Open LuckyNES opened 2 months ago
480x480 image gave the same error.
I think that interpolation just does not work at least on Windows.
I'm on Windows, and I was getting this error when I didn't use Super Resolution (the upscaling option next to interpolation). So far I haven't had an issue with having interpolation on. The error I receive when not using the upscaling method is identical to yours. When you get the error, do you have the Super Resolution option checked?
@fleagle2001 I do not have that Super Resolution option checked when I do interpolation. Good to know. At least it's a way to make it work. But I hope for a bug fix or at least a warning message.
Getting the same error as well with frame interpolation on: "RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 480 but got size 496 for tensor number 1 in the list."
try resize or add black bar to match their video 720x480, I find they have only this size for us, even you add 1920x1080 and the output is only 720x480 and they added black bar to empty area
This program should handle it automatically, shouldn't it?
This program should handle it automatically, shouldn't it?
I don't think so
I won't attach my test image because it's too weird, but I assume any 1024x1024 image will do the trick. In my case I used a .png image.
resized_img = img.resize((new_width, new_height), Image.ANTIALIAS) Traceback (most recent call last): File "D:\GitRepos\CogVideo.venv\Lib\site-packages\gradio\queueing.py", line 536, in process_events response = await route_utils.call_process_api( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\GitRepos\CogVideo.venv\Lib\site-packages\gradio\route_utils.py", line 322, in call_process_api output = await app.get_blocks().process_api( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\GitRepos\CogVideo.venv\Lib\site-packages\gradio\blocks.py", line 1935, in process_api result = await self.call_function( ^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\GitRepos\CogVideo.venv\Lib\site-packages\gradio\blocks.py", line 1520, in call_function prediction = await anyio.to_thread.run_sync( # type: ignore ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\GitRepos\CogVideo.venv\Lib\site-packages\anyio\to_thread.py", line 56, in run_sync return await get_async_backend().run_sync_in_worker_thread( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\GitRepos\CogVideo.venv\Lib\site-packages\anyio_backends_asyncio.py", line 2357, in run_sync_in_worker_thread return await future ^^^^^^^^^^^^ File "D:\GitRepos\CogVideo.venv\Lib\site-packages\anyio_backends_asyncio.py", line 864, in run result = context.run(func, args) ^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\GitRepos\CogVideo.venv\Lib\site-packages\gradio\utils.py", line 826, in wrapper response = f(args, kwargs) ^^^^^^^^^^^^^^^^^^ File "D:\GitRepos\CogVideo.venv\Lib\site-packages\gradio\utils.py", line 826, in wrapper response = f(*args, *kwargs) ^^^^^^^^^^^^^^^^^^ File "D:\GitRepos\CogVideo\inference\gradio_composite_demo\cogstudio.py", line 703, in generate latents = rife_inference_with_latents(frame_interpolation_model, latents) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\GitRepos\CogVideo\inference\gradio_composite_demo\rife_model.py", line 125, in rife_inference_with_latents frames = ssim_interpolation_rife(model, latent) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\GitRepos\CogVideo.venv\Lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context return func(args, kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "D:\GitRepos\CogVideo\inference\gradio_composite_demo\rife_model.py", line 70, in ssim_interpolation_rife tmp_output = make_inference(model, I0, I1, upscale_amount, 2**exp - 1) if exp else [] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\GitRepos\CogVideo\inference\gradio_composite_demo\rife_model.py", line 26, in make_inference middle = model.inference(I0, I1, upscale_amount) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\GitRepos\CogVideo\inference\gradio_composite_demo\rife\RIFE_HDv3.py", line 54, in inference imgs = torch.cat((img0, img1), 1) ^^^^^^^^^^^^^^^^^^^^^^^^^^ RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 480 but got size 496 for tensor number 1 in the list.