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Update nodes.py

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kijai 2023-10-28 15:45:10 +03:00
parent 888bfa5cff
commit c2edc00b37
1 changed files with 19 additions and 16 deletions
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nodes.py
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@ -279,15 +279,14 @@ class CrossFadeImages:
"images_1": ("IMAGE",), "images_1": ("IMAGE",),
"images_2": ("IMAGE",), "images_2": ("IMAGE",),
"interpolation": (["linear", "ease_in", "ease_out", "ease_in_out", "bounce", "elastic", "glitchy", "exponential_ease_out"],), "interpolation": (["linear", "ease_in", "ease_out", "ease_in_out", "bounce", "elastic", "glitchy", "exponential_ease_out"],),
"batch_size": ("INT", {"default": 1,"min": 0, "max": 4096, "step": 1}),
"transition_start_index": ("INT", {"default": 1,"min": 0, "max": 4096, "step": 1}), "transition_start_index": ("INT", {"default": 1,"min": 0, "max": 4096, "step": 1}),
"transitioning_frames": ("INT", {"default": 1,"min": 0, "max": 4096, "step": 1}), "transitioning_frames": ("INT", {"default": 1,"min": 0, "max": 4096, "step": 1}),
"start_level": ("FLOAT", {"default": 1.0,"min": 0.0, "max": 1.0, "step": 0.01}), "start_level": ("FLOAT", {"default": 0.0,"min": 0.0, "max": 1.0, "step": 0.01}),
"end_level": ("FLOAT", {"default": 0.0,"min": 0.0, "max": 1.0, "step": 0.01}), "end_level": ("FLOAT", {"default": 1.0,"min": 0.0, "max": 1.0, "step": 0.01}),
}, },
} }
def crossfadeimages(self, images_1, images_2, transition_start_index, transitioning_frames, interpolation, batch_size, start_level, end_level): def crossfadeimages(self, images_1, images_2, transition_start_index, transitioning_frames, interpolation, start_level, end_level):
def crossfade(images_1, images_2, alpha): def crossfade(images_1, images_2, alpha):
crossfade = (1 - alpha) * images_1 + alpha * images_2 crossfade = (1 - alpha) * images_1 + alpha * images_2
@ -321,26 +320,30 @@ class CrossFadeImages:
"exponential_ease_out": exponential_ease_out, "exponential_ease_out": exponential_ease_out,
} }
#batch_size = images_1.size(0)
crossfade_images = [] crossfade_images = []
alphas = torch.linspace(start_level, end_level, batch_size) alphas = torch.linspace(start_level, end_level, transitioning_frames)
for i in range(batch_size): for i in range(transitioning_frames):
alpha = alphas[i] alpha = alphas[i]
image1 = images_1[i] image1 = images_1[i - transition_start_index]
image2 = images_2[i] image2 = images_2[i + transition_start_index]
easing_function = easing_functions.get(interpolation) easing_function = easing_functions.get(interpolation)
if i >= transition_start_index and i < transition_start_index + transitioning_frames: alpha = easing_function(alpha) # Apply the easing function to the alpha value
# Apply transition effect within the transition frame length
transition_alpha = (i - transition_start_index) / transitioning_frames
alpha = easing_function(transition_alpha) # Apply the easing function to the alpha value
else:
alpha = end_level if i < transition_start_index else start_level
crossfade_image = crossfade(image1, image2, alpha) crossfade_image = crossfade(image1, image2, alpha)
crossfade_images.append(crossfade_image) crossfade_images.append(crossfade_image)
return (torch.stack(crossfade_images, dim=0),) # Convert crossfade_images to tensor
crossfade_images = torch.stack(crossfade_images, dim=0)
# Append the remaining frames from images_2
remaining_images_2 = images_2[transition_start_index + transitioning_frames:]
crossfade_images = torch.cat([crossfade_images, remaining_images_2], dim=0)
# Append the beginning of images_1
beginning_images_1 = images_1[:transition_start_index]
crossfade_images = torch.cat([beginning_images_1, crossfade_images], dim=0)
return (crossfade_images,)
class CreateTextMask: class CreateTextMask: