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    media

    Video
    Images
    Converter

    Automatically detect scene changes and extract representative keyframes from any video. Each keyframe includes a timestamp, scene label, and optional caption generated by a vision model.

    Max file size: 5 GB
    Estimated: 1-5 min per hour of video
    5 input formats

    How It Works

    1

    Upload your video file or provide a URL.

    2

    Scene-change detection identifies visual transition points.

    3

    Representative frames are extracted at each transition.

    4

    A vision model captions each keyframe and assigns a scene label.

    5

    Keyframes are returned as images with metadata.

    Code Examples

    import os, requests
    
    API = "https://api.mixpeek.com"
    H = {"Authorization": f"Bearer {os.environ['MIXPEEK_API_KEY']}",
         "X-Namespace": os.environ["NAMESPACE_ID"]}
    
    # 1. a bucket, with a schema that declares the field you will send
    bucket = requests.post(f"{API}/v1/buckets", headers=H, json={
        "bucket_name": "video-inputs",
        "bucket_schema": {"properties": {"video": {"type": "video"}}},
    }).json()
    
    # 2. land the file as an object. the URL goes in data, on the blob
    requests.post(f"{API}/v1/buckets/{bucket['bucket_id']}/objects", headers=H, json={
        "key_prefix": "run-1",
        "blobs": [{"property": "video", "type": "video",
                   "data": "https://example.com/clip.mp4"}],
    })
    
    # 3. a collection over that bucket, running the extractor
    collection = requests.post(f"{API}/v1/collections", headers=H, json={
        "collection_name": "video-to-keyframes",
        "source": {"type": "bucket", "bucket_ids": [bucket["bucket_id"]]},
        "feature_extractor": {"feature_extractor_name": "multimodal_extractor", "version": "v1"},
    }).json()
    
    # 4. run extraction over the bucket
    requests.post(f"{API}/v1/buckets/{bucket['bucket_id']}/batches", headers=H, json={
        "collection_ids": [collection["collection_id"]],
        "auto_submit": True,
    })
    
    # 5. read the output
    docs = requests.get(
        f"{API}/v1/collections/{collection['collection_id']}/documents", headers=H
    ).json()
    print(docs)

    Use Cases

    Build visual indexes for video libraries
    Generate storyboards for film and advertising review
    Create thumbnail galleries for e-learning platforms
    Power visual search across video catalogs

    Supported Input Formats

    MP4
    MOV
    AVI
    MKV
    WebM

    Quick Info

    Categorymedia
    Max File Size5 GB
    Est. Time1-5 min per hour of video

    Processing millions of hours of video?

    Run this as a managed pipeline over your entire video archive, no infrastructure to build or maintain. Talk to us about processing at scale.

    Run it over a library

    Mixpeek runs this conversion as a pipeline over a whole library in your object storage, with the output landing as queryable documents. It is not a single-file converter.

    Frequently Asked Questions

    Ready to convert video to images?

    Start using the Mixpeek Video to Keyframes in minutes. Sign up for a free API key and follow the documentation to get started.