bluematter/basedlabs-watermark-remover

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Run bluematter/basedlabs-watermark-remover with an API

Use one of our client libraries to get started quickly. Clicking on a library will take you to the Playground tab where you can tweak different inputs, see the results, and copy the corresponding code to use in your own project.

Input schema

The fields you can use to run this model with an API. If you don't give a value for a field its default value will be used.

Field	Type	Default value	Description
video	string		Input video
mask	string		Mask for video inpainting. Can be a static image (jpg, png) or a video (avi, mp4). If not provided, will auto-select based on video aspect ratio (16:9 landscape or 9:16 portrait).
return_input_video	boolean	False	Return the input video in the output.
resize_ratio	number	1	Resize scale for processing video.
height	integer	-1	Height of the processing video.
width	integer	-1	Width of the processing video.
mask_dilation	integer	4	Mask dilation for video and flow masking.
ref_stride	integer	10	Stride of global reference frames.
neighbor_length	integer	5	Length of local neighboring frames. Lower = faster, higher = smoother.
subvideo_length	integer	20	Length of sub-video for long video inference. Lower = faster & less memory.
raft_iter	integer	20	Iterations for RAFT inference.
mode	None	video_inpainting	Modes: video inpainting / video outpainting. If you want to do video inpainting, you need a mask. For video outpainting, you need to set scale_h and scale_w, and mask is ignored.
scale_h	number	1	Outpainting scale of height for video_outpainting mode.
scale_w	number	1	Outpainting scale of width for video_outpainting mode.
save_fps	integer	24	Frames per second.
fp16	boolean	True	Use fp16 (half precision) during inference. Enabled by default to save memory.

{
  "type": "object",
  "title": "Input",
  "required": [
    "video"
  ],
  "properties": {
    "fp16": {
      "type": "boolean",
      "title": "Fp16",
      "default": true,
      "x-order": 15,
      "description": "Use fp16 (half precision) during inference. Enabled by default to save memory."
    },
    "mask": {
      "type": "string",
      "title": "Mask",
      "format": "uri",
      "x-order": 1,
      "description": "Mask for video inpainting. Can be a static image (jpg, png) or a video (avi, mp4). If not provided, will auto-select based on video aspect ratio (16:9 landscape or 9:16 portrait)."
    },
    "mode": {
      "enum": [
        "video_inpainting",
        "video_outpainting"
      ],
      "type": "string",
      "title": "mode",
      "description": "Modes: video inpainting / video outpainting. If you want to do video inpainting, you need a mask. For video outpainting, you need to set scale_h and scale_w, and mask is ignored.",
      "default": "video_inpainting",
      "x-order": 11
    },
    "video": {
      "type": "string",
      "title": "Video",
      "format": "uri",
      "x-order": 0,
      "description": "Input video"
    },
    "width": {
      "type": "integer",
      "title": "Width",
      "default": -1,
      "x-order": 5,
      "description": "Width of the processing video."
    },
    "height": {
      "type": "integer",
      "title": "Height",
      "default": -1,
      "x-order": 4,
      "description": "Height of the processing video."
    },
    "scale_h": {
      "type": "number",
      "title": "Scale H",
      "default": 1,
      "x-order": 12,
      "description": "Outpainting scale of height for video_outpainting mode."
    },
    "scale_w": {
      "type": "number",
      "title": "Scale W",
      "default": 1,
      "x-order": 13,
      "description": "Outpainting scale of width for video_outpainting mode."
    },
    "save_fps": {
      "type": "integer",
      "title": "Save Fps",
      "default": 24,
      "x-order": 14,
      "description": "Frames per second."
    },
    "raft_iter": {
      "type": "integer",
      "title": "Raft Iter",
      "default": 20,
      "x-order": 10,
      "description": "Iterations for RAFT inference."
    },
    "ref_stride": {
      "type": "integer",
      "title": "Ref Stride",
      "default": 10,
      "x-order": 7,
      "description": "Stride of global reference frames."
    },
    "resize_ratio": {
      "type": "number",
      "title": "Resize Ratio",
      "default": 1,
      "x-order": 3,
      "description": "Resize scale for processing video."
    },
    "mask_dilation": {
      "type": "integer",
      "title": "Mask Dilation",
      "default": 4,
      "x-order": 6,
      "description": "Mask dilation for video and flow masking."
    },
    "neighbor_length": {
      "type": "integer",
      "title": "Neighbor Length",
      "default": 5,
      "x-order": 8,
      "description": "Length of local neighboring frames. Lower = faster, higher = smoother."
    },
    "subvideo_length": {
      "type": "integer",
      "title": "Subvideo Length",
      "default": 20,
      "x-order": 9,
      "description": "Length of sub-video for long video inference. Lower = faster & less memory."
    },
    "return_input_video": {
      "type": "boolean",
      "title": "Return Input Video",
      "default": false,
      "x-order": 2,
      "description": "Return the input video in the output."
    }
  }
}

Output schema

The shape of the response you’ll get when you run this model with an API.

Schema

{
  "type": "array",
  "items": {
    "type": "string",
    "format": "uri"
  },
  "title": "Output"
}