I use MicroSoft Video indexer to run Video intelligence and extract useful features/contents from user video inputs. I've been using the web interface, but now I'm needing to automate this by using the Rest API.
There are 2 approaches to specifying the video file to upload. One is ingesting raw bytes and the other is citing the address of a video file on the cloud (recommended). See the API doc.
The problem is that I'm having issues specifying a file on Google Cloud Storage bucket. I understand that you have to specify the URL of a publicly available file, which I'm doing by providing the signedURL of the video file. But it keeps giving me the error below which doesn't happen when I specify the address of the same video file uploaded to Cloudinary.
{
"ErrorType": "INVALID_INPUT",
"Message": "Url content type 'application/xml' is not supported. Only audio and video files are supported. You can find the supported types here: https://learn.microsoft.com/ro-ro/azure/media-services/media-services-media-encoder-standard-formats. Trace id: '7e9e2626-6dd3-4e9b-8b06-5991cfdb896c"
}
For reference, here are the 2 addresses:
I can provide the actual URL if you're needing to test it.
Ok, I solved this by encoding the query params path of the signedURL gotten from GCS before adding it to the videoUrl params sent to MicroSoft Video Indexer (MVI)
const temp = signedURL.split('?')
videoUrl = temp[0] + encodeURIComponent(`?${temp[1]}`)
This is because MVI runs decodeURIComponent on the videoUrl - thus the goal is to make the result equal to the original url sent by GCS:
const bucketFile = bucket.file(filePath)
const [signedURL] = await bucketFile.getSignedUrl({
action: 'read',
expires: 3600 * 1000, // 1hr or add-your-expiration,
})