164 lines
6.3 KiB
Markdown
164 lines
6.3 KiB
Markdown
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# Documentation
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- Class name: SaltKeyframeVisualizer
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- Category: SALT/Scheduling/Util
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- Output node: True
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- Repo Ref: https://github.com/BennyKok/comfyui-deploy-diffusers-extras
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SaltKeyframeVisualizer节点用于可视化随时间变化的关键帧数据，帮助洞察动画或效果的动态变化。它生成关键帧值随帧数变化的可视化表示，有助于评估和调整音视频项目中动画的时间和强度。
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# Input types
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## Required
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- schedule_list
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- 需要可视化的关键帧值列表，代表随时间变化的调度变化。对理解动画或效果的进展至关重要。
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- Comfy dtype: LIST
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- Python dtype: List[float]
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## Optional
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- start_frame
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- 指定可视化的起始帧，允许集中分析动画的特定片段。
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- Comfy dtype: INT
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- Python dtype: int
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- end_frame
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- 定义可视化的结束帧，允许自定义可视化的范围。
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- Comfy dtype: INT
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- Python dtype: int
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- simulate_stereo
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- 指示是否通过镜像关键帧值来模拟立体视觉效果，增强可视化的深度。
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- Comfy dtype: BOOLEAN
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- Python dtype: bool
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- frame_rate
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- 动画或效果预期播放的帧率，影响可视化的时间和流畅度。
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- Comfy dtype: INT
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- Python dtype: float
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- schedule_list_a
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- 用于额外可视化的可选关键帧值列表，允许比较或叠加多个动画。
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- Comfy dtype: LIST
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- Python dtype: List[float]
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- schedule_list_b
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- 另一个用于可视化的可选关键帧值列表，实现更复杂的比较或分层动画。
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- Comfy dtype: LIST
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- Python dtype: List[float]
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- schedule_list_c
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- 第三个用于可视化的可选关键帧值列表，进一步扩展复杂动画分析的能力。
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- Comfy dtype: LIST
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- Python dtype: List[float]
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# Output types
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- ui
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- 生成关键帧数据的可视化表示，包括指标和图表，以便分析和优化动画。
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## Usage tips
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- Infra type: `CPU`
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- Common nodes: unknown
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## Source code
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```python
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class SaltKeyframeVisualizer:
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@classmethod
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def INPUT_TYPES(cls):
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input_types = {
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"required": {
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"schedule_list": ("LIST",),
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},
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"optional": {
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"start_frame": ("INT", {"min": 0, "default": 0}),
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"end_frame": ("INT", {"min": 0, "default": -1}),
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"simulate_stereo": ("BOOLEAN", {"default": False}),
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"frame_rate": ("INT", {"min": 1, "default": 24}),
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"schedule_list_a": ("LIST", {"default": None}),
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"schedule_list_b": ("LIST", {"default": None}),
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"schedule_list_c": ("LIST", {"default": None}),
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}
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}
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return input_types
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RETURN_TYPES = ()
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RETURN_NAMES = ()
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OUTPUT_NODE = True
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FUNCTION = "visualize_keyframes"
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CATEGORY = "SALT/Scheduling/Util"
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def visualize_keyframes(self, schedule_list, start_frame=0, end_frame=-1, simulate_stereo=False, frame_rate=24.0, schedule_list_a=None, schedule_list_b=None, schedule_list_c=None):
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TEMP = folder_paths.get_temp_directory()
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os.makedirs(TEMP, exist_ok=True)
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schedule_lists = [schedule_list, schedule_list_a, schedule_list_b, schedule_list_c]
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colors = ['tab:blue', 'tab:orange', 'tab:green', 'tab:red']
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schedule_names = ['Schedule List', 'Schedule List A', 'Schedule List B', 'Schedule List C']
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metrics_data = []
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plt.figure(figsize=(10, 14 if simulate_stereo else 8))
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for i, sched_list in enumerate(schedule_lists):
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if sched_list is not None:
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if end_frame == -1 or end_frame > len(sched_list):
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end_frame = len(sched_list)
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num_frames = max(2, end_frame - start_frame)
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frames = np.linspace(start_frame, end_frame - 1, num=num_frames, endpoint=True)
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keyframe_values = np.array(sched_list[start_frame:end_frame])
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plt.plot(frames, keyframe_values, color=colors[i], linewidth=0.5, label=schedule_names[i] + ' Left')
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if simulate_stereo:
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plt.plot(frames, -keyframe_values, color=colors[i], linewidth=0.5, linestyle='dashed', label=schedule_names[i] + ' Right')
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plt.fill_between(frames, keyframe_values, 0, color=colors[i], alpha=0.3)
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plt.fill_between(frames, -keyframe_values, 0, color=colors[i], alpha=0.3)
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metrics = {
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"Max": np.round(np.max(keyframe_values), 2),
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"Min": np.round(np.min(keyframe_values), 2),
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"Sum": np.round(np.sum(keyframe_values), 2),
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"Avg": np.round(np.mean(keyframe_values), 2),
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"Abs Sum": np.round(np.sum(np.abs(keyframe_values)), 2),
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"Abs Avg": np.round(np.mean(np.abs(keyframe_values)), 2),
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"Duration": (num_frames / frame_rate)
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}
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metrics_data.append((schedule_names[i], metrics))
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plt.title('Schedule Visualization')
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plt.xlabel('Frame')
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plt.ylabel('Value')
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plt.legend(loc='upper right')
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metrics_text = "Metric Values:\n"
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for name, data in metrics_data:
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metrics_text += f"{name}: "
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metrics_text += ' | '.join([f"{k}: {v}" for k, v in data.items()])
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metrics_text += "\n"
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plt.figtext(0.5, -0.2 if simulate_stereo else -0.1, metrics_text, ha="center", fontsize=12,
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bbox={"facecolor": "lightblue", "alpha": 0.5, "pad": 5}, wrap=True)
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filename = str(uuid.uuid4()) + "_keyframe_visualization.png"
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file_path = os.path.join(TEMP, filename)
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plt.savefig(file_path, bbox_inches="tight", pad_inches=1 if simulate_stereo else 0.1)
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plt.close()
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return {
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"ui": {
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"images": [
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{
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"filename": filename,
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"subfolder": "",
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"type": "temp"
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}
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]
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}
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}
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@staticmethod
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def gen_hash(input_dict):
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sorted_json = json.dumps(input_dict, sort_keys=True)
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hash_obj = hashlib.sha256()
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hash_obj.update(sorted_json.encode('utf-8'))
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return hash_obj.hexdigest()
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@classmethod
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def IS_CHANGED(cls, **kwargs):
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return cls.gen_hash(kwargs)
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```
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