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What is Search?

Search lets you locate exact moments across thousands of hours of video using natural language or an image reference. Results are split into three specialized buckets—embeddings, transcript, and ocr— So you can quickly see why something matched. The path to use search: 
core/search
To search with natural language: 
resp = moonshine.run(
    flow="core/search",
    index="your-index-name",
    query="your search query, ex: red car",
    num_args=10  # optional, defaults to 5
)
Where num_args are the max number of results returned and is optional. To search with an image: 
resp = moonshine.run(
    flow="core/search",
    image="./reference.png",  # local path or public URL
    image="path/to/image.jpg",
)
If both an image and query are supplied, the image will take precedence. Using a Subindex will isolate a search a subset of the videos in an index. To use it: 
resp = moonshine.run(
    flow="core/search",
    index="your-index-name",
    query="your search query, ex: red car",
    subindex=[
        "FHXYU838JHDWK.mp4",
        "AJDIEUJDKSLW.mp4"
    ],
)
where the subindex is a list of video IDs to search within.

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Search Response Format

Search returns a list of match objects. The match object schema is:
​
[0]
string
Moonshine-assigned file_ide.g. FHXYU838JHDWK.mp4
for match in resp["output"]["embeddings"]:
    file_id      = match[0]
    start_frame  = match[1]
    end_frame    = match[2]
    start_time   = match[3]
    end_time     = match[4]

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Search JSON

Workflows are in a private beta. Please contact us at team@usemoonshine.com to request access.
​
index
string
required
Name/ID of the parent index to search.
​
query
string
Natural-language text.
Ignored if image is supplied.
​
image
string
Local file path or public URL to an image used as the search reference.
​
subindex
List[str]
An optional list of file_idto narrow the search scope.
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num_args
int
Max results per result-type bucket.