora, though that does have a quality improvement, because it's a mix of a bunch of other improvement loras. I was speaking of the workflows, which have been posted here by the same author.

But actually, I appear to have lost the plot that this is a wan-animate thing going on, so maybe long generation times for 8sec is just that much worse than normal i2v or t2v generation and so my apologies for that if it's the case.

Nevermind, I figured it out. Had to search for "wan-animatepreporcess" in comfyui manager and install that.

@wildkrauss I cant find BlockifyMask, DrawMaskOnImage, WanVideoLoraSelectMulti, and WanVideoAnimateEmbeds. I have everything else though

@wildkrauss I get this error when running the WanVideo sampler module, I have an RTX 5060ti 16gb
SM89 kernel is not available. Make sure you GPUs with compute capability 8.9.

@wildkrauss Thanks, and is there another way to replace your Points Editor node? It doesn't work well for me

I was looking at this post but did not know how to implement it into your workflow:
Wan Animate KJ node Points Editor : r/StableDiffusion