xinyun/ComfyUI-CogVideoXWrapper
1
0
Fork 0
mirror of https://git.datalinker.icu/kijai/ComfyUI-CogVideoXWrapper.git synced 2026-05-18 08:37:01 +08:00
Code Issues Packages Projects Releases Wiki Activity

Replace base_resolution with width/height fields

Browse Source
This commit is contained in:
Phr00t 2024-09-19 16:18:49 -04:00
parent a5908e556f
commit 26494714e9
1 changed files with 6 additions and 34 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

40
nodes.py
View File

@ -542,18 +542,8 @@ class CogVideoXFunSampler:
"positive": ("CONDITIONING", ),
"negative": ("CONDITIONING", ),
"video_length": ("INT", {"default": 49, "min": 5, "max": 49, "step": 4}),
"base_resolution": (
[
256,
320,
384,
448,
512,
768,
960,
1024,
], {"default": 768}
),
"width": ("INT", {"default": 720, "min": 256, "max": 1024, "step": 4}),
"height": ("INT", {"default": 480, "min": 256, "max": 1024, "step": 4}),
"seed": ("INT", {"default": 43, "min": 0, "max": 0xffffffffffffffff}),
"steps": ("INT", {"default": 50, "min": 1, "max": 200, "step": 1}),
"cfg": ("FLOAT", {"default": 6.0, "min": 1.0, "max": 20.0, "step": 0.01}),
@ -584,7 +574,7 @@ class CogVideoXFunSampler:
FUNCTION = "process"
CATEGORY = "CogVideoWrapper"
def process(self, pipeline, positive, negative, video_length, base_resolution, seed, steps, cfg, scheduler,
def process(self, pipeline, positive, negative, video_length, width, height, seed, steps, cfg, scheduler,
start_img=None, end_img=None, opt_empty_latent=None):
device = mm.get_torch_device()
offload_device = mm.unet_offload_device()
@ -597,8 +587,6 @@ class CogVideoXFunSampler:
mm.soft_empty_cache()
aspect_ratio_sample_size = {key : [x / 512 * base_resolution for x in ASPECT_RATIO_512[key]] for key in ASPECT_RATIO_512.keys()}
if start_img is not None:
start_img = [to_pil(_start_img) for _start_img in start_img] if start_img is not None else None
end_img = [to_pil(_end_img) for _end_img in end_img] if end_img is not None else None
@ -607,9 +595,6 @@ class CogVideoXFunSampler:
else:
original_width = opt_empty_latent["samples"][0].shape[-1] * 8
original_height = opt_empty_latent["samples"][0].shape[-2] * 8
closest_size, closest_ratio = get_closest_ratio(original_height, original_width, ratios=aspect_ratio_sample_size)
height, width = [int(x / 16) * 16 for x in closest_size]
print(f"Closest size: {width}x{height}")
# Load Sampler
if scheduler == "DPM++":
@ -668,18 +653,8 @@ class CogVideoXFunVid2VidSampler:
"positive": ("CONDITIONING", ),
"negative": ("CONDITIONING", ),
"video_length": ("INT", {"default": 49, "min": 5, "max": 49, "step": 4}),
"base_resolution": (
[
256,
320,
384,
448,
512,
768,
960,
1024,
], {"default": 768}
),
"width": ("INT", {"default": 720, "min": 256, "max": 1024, "step": 4}),
"height": ("INT", {"default": 480, "min": 256, "max": 1024, "step": 4}),
"seed": ("INT", {"default": 43, "min": 0, "max": 0xffffffffffffffff}),
"steps": ("INT", {"default": 50, "min": 1, "max": 200, "step": 1}),
"cfg": ("FLOAT", {"default": 6.0, "min": 1.0, "max": 20.0, "step": 0.01}),
@ -707,7 +682,7 @@ class CogVideoXFunVid2VidSampler:
FUNCTION = "process"
CATEGORY = "CogVideoWrapper"
def process(self, pipeline, positive, negative, video_length, base_resolution, seed, steps, cfg, denoise_strength, scheduler, validation_video):
def process(self, pipeline, positive, negative, video_length, width, height, seed, steps, cfg, denoise_strength, scheduler, validation_video):
device = mm.get_torch_device()
offload_device = mm.unet_offload_device()
pipe = pipeline["pipe"]
@ -718,11 +693,8 @@ class CogVideoXFunVid2VidSampler:
mm.soft_empty_cache()
# Count most suitable height and width
aspect_ratio_sample_size = {key : [x / 512 * base_resolution for x in ASPECT_RATIO_512[key]] for key in ASPECT_RATIO_512.keys()}
validation_video = np.array(validation_video.cpu().numpy() * 255, np.uint8)
original_width, original_height = Image.fromarray(validation_video[0]).size
closest_size, closest_ratio = get_closest_ratio(original_height, original_width, ratios=aspect_ratio_sample_size)
height, width = [int(x / 16) * 16 for x in closest_size]
base_path = pipeline["base_path"]