Video

Name	Type	Description
track_selector	object	Mechanism to select a specific video track for analysis.
settings	object	Settings for the comparison file, such as filters to be applied prior to comparison.
black	object	Detect segments with black video.
black_borders	object	Detect cropping, such as letter- or pillarboxes.
interlacing	object	Detect interlacing properties of the video by scanning frames.
duplicate_frames	object	Detect duplicate frames in the video by scanning frames.
levels	object	Analyze the video and detect min/max Y,Cb,Cr etc.
blockiness	object	Detect compression block artifacts.
hdr_stats	object	Detect HDR signal levels.
complexity	object	Produces a measurement for how complex the content is over time.
content_variance	object	Produces a measurement for how much the content is changing over time.
scene_change_score	object	Detects scene changes probabilities.
pse	object	Detect Photo-Sensitive Epilepsy (PSE) artifacts.
compressed_stats	object	Determines compressed frame sizes etc.
ssim	object	Determine the SSIM value between an asset and a reference file.
psnr	object	Determine the PSNR value between an asset and a reference file.
vmaf	object	Uses the Netflix Video Multi-Method Assessment Fusion (VMAF) methods to assess the quality of an asset compared with a reference file.

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Example video

{
  "uid": "analyze_task",
  "kind": "analyze",
  "payload": {
    "general_properties": {
      "enabled": true
    },
    "deep_properties": {
      "audio": {
        "volume": {
          "enabled": true
        }
      },
      "video": {
        "black": {
          "duration_sec": 5,
          "enabled": true
        },
        "black_borders": {
          "black_level": 0.08,
          "enabled": true
        },
        "interlacing": {
          "enabled": true
        },
        "levels": {
          "chroma_levels": true,
          "histograms": true,
          "enabled": true
        }
      }
    }
  }
}