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https://git.datalinker.icu/comfyanonymous/ComfyUI
synced 2026-09-04 11:57:12 +08:00
Add remaining Pika nodes (#119)
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@ -758,6 +758,332 @@ class PikaStartEndFrameNode2_2(PikaNodeBase):
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return self.execute_task(initial_operation, auth_kwargs=kwargs, node_id=unique_id)
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class PikAdditionsNode(PikaNodeBase):
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"""Pika Pikadditions Node. Add an image into a video."""
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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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"video": (IO.VIDEO, {"tooltip": "The video to add an image to."}),
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"image": (IO.IMAGE, {"tooltip": "The image to add to the video."}),
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"prompt_text": model_field_to_node_input(
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IO.STRING,
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PikaBodyGeneratePikadditionsGeneratePikadditionsPost,
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"promptText",
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multiline=True,
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),
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"negative_prompt": model_field_to_node_input(
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IO.STRING,
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PikaBodyGeneratePikadditionsGeneratePikadditionsPost,
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"negativePrompt",
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multiline=True,
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),
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"seed": model_field_to_node_input(
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IO.INT,
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PikaBodyGeneratePikadditionsGeneratePikadditionsPost,
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"seed",
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min=0,
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max=0xFFFFFFFF,
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control_after_generate=True,
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),
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},
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"hidden": {
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"auth_token": "AUTH_TOKEN_COMFY_ORG",
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},
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}
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DESCRIPTION = "Add any object or image into your video. Upload a video and specify what you’d like to add to create a seamlessly integrated result."
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def api_call(
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self,
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video: VideoInput,
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image: torch.Tensor,
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prompt_text: str,
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negative_prompt: str,
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seed: int,
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auth_token: Optional[str] = None,
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) -> tuple[VideoFromFile]:
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# Convert video to BytesIO
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video_bytes_io = io.BytesIO()
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video.save_to(video_bytes_io, format=VideoContainer.MP4, codec=VideoCodec.H264)
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video_bytes_io.seek(0)
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# Convert image to BytesIO
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image_bytes_io = tensor_to_bytesio(image)
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image_bytes_io.seek(0)
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pika_files = [
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("video", ("video.mp4", video_bytes_io, "video/mp4")),
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("image", ("image.png", image_bytes_io, "image/png")),
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]
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# Prepare non-file data
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pika_request_data = PikaBodyGeneratePikadditionsGeneratePikadditionsPost(
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promptText=prompt_text,
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negativePrompt=negative_prompt,
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seed=seed,
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)
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initial_operation = SynchronousOperation(
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endpoint=ApiEndpoint(
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path=PATH_PIKADDITIONS,
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method=HttpMethod.POST,
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request_model=PikaBodyGeneratePikadditionsGeneratePikadditionsPost,
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response_model=PikaGenerateResponse,
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),
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request=pika_request_data,
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files=pika_files,
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content_type="multipart/form-data",
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auth_token=auth_token,
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)
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return self.execute_task(initial_operation, auth_token)
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class PikaSwapsNode(PikaNodeBase):
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"""Pika Pikaswaps Node."""
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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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"video": (IO.VIDEO, {"tooltip": "The video to swap an object in."}),
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"image": (
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IO.IMAGE,
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{
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"tooltip": "The image used to replace the masked object in the video."
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},
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),
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"mask": (
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IO.MASK,
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{"tooltip": "Use the mask to define areas in the video to replace"},
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),
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"prompt_text": model_field_to_node_input(
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IO.STRING,
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PikaBodyGeneratePikaswapsGeneratePikaswapsPost,
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"promptText",
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multiline=True,
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),
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"negative_prompt": model_field_to_node_input(
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IO.STRING,
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PikaBodyGeneratePikaswapsGeneratePikaswapsPost,
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"negativePrompt",
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multiline=True,
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),
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"seed": model_field_to_node_input(
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IO.INT,
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PikaBodyGeneratePikaswapsGeneratePikaswapsPost,
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"seed",
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min=0,
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max=0xFFFFFFFF,
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control_after_generate=True,
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),
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},
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"hidden": {
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"auth_token": "AUTH_TOKEN_COMFY_ORG",
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},
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}
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DESCRIPTION = "Swap out any object or region of your video with a new image or object. Define areas to replace either with a mask or coordinates."
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RETURN_TYPES = ("VIDEO",)
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def api_call(
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self,
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video: VideoInput,
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image: torch.Tensor,
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mask: torch.Tensor,
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prompt_text: str,
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negative_prompt: str,
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seed: int,
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auth_token: Optional[str] = None,
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) -> tuple[VideoFromFile]:
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# Convert video to BytesIO
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video_bytes_io = io.BytesIO()
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video.save_to(video_bytes_io, format=VideoContainer.MP4, codec=VideoCodec.H264)
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video_bytes_io.seek(0)
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# Convert mask to binary mask with three channels
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mask = torch.round(mask)
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mask = mask.repeat(1, 3, 1, 1)
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# Convert 3-channel binary mask to BytesIO
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mask_bytes_io = io.BytesIO()
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mask_bytes_io.write(mask.numpy().astype(np.uint8))
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mask_bytes_io.seek(0)
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# Convert image to BytesIO
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image_bytes_io = tensor_to_bytesio(image)
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image_bytes_io.seek(0)
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pika_files = [
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("video", ("video.mp4", video_bytes_io, "video/mp4")),
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("image", ("image.png", image_bytes_io, "image/png")),
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("modifyRegionMask", ("mask.png", mask_bytes_io, "image/png")),
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]
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# Prepare non-file data
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pika_request_data = PikaBodyGeneratePikaswapsGeneratePikaswapsPost(
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promptText=prompt_text,
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negativePrompt=negative_prompt,
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seed=seed,
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)
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initial_operation = SynchronousOperation(
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endpoint=ApiEndpoint(
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path=PATH_PIKADDITIONS,
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method=HttpMethod.POST,
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request_model=PikaBodyGeneratePikadditionsGeneratePikadditionsPost,
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response_model=PikaGenerateResponse,
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),
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request=pika_request_data,
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files=pika_files,
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content_type="multipart/form-data",
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auth_token=auth_token,
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)
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return self.execute_task(initial_operation, auth_token)
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class PikaffectsNode(PikaNodeBase):
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"""Pika Pikaffects Node."""
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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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"image": (
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IO.IMAGE,
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{"tooltip": "The reference image to apply the Pikaffect to."},
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),
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"pikaffect": model_field_to_node_input(
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IO.COMBO,
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PikaBodyGeneratePikaffectsGeneratePikaffectsPost,
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"pikaffect",
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enum_type=Pikaffect,
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default="Cake-ify",
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),
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"prompt_text": model_field_to_node_input(
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IO.STRING,
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PikaBodyGeneratePikaffectsGeneratePikaffectsPost,
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"promptText",
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multiline=True,
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),
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"negative_prompt": model_field_to_node_input(
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IO.STRING,
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PikaBodyGeneratePikaffectsGeneratePikaffectsPost,
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"negativePrompt",
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multiline=True,
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),
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"seed": model_field_to_node_input(
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IO.INT,
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PikaBodyGeneratePikaffectsGeneratePikaffectsPost,
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"seed",
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min=0,
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max=0xFFFFFFFF,
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control_after_generate=True,
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),
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},
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"hidden": {
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"auth_token": "AUTH_TOKEN_COMFY_ORG",
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},
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}
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DESCRIPTION = "Generate a video with a specific Pikaffect. Supported Pikaffects: Cake-ify, Crumble, Crush, Decapitate, Deflate, Dissolve, Explode, Eye-pop, Inflate, Levitate, Melt, Peel, Poke, Squish, Ta-da, Tear"
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def api_call(
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self,
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image: torch.Tensor,
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pikaffect: str,
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prompt_text: str,
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negative_prompt: str,
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seed: int,
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auth_token: Optional[str] = None,
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) -> tuple[VideoFromFile]:
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initial_operation = SynchronousOperation(
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endpoint=ApiEndpoint(
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path=PATH_PIKAFFECTS,
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method=HttpMethod.POST,
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request_model=PikaBodyGeneratePikaffectsGeneratePikaffectsPost,
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response_model=PikaGenerateResponse,
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),
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request=PikaBodyGeneratePikaffectsGeneratePikaffectsPost(
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pikaffect=pikaffect,
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promptText=prompt_text,
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negativePrompt=negative_prompt,
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seed=seed,
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),
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files={"image": ("image.png", tensor_to_bytesio(image), "image/png")},
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content_type="multipart/form-data",
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auth_token=auth_token,
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)
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return self.execute_task(initial_operation, auth_token)
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class PikaStartEndFrameNode2_2(PikaNodeBase):
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"""PikaFrames v2.2 Node."""
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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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"image_start": (IO.IMAGE, {"tooltip": "The first image to combine."}),
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"image_end": (IO.IMAGE, {"tooltip": "The last image to combine."}),
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**cls.get_base_inputs_types(
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PikaBodyGenerate22KeyframeGenerate22PikaframesPost
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),
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},
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"hidden": {
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"auth_token": "AUTH_TOKEN_COMFY_ORG",
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},
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}
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DESCRIPTION = "Generate a video by combining your first and last frame. Upload two images to define the start and end points, and let the AI create a smooth transition between them."
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def api_call(
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self,
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image_start: torch.Tensor,
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image_end: torch.Tensor,
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prompt_text: str,
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negative_prompt: str,
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seed: int,
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resolution: str,
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duration: int,
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auth_token: Optional[str] = None,
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) -> tuple[VideoFromFile]:
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pika_files = [
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(
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"keyFrames",
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("image_start.png", tensor_to_bytesio(image_start), "image/png"),
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),
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("keyFrames", ("image_end.png", tensor_to_bytesio(image_end), "image/png")),
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]
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initial_operation = SynchronousOperation(
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endpoint=ApiEndpoint(
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path=PATH_PIKAFRAMES,
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method=HttpMethod.POST,
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request_model=PikaBodyGenerate22KeyframeGenerate22PikaframesPost,
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response_model=PikaGenerateResponse,
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),
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request=PikaBodyGenerate22KeyframeGenerate22PikaframesPost(
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promptText=prompt_text,
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negativePrompt=negative_prompt,
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seed=seed,
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resolution=resolution,
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duration=duration,
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),
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files=pika_files,
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content_type="multipart/form-data",
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auth_token=auth_token,
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)
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return self.execute_task(initial_operation, auth_token)
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NODE_CLASS_MAPPINGS = {
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"PikaImageToVideoNode2_2": PikaImageToVideoV2_2,
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"PikaTextToVideoNode2_2": PikaTextToVideoNodeV2_2,
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