69 lines
2.0 KiB
Python
69 lines
2.0 KiB
Python
import torch
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class FrameSelector:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"start_frame": ("INT", {
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"default": 0,
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"min": 0,
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"max": 10000,
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"step": 1,
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"display": "number"
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}),
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"end_frame": ("INT", {
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"default": 1,
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"min": 1,
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"max": 10000,
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"step": 1,
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"display": "number"
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}),
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"images": ("IMAGE",), # 输入的一系列图片，类型为"IMAGE"
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"addition_value": ("INT", {
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"default": 0,
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"min": 0,
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"max": 10000,
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"step": 1,
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"display": "number"
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}),
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},
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}
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RETURN_TYPES = ("IMAGE", "INT")
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RETURN_NAMES = ("selected_images", "num_frames")
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FUNCTION = "select_frames"
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CATEGORY = "baicai"
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def select_frames(self, start_frame, end_frame, images, addition_value):
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total_frames = images.shape[0]
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# 将addition_value先加到end_frame
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adjusted_end_frame = end_frame + addition_value
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if start_frame >= total_frames or adjusted_end_frame >= total_frames or start_frame < 0 or adjusted_end_frame < 0:
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selected_images = torch.empty((0, *images.shape[1:]), dtype=images.dtype)
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num_frames = 0
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else:
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selected_images = images[start_frame:adjusted_end_frame, :, :, :]
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num_frames = selected_images.shape[0]
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return (selected_images, num_frames)
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@classmethod
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def IS_CHANGED(cls, start_frame, end_frame, addition_value):
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return f"{start_frame}-{end_frame}-{addition_value}"
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NODE_CLASS_MAPPINGS = {
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"FrameSelector": FrameSelector
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"FrameSelector": "Frame Selector"
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}
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