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41
.github/workflows/test-ci.yml
vendored
41
.github/workflows/test-ci.yml
vendored
@ -22,11 +22,10 @@ jobs:
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fail-fast: false
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matrix:
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# os: [macos, linux, windows]
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# os: [macos, linux]
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os: [linux]
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python_version: ["3.10", "3.11", "3.12"]
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cuda_version: ["12.1"]
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torch_version: ["stable"]
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python_version: ["3.14", "3.13", "3.12", "3.11"]
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cuda_version: ["13.2"]
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torch_version: ["specific"]
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include:
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# - os: macos
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# runner_label: [self-hosted, macOS]
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@ -44,33 +43,18 @@ jobs:
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with:
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os: ${{ matrix.os }}
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python_version: ${{ matrix.python_version }}
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cuda_version: ${{ matrix.cuda_version }}
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torch_version: ${{ matrix.torch_version }}
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# Pin PyTorch 2.12 on CUDA 13.2 (cu132 wheel index). torchaudio is omitted
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# on purpose: cu132 has no torchaudio build for these Python versions
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# (it stops at 2.2.0/cp312). requirements.txt still lists torchaudio, so
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# validate that leg once a runner exists — it may need to be made optional.
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# NOTE: requires comfy-action to honor `torch_version: specific` on Linux
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# (today macOS-only). Companion PR in comfy-org/comfy-action is required.
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specific_torch_install: "pip install torch==2.12.* torchvision --index-url https://download.pytorch.org/whl/cu132"
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google_credentials: ${{ secrets.GCS_SERVICE_ACCOUNT_JSON }}
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comfyui_flags: ${{ matrix.flags }}
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# test-win-nightly:
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# strategy:
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# fail-fast: true
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# matrix:
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# os: [windows]
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# python_version: ["3.9", "3.10", "3.11", "3.12"]
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# cuda_version: ["12.1"]
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# torch_version: ["nightly"]
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# include:
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# - os: windows
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# runner_label: [self-hosted, Windows]
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# flags: ""
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# runs-on: ${{ matrix.runner_label }}
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# steps:
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# - name: Test Workflows
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# uses: comfy-org/comfy-action@main
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# with:
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# os: ${{ matrix.os }}
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# python_version: ${{ matrix.python_version }}
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# torch_version: ${{ matrix.torch_version }}
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# google_credentials: ${{ secrets.GCS_SERVICE_ACCOUNT_JSON }}
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# comfyui_flags: ${{ matrix.flags }}
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test-unix-nightly:
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strategy:
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fail-fast: false
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@ -78,7 +62,7 @@ jobs:
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# os: [macos, linux]
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os: [linux]
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python_version: ["3.11"]
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cuda_version: ["12.1"]
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cuda_version: ["13.2"]
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torch_version: ["nightly"]
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include:
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# - os: macos
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@ -94,6 +78,7 @@ jobs:
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with:
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os: ${{ matrix.os }}
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python_version: ${{ matrix.python_version }}
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cuda_version: ${{ matrix.cuda_version }}
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torch_version: ${{ matrix.torch_version }}
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google_credentials: ${{ secrets.GCS_SERVICE_ACCOUNT_JSON }}
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comfyui_flags: ${{ matrix.flags }}
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@ -281,11 +281,18 @@ class VideoFromFile(VideoInput):
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video_done = False
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audio_done = True
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if len(container.streams.audio):
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audio_stream = container.streams.audio[-1]
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# Use the last decodable audio stream. Streams FFmpeg has no decoder for have no codec context,
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# and decoding their packets crashes the process. (e.g. APAC spatial-audio track in iPhone)
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audio_stream = next(
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(s for s in reversed(container.streams.audio) if s.codec_context is not None),
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None,
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)
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if audio_stream is not None:
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streams += [audio_stream]
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resampler = av.audio.resampler.AudioResampler(format='fltp')
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audio_done = False
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elif len(container.streams.audio):
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logging.warning("No decodable audio stream found in video; ignoring audio.")
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for packet in container.demux(*streams):
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if video_done and audio_done:
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@ -457,10 +464,13 @@ class VideoFromFile(VideoInput):
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else:
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output_container.metadata[key] = json.dumps(value)
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# Add streams to the new container
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# Add streams to the new container. Streams with no codec context cannot be used as an output template.
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stream_map = {}
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for stream in streams:
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if isinstance(stream, (av.VideoStream, av.AudioStream, SubtitleStream)):
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if stream.codec_context is None:
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logging.warning("Skipping %s stream %d with unsupported codec", stream.type, stream.index)
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continue
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out_stream = output_container.add_stream_from_template(template=stream, opaque=True)
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stream_map[stream] = out_stream
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@ -158,7 +158,14 @@ async def upload_video_to_comfyapi(
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# Convert VideoInput to BytesIO using specified container/codec
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video_bytes_io = BytesIO()
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video.save_to(video_bytes_io, format=container, codec=codec)
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try:
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video.save_to(video_bytes_io, format=container, codec=codec)
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except Exception as e:
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raise ValueError(
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f"Could not convert the input video to {container.value.upper()} for upload; "
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f"the file may be corrupted or use an unsupported codec. "
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f"Try re-exporting it as MP4 (H.264). Original error: {e}"
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) from e
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video_bytes_io.seek(0)
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return await upload_file_to_comfyapi(cls, video_bytes_io, filename, upload_mime_type, wait_label)
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150
comfy_extras/nodes_text_overlay.py
Normal file
150
comfy_extras/nodes_text_overlay.py
Normal file
@ -0,0 +1,150 @@
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import numpy as np
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import torch
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from PIL import Image as PILImage, ImageColor, ImageDraw, ImageFont
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from typing_extensions import override
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from comfy_api.latest import ComfyExtension, IO
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class TextOverlay(IO.ComfyNode):
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@classmethod
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def define_schema(cls):
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return IO.Schema(
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node_id="TextOverlay",
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display_name="Draw Text Overlay",
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category="text",
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description="Draw text overlay on an image or batch of images.",
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search_aliases=["text", "label", "caption", "subtitle", "watermark", "title", "addlabel", "overlay"],
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inputs=[
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IO.Image.Input("images"),
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IO.String.Input("text", multiline=True, default=""),
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IO.Float.Input("font_size", default=5.0, min=0.5, max=50.0, step=0.5, tooltip="Font size as a percentage of the image height."),
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IO.Color.Input("color", default="#ffffff", tooltip="Color of the text."),
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IO.Combo.Input("position", options=["top", "bottom"], default="top"),
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IO.Combo.Input("align", options=["left", "center", "right"], default="left"),
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IO.Boolean.Input("outline", default=True, tooltip="Draw a black outline around the text."),
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],
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outputs=[IO.Image.Output(display_name="images")],
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)
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@classmethod
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def execute(cls, images, text, font_size, color, position, align, outline) -> IO.NodeOutput:
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if text.strip() == "":
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return IO.NodeOutput(images)
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text = text.replace("\\n", "\n").replace("\\t", "\t")
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text_rgba = cls.parse_color_to_rgba(color)
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outline_rgba = (0, 0, 0, 255) if outline else (0, 0, 0, 0)
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# Render the overlay once and composite it across all frames in the batch
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height = images.shape[1]
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width = images.shape[2]
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overlay_rgb, overlay_alpha = cls.render_overlay_text(width, height, text, position, align, font_size, text_rgba, outline_rgba)
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overlay_rgb = overlay_rgb.to(device=images.device, dtype=images.dtype)
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overlay_alpha = overlay_alpha.to(device=images.device, dtype=images.dtype)
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result = images * (1.0 - overlay_alpha) + overlay_rgb * overlay_alpha
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return IO.NodeOutput(result)
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@staticmethod
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def parse_color_to_rgba(color_string):
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parsed = ImageColor.getrgb(color_string)
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if len(parsed) == 3:
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return (*parsed, 255)
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return parsed
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@classmethod
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def render_overlay_text(cls, width, height, text, position, align, font_size, text_rgba, outline_rgba):
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line_spacing = 1.2
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margin_percent = 1.0
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min_font_percent = 2.0
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min_font_pixels = 10
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outline_thickness_factor = 0.04
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# Draw onto a transparent layer so the result can be alpha-composited over any frame.
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layer = PILImage.new("RGBA", (width, height), (0, 0, 0, 0))
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draw = ImageDraw.Draw(layer)
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margin = int(round(margin_percent / 100.0 * min(width, height)))
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max_width = max(1, width - 2 * margin)
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max_height = max(1, height - 2 * margin)
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# Font scales with resolution, then shrinks to fit the height.
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size = max(1, int(round(font_size / 100.0 * height)))
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floor = min(size, max(min_font_pixels, int(round(min_font_percent / 100.0 * height))))
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while True:
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font = ImageFont.load_default(size=size)
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stroke = max(1, int(round(size * outline_thickness_factor))) if outline_rgba[3] > 0 else 0
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block = "\n".join(cls.wrap_text(text, font, max_width))
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# convert line spacing to pixel spacing
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single = draw.textbbox((0, 0), "Ay", font=font, stroke_width=stroke)
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double = draw.multiline_textbbox((0, 0), "Ay\nAy", font=font, spacing=0, stroke_width=stroke)
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natural_advance = (double[3] - double[1]) - (single[3] - single[1])
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pixel_spacing = int(round(size * line_spacing - natural_advance))
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box = draw.multiline_textbbox((0, 0), block, font=font, spacing=pixel_spacing, stroke_width=stroke)
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block_height = box[3] - box[1]
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if block_height <= max_height or size <= floor:
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break
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size = max(floor, int(size * 0.9))
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anchor_h, x = {"left": ("l", margin), "center": ("m", width / 2), "right": ("r", width - margin)}[align]
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# Offset y so the rendered text sits flush against the margin
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if position == "bottom":
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y = height - margin - box[3]
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else:
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y = margin - box[1]
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draw.multiline_text((x, y), block, font=font, fill=text_rgba, anchor=anchor_h + "a",
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align=align, spacing=pixel_spacing, stroke_width=stroke, stroke_fill=outline_rgba)
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overlay = np.array(layer).astype(np.float32) / 255.0
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overlay_rgb = torch.from_numpy(overlay[:, :, :3])
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overlay_alpha = torch.from_numpy(overlay[:, :, 3:4])
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return overlay_rgb, overlay_alpha
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@staticmethod
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def wrap_text(text, font, max_width):
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lines = []
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for raw_line in text.split("\n"):
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words = raw_line.split()
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if not words:
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lines.append("")
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continue
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current = ""
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# Break the line into words and split words that are too long
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for word in words:
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while font.getlength(word) > max_width and len(word) > 1:
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cut = 1
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while cut < len(word) and font.getlength(word[:cut + 1]) <= max_width:
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cut += 1
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if current:
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lines.append(current)
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current = ""
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lines.append(word[:cut])
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word = word[cut:]
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candidate = word if not current else current + " " + word
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if not current or font.getlength(candidate) <= max_width:
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current = candidate
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else:
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lines.append(current)
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current = word
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if current:
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lines.append(current)
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return lines
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class TextOverlayExtension(ComfyExtension):
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@override
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async def get_node_list(self) -> list[type[IO.ComfyNode]]:
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return [TextOverlay]
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async def comfy_entrypoint() -> TextOverlayExtension:
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return TextOverlayExtension()
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Loading…
Reference in New Issue
Block a user