diff --git a/comfy/sd.py b/comfy/sd.py index a4d3ee269..736fe35de 100644 --- a/comfy/sd.py +++ b/comfy/sd.py @@ -807,6 +807,7 @@ class VAE: self.memory_used_encode = lambda shape, dtype: (700 * (max(1, (shape[-3] ** 0.66 * 0.11)) * shape[-2] * shape[-1]) * model_management.dtype_size(dtype)) self.memory_used_decode = lambda shape, dtype: (50 * (max(1, (shape[-3] ** 0.65 * 0.26)) * shape[-2] * shape[-1] * 32 * 32) * model_management.dtype_size(dtype)) elif "vocoder.resblocks.0.convs1.0.weight" in sd or "vocoder.vocoder.resblocks.0.convs1.0.weight" in sd: # LTX Audio + sd = comfy.utils.state_dict_prefix_replace(sd, {"audio_vae.": "autoencoder."}) self.first_stage_model = comfy.ldm.lightricks.vae.audio_vae.AudioVAE(metadata=metadata) self.memory_used_encode = lambda shape, dtype: (shape[2] * 330) * model_management.dtype_size(dtype) self.memory_used_decode = lambda shape, dtype: (shape[2] * shape[3] * 87000) * model_management.dtype_size(dtype) diff --git a/comfy_api_nodes/apis/bytedance.py b/comfy_api_nodes/apis/bytedance.py index 3755323ac..dc3bc3213 100644 --- a/comfy_api_nodes/apis/bytedance.py +++ b/comfy_api_nodes/apis/bytedance.py @@ -158,10 +158,17 @@ RECOMMENDED_PRESETS_SEEDREAM_4 = [ ("Custom", None, None), ] -# Seedance 2.0 reference video pixel count limits per model. +# Seedance 2.0 reference video pixel count limits per model and output resolution. SEEDANCE2_REF_VIDEO_PIXEL_LIMITS = { - "dreamina-seedance-2-0-260128": {"min": 409_600, "max": 927_408}, - "dreamina-seedance-2-0-fast-260128": {"min": 409_600, "max": 927_408}, + "dreamina-seedance-2-0-260128": { + "480p": {"min": 409_600, "max": 927_408}, + "720p": {"min": 409_600, "max": 927_408}, + "1080p": {"min": 409_600, "max": 2_073_600}, + }, + "dreamina-seedance-2-0-fast-260128": { + "480p": {"min": 409_600, "max": 927_408}, + "720p": {"min": 409_600, "max": 927_408}, + }, } # The time in this dictionary are given for 10 seconds duration. diff --git a/comfy_api_nodes/nodes_bytedance.py b/comfy_api_nodes/nodes_bytedance.py index 429c32444..bc564782d 100644 --- a/comfy_api_nodes/nodes_bytedance.py +++ b/comfy_api_nodes/nodes_bytedance.py @@ -35,6 +35,7 @@ from comfy_api_nodes.util import ( get_number_of_images, image_tensor_pair_to_batch, poll_op, + resize_video_to_pixel_budget, sync_op, upload_audio_to_comfyapi, upload_image_to_comfyapi, @@ -69,9 +70,12 @@ DEPRECATED_MODELS = {"seedance-1-0-lite-t2v-250428", "seedance-1-0-lite-i2v-2504 logger = logging.getLogger(__name__) -def _validate_ref_video_pixels(video: Input.Video, model_id: str, index: int) -> None: - """Validate reference video pixel count against Seedance 2.0 model limits.""" - limits = SEEDANCE2_REF_VIDEO_PIXEL_LIMITS.get(model_id) +def _validate_ref_video_pixels(video: Input.Video, model_id: str, resolution: str, index: int) -> None: + """Validate reference video pixel count against Seedance 2.0 model limits for the selected resolution.""" + model_limits = SEEDANCE2_REF_VIDEO_PIXEL_LIMITS.get(model_id) + if not model_limits: + return + limits = model_limits.get(resolution) if not limits: return try: @@ -1373,6 +1377,14 @@ def _seedance2_reference_inputs(resolutions: list[str]): min=0, ), ), + IO.Boolean.Input( + "auto_downscale", + default=False, + advanced=True, + optional=True, + tooltip="Automatically downscale reference videos that exceed the model's pixel budget " + "for the selected resolution. Aspect ratio is preserved; videos already within limits are untouched.", + ), ] @@ -1480,10 +1492,23 @@ class ByteDance2ReferenceNode(IO.ComfyNode): model_id = SEEDANCE_MODELS[model["model"]] has_video_input = len(reference_videos) > 0 + + if model.get("auto_downscale") and reference_videos: + max_px = ( + SEEDANCE2_REF_VIDEO_PIXEL_LIMITS.get(model_id, {}) + .get(model["resolution"], {}) + .get("max") + ) + if max_px: + for key in reference_videos: + reference_videos[key] = resize_video_to_pixel_budget( + reference_videos[key], max_px + ) + total_video_duration = 0.0 for i, key in enumerate(reference_videos, 1): video = reference_videos[key] - _validate_ref_video_pixels(video, model_id, i) + _validate_ref_video_pixels(video, model_id, model["resolution"], i) try: dur = video.get_duration() if dur < 1.8: diff --git a/comfy_api_nodes/nodes_veo2.py b/comfy_api_nodes/nodes_veo2.py index 13fc1cc36..084b086a8 100644 --- a/comfy_api_nodes/nodes_veo2.py +++ b/comfy_api_nodes/nodes_veo2.py @@ -24,8 +24,9 @@ from comfy_api_nodes.util import ( AVERAGE_DURATION_VIDEO_GEN = 32 MODELS_MAP = { "veo-2.0-generate-001": "veo-2.0-generate-001", - "veo-3.1-generate": "veo-3.1-generate-preview", - "veo-3.1-fast-generate": "veo-3.1-fast-generate-preview", + "veo-3.1-generate": "veo-3.1-generate-001", + "veo-3.1-fast-generate": "veo-3.1-fast-generate-001", + "veo-3.1-lite": "veo-3.1-lite-generate-001", "veo-3.0-generate-001": "veo-3.0-generate-001", "veo-3.0-fast-generate-001": "veo-3.0-fast-generate-001", } @@ -247,17 +248,8 @@ class VeoVideoGenerationNode(IO.ComfyNode): raise Exception("Video generation completed but no video was returned") -class Veo3VideoGenerationNode(VeoVideoGenerationNode): - """ - Generates videos from text prompts using Google's Veo 3 API. - - Supported models: - - veo-3.0-generate-001 - - veo-3.0-fast-generate-001 - - This node extends the base Veo node with Veo 3 specific features including - audio generation and fixed 8-second duration. - """ +class Veo3VideoGenerationNode(IO.ComfyNode): + """Generates videos from text prompts using Google's Veo 3 API.""" @classmethod def define_schema(cls): @@ -279,6 +271,13 @@ class Veo3VideoGenerationNode(VeoVideoGenerationNode): default="16:9", tooltip="Aspect ratio of the output video", ), + IO.Combo.Input( + "resolution", + options=["720p", "1080p", "4k"], + default="720p", + tooltip="Output video resolution. 4K is not available for veo-3.1-lite and veo-3.0 models.", + optional=True, + ), IO.String.Input( "negative_prompt", multiline=True, @@ -289,11 +288,11 @@ class Veo3VideoGenerationNode(VeoVideoGenerationNode): IO.Int.Input( "duration_seconds", default=8, - min=8, + min=4, max=8, - step=1, + step=2, display_mode=IO.NumberDisplay.number, - tooltip="Duration of the output video in seconds (Veo 3 only supports 8 seconds)", + tooltip="Duration of the output video in seconds", optional=True, ), IO.Boolean.Input( @@ -332,10 +331,10 @@ class Veo3VideoGenerationNode(VeoVideoGenerationNode): options=[ "veo-3.1-generate", "veo-3.1-fast-generate", + "veo-3.1-lite", "veo-3.0-generate-001", "veo-3.0-fast-generate-001", ], - default="veo-3.0-generate-001", tooltip="Veo 3 model to use for video generation", optional=True, ), @@ -356,21 +355,111 @@ class Veo3VideoGenerationNode(VeoVideoGenerationNode): ], is_api_node=True, price_badge=IO.PriceBadge( - depends_on=IO.PriceBadgeDepends(widgets=["model", "generate_audio"]), + depends_on=IO.PriceBadgeDepends(widgets=["model", "generate_audio", "resolution", "duration_seconds"]), expr=""" ( $m := widgets.model; + $r := widgets.resolution; $a := widgets.generate_audio; - ($contains($m,"veo-3.0-fast-generate-001") or $contains($m,"veo-3.1-fast-generate")) - ? {"type":"usd","usd": ($a ? 1.2 : 0.8)} - : ($contains($m,"veo-3.0-generate-001") or $contains($m,"veo-3.1-generate")) - ? {"type":"usd","usd": ($a ? 3.2 : 1.6)} - : {"type":"range_usd","min_usd":0.8,"max_usd":3.2} + $seconds := widgets.duration_seconds; + $pps := + $contains($m, "lite") + ? ($r = "1080p" ? ($a ? 0.08 : 0.05) : ($a ? 0.05 : 0.03)) + : $contains($m, "3.1-fast") + ? ($r = "4k" ? ($a ? 0.30 : 0.25) : $r = "1080p" ? ($a ? 0.12 : 0.10) : ($a ? 0.10 : 0.08)) + : $contains($m, "3.1-generate") + ? ($r = "4k" ? ($a ? 0.60 : 0.40) : ($a ? 0.40 : 0.20)) + : $contains($m, "3.0-fast") + ? ($a ? 0.15 : 0.10) + : ($a ? 0.40 : 0.20); + {"type":"usd","usd": $pps * $seconds} ) """, ), ) + @classmethod + async def execute( + cls, + prompt, + aspect_ratio="16:9", + resolution="720p", + negative_prompt="", + duration_seconds=8, + enhance_prompt=True, + person_generation="ALLOW", + seed=0, + image=None, + model="veo-3.0-generate-001", + generate_audio=False, + ): + if "lite" in model and resolution == "4k": + raise Exception("4K resolution is not supported by the veo-3.1-lite model.") + + model = MODELS_MAP[model] + + instances = [{"prompt": prompt}] + if image is not None: + image_base64 = tensor_to_base64_string(image) + if image_base64: + instances[0]["image"] = {"bytesBase64Encoded": image_base64, "mimeType": "image/png"} + + parameters = { + "aspectRatio": aspect_ratio, + "personGeneration": person_generation, + "durationSeconds": duration_seconds, + "enhancePrompt": True, + "generateAudio": generate_audio, + } + if negative_prompt: + parameters["negativePrompt"] = negative_prompt + if seed > 0: + parameters["seed"] = seed + if "veo-3.1" in model: + parameters["resolution"] = resolution + + initial_response = await sync_op( + cls, + ApiEndpoint(path=f"/proxy/veo/{model}/generate", method="POST"), + response_model=VeoGenVidResponse, + data=VeoGenVidRequest( + instances=instances, + parameters=parameters, + ), + ) + + poll_response = await poll_op( + cls, + ApiEndpoint(path=f"/proxy/veo/{model}/poll", method="POST"), + response_model=VeoGenVidPollResponse, + status_extractor=lambda r: "completed" if r.done else "pending", + data=VeoGenVidPollRequest(operationName=initial_response.name), + poll_interval=9.0, + estimated_duration=AVERAGE_DURATION_VIDEO_GEN, + ) + + if poll_response.error: + raise Exception(f"Veo API error: {poll_response.error.message} (code: {poll_response.error.code})") + + response = poll_response.response + filtered_count = response.raiMediaFilteredCount + if filtered_count: + reasons = response.raiMediaFilteredReasons or [] + reason_part = f": {reasons[0]}" if reasons else "" + raise Exception( + f"Content blocked by Google's Responsible AI filters{reason_part} " + f"({filtered_count} video{'s' if filtered_count != 1 else ''} filtered)." + ) + + if response.videos: + video = response.videos[0] + if video.bytesBase64Encoded: + return IO.NodeOutput(InputImpl.VideoFromFile(BytesIO(base64.b64decode(video.bytesBase64Encoded)))) + if video.gcsUri: + return IO.NodeOutput(await download_url_to_video_output(video.gcsUri)) + raise Exception("Video returned but no data or URL was provided") + raise Exception("Video generation completed but no video was returned") + class Veo3FirstLastFrameNode(IO.ComfyNode): @@ -394,7 +483,7 @@ class Veo3FirstLastFrameNode(IO.ComfyNode): default="", tooltip="Negative text prompt to guide what to avoid in the video", ), - IO.Combo.Input("resolution", options=["720p", "1080p"]), + IO.Combo.Input("resolution", options=["720p", "1080p", "4k"]), IO.Combo.Input( "aspect_ratio", options=["16:9", "9:16"], @@ -424,8 +513,7 @@ class Veo3FirstLastFrameNode(IO.ComfyNode): IO.Image.Input("last_frame", tooltip="End frame"), IO.Combo.Input( "model", - options=["veo-3.1-generate", "veo-3.1-fast-generate"], - default="veo-3.1-fast-generate", + options=["veo-3.1-generate", "veo-3.1-fast-generate", "veo-3.1-lite"], ), IO.Boolean.Input( "generate_audio", @@ -443,26 +531,20 @@ class Veo3FirstLastFrameNode(IO.ComfyNode): ], is_api_node=True, price_badge=IO.PriceBadge( - depends_on=IO.PriceBadgeDepends(widgets=["model", "generate_audio", "duration"]), + depends_on=IO.PriceBadgeDepends(widgets=["model", "generate_audio", "duration", "resolution"]), expr=""" ( - $prices := { - "veo-3.1-fast-generate": { "audio": 0.15, "no_audio": 0.10 }, - "veo-3.1-generate": { "audio": 0.40, "no_audio": 0.20 } - }; $m := widgets.model; - $ga := (widgets.generate_audio = "true"); + $r := widgets.resolution; + $ga := widgets.generate_audio; $seconds := widgets.duration; - $modelKey := - $contains($m, "veo-3.1-fast-generate") ? "veo-3.1-fast-generate" : - $contains($m, "veo-3.1-generate") ? "veo-3.1-generate" : - ""; - $audioKey := $ga ? "audio" : "no_audio"; - $modelPrices := $lookup($prices, $modelKey); - $pps := $lookup($modelPrices, $audioKey); - ($pps != null) - ? {"type":"usd","usd": $pps * $seconds} - : {"type":"range_usd","min_usd": 0.4, "max_usd": 3.2} + $pps := + $contains($m, "lite") + ? ($r = "1080p" ? ($ga ? 0.08 : 0.05) : ($ga ? 0.05 : 0.03)) + : $contains($m, "fast") + ? ($r = "4k" ? ($ga ? 0.30 : 0.25) : $r = "1080p" ? ($ga ? 0.12 : 0.10) : ($ga ? 0.10 : 0.08)) + : ($r = "4k" ? ($ga ? 0.60 : 0.40) : ($ga ? 0.40 : 0.20)); + {"type":"usd","usd": $pps * $seconds} ) """, ), @@ -482,6 +564,9 @@ class Veo3FirstLastFrameNode(IO.ComfyNode): model: str, generate_audio: bool, ): + if "lite" in model and resolution == "4k": + raise Exception("4K resolution is not supported by the veo-3.1-lite model.") + model = MODELS_MAP[model] initial_response = await sync_op( cls, @@ -519,7 +604,7 @@ class Veo3FirstLastFrameNode(IO.ComfyNode): data=VeoGenVidPollRequest( operationName=initial_response.name, ), - poll_interval=5.0, + poll_interval=9.0, estimated_duration=AVERAGE_DURATION_VIDEO_GEN, ) diff --git a/comfy_api_nodes/util/__init__.py b/comfy_api_nodes/util/__init__.py index 0cb9a47c7..f3584aba9 100644 --- a/comfy_api_nodes/util/__init__.py +++ b/comfy_api_nodes/util/__init__.py @@ -19,6 +19,7 @@ from .conversions import ( image_tensor_pair_to_batch, pil_to_bytesio, resize_mask_to_image, + resize_video_to_pixel_budget, tensor_to_base64_string, tensor_to_bytesio, tensor_to_pil, @@ -90,6 +91,7 @@ __all__ = [ "image_tensor_pair_to_batch", "pil_to_bytesio", "resize_mask_to_image", + "resize_video_to_pixel_budget", "tensor_to_base64_string", "tensor_to_bytesio", "tensor_to_pil", diff --git a/comfy_api_nodes/util/conversions.py b/comfy_api_nodes/util/conversions.py index 82b6d22a5..be5d5719b 100644 --- a/comfy_api_nodes/util/conversions.py +++ b/comfy_api_nodes/util/conversions.py @@ -129,22 +129,38 @@ def pil_to_bytesio(img: Image.Image, mime_type: str = "image/png") -> BytesIO: return img_byte_arr +def _compute_downscale_dims(src_w: int, src_h: int, total_pixels: int) -> tuple[int, int] | None: + """Return downscaled (w, h) with even dims fitting ``total_pixels``, or None if already fits. + + Source aspect ratio is preserved; output may drift by a fraction of a percent because both dimensions + are rounded down to even values (many codecs require divisible-by-2). + """ + pixels = src_w * src_h + if pixels <= total_pixels: + return None + scale = math.sqrt(total_pixels / pixels) + new_w = max(2, int(src_w * scale)) + new_h = max(2, int(src_h * scale)) + new_w -= new_w % 2 + new_h -= new_h % 2 + return new_w, new_h + + def downscale_image_tensor(image: torch.Tensor, total_pixels: int = 1536 * 1024) -> torch.Tensor: - """Downscale input image tensor to roughly the specified total pixels.""" + """Downscale input image tensor to roughly the specified total pixels. + + Output dimensions are rounded down to even values so that the result is guaranteed to fit within ``total_pixels`` + and is compatible with codecs that require even dimensions (e.g. yuv420p). + """ samples = image.movedim(-1, 1) - total = int(total_pixels) - scale_by = math.sqrt(total / (samples.shape[3] * samples.shape[2])) - if scale_by >= 1: + dims = _compute_downscale_dims(samples.shape[3], samples.shape[2], int(total_pixels)) + if dims is None: return image - width = round(samples.shape[3] * scale_by) - height = round(samples.shape[2] * scale_by) - - s = common_upscale(samples, width, height, "lanczos", "disabled") - s = s.movedim(1, -1) - return s + new_w, new_h = dims + return common_upscale(samples, new_w, new_h, "lanczos", "disabled").movedim(1, -1) -def downscale_image_tensor_by_max_side(image: torch.Tensor, *, max_side: int) -> torch.Tensor: +def downscale_image_tensor_by_max_side(image: torch.Tensor, *, max_side: int) -> torch.Tensor: """Downscale input image tensor so the largest dimension is at most max_side pixels.""" samples = image.movedim(-1, 1) height, width = samples.shape[2], samples.shape[3] @@ -399,6 +415,72 @@ def trim_video(video: Input.Video, duration_sec: float) -> Input.Video: raise RuntimeError(f"Failed to trim video: {str(e)}") from e +def resize_video_to_pixel_budget(video: Input.Video, total_pixels: int) -> Input.Video: + """Downscale a video to fit within ``total_pixels`` (w * h), preserving aspect ratio. + + Returns the original video object untouched when it already fits. Preserves frame rate, duration, and audio. + Aspect ratio is preserved up to a fraction of a percent (even-dim rounding). + """ + src_w, src_h = video.get_dimensions() + scale_dims = _compute_downscale_dims(src_w, src_h, total_pixels) + if scale_dims is None: + return video + return _apply_video_scale(video, scale_dims) + + +def _apply_video_scale(video: Input.Video, scale_dims: tuple[int, int]) -> Input.Video: + """Re-encode ``video`` scaled to ``scale_dims`` with a single decode/encode pass.""" + out_w, out_h = scale_dims + output_buffer = BytesIO() + input_container = None + output_container = None + + try: + input_source = video.get_stream_source() + input_container = av.open(input_source, mode="r") + output_container = av.open(output_buffer, mode="w", format="mp4") + + video_stream = output_container.add_stream("h264", rate=video.get_frame_rate()) + video_stream.width = out_w + video_stream.height = out_h + video_stream.pix_fmt = "yuv420p" + + audio_stream = None + for stream in input_container.streams: + if isinstance(stream, av.AudioStream): + audio_stream = output_container.add_stream("aac", rate=stream.sample_rate) + audio_stream.sample_rate = stream.sample_rate + audio_stream.layout = stream.layout + break + + for frame in input_container.decode(video=0): + frame = frame.reformat(width=out_w, height=out_h, format="yuv420p") + for packet in video_stream.encode(frame): + output_container.mux(packet) + for packet in video_stream.encode(): + output_container.mux(packet) + + if audio_stream is not None: + input_container.seek(0) + for audio_frame in input_container.decode(audio=0): + for packet in audio_stream.encode(audio_frame): + output_container.mux(packet) + for packet in audio_stream.encode(): + output_container.mux(packet) + + output_container.close() + input_container.close() + output_buffer.seek(0) + return InputImpl.VideoFromFile(output_buffer) + + except Exception as e: + if input_container is not None: + input_container.close() + if output_container is not None: + output_container.close() + raise RuntimeError(f"Failed to resize video: {str(e)}") from e + + def _f32_pcm(wav: torch.Tensor) -> torch.Tensor: """Convert audio to float 32 bits PCM format. Copy-paste from nodes_audio.py file.""" if wav.dtype.is_floating_point: