Photo Upload

const result = await mediaviz.photoUpload.uploadPhoto(
  '<PROJECT_TABLE_NAME>',
  '<COMPANY_ID>',
  '<USER_ID>',
  '<PHOTO_INDEX>',
  '<PHOTO>'
);

const result = await mediaviz.photoUpload.uploadPhoto(
  '<PROJECT_TABLE_NAME>',
  '<COMPANY_ID>',
  '<USER_ID>',
  '<PHOTO_INDEX>',
  '<PHOTO>'
);

const result = await mediaviz.photoUpload.uploadPhoto(
  '<PROJECT_TABLE_NAME>',
  '<COMPANY_ID>',
  '<USER_ID>',
  '<PHOTO_INDEX>',
  '<PHOTO>'
);

result = mediaviz.photo_upload.upload_photo(
    '<PROJECT_TABLE_NAME>',
    '<COMPANY_ID>',
    '<USER_ID>',
    '<PHOTO_INDEX>',
    '<PHOTO>'
)

$result = $mediaviz->photoUpload->uploadPhoto(
  '<PROJECT_TABLE_NAME>',
  '<COMPANY_ID>',
  '<USER_ID>',
  '<PHOTO_INDEX>',
  '<PHOTO>'
);

# Step 1: get_project_prelim_model_request_template
curl -X GET 'https://api.mediaviz.ai/api/v1/project_outcome/<PROJECT_TABLE_NAME>' \
  -H 'Authorization: Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VyX2lkIjoidXNyXzAxYWJjMTIzIiwiZXhwIjoxNzQzNjMwMzI5fQ.RwJF-KLLr8K5JgEtIeFiKWELcv-FDLNzMPHJ2St_wAo'

# Step 2: Upload a preprocessed photo with metadata via headers
curl -X POST 'https://upload.mediaviz.ai/photo_upload' \
  -H 'Authorization: Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VyX2lkIjoidXNyXzAxYWJjMTIzIiwiZXhwIjoxNzQzNjMwMzI5fQ.RwJF-KLLr8K5JgEtIeFiKWELcv-FDLNzMPHJ2St_wAo' \
  -H 'x-company-id: <COMPANY_ID>' \
  -H 'x-user-id: <USER_ID>' \
  -H 'x-project-table-name: <PROJECT_TABLE_NAME>' \
  -H 'x-title: <TITLE>' \
  -H 'Content-Type: application/json' \
  --data @- <<'JSON'
{
  "file_content": "<FILE_CONTENT>",
  "mimetype": "<MIMETYPE>",
  "file_path": "<FILE_PATH>"
}
JSON

const result = await mediaviz.photoUpload.uploadPhotoToMediaviz(
  '<COMPANY_ID>',
  '<USER_ID>',
  '<PROJECT_TABLE_NAME>',
  '<TITLE>',
  {
    fileContent: '<FILE_CONTENT>',
    mimetype: '<MIMETYPE>',
    filePath: '<FILE_PATH>'
  },
  {
    clientSideId: '<CLIENT_SIDE_ID>',
    blur: '<BLUR>',
    colors: '<COLORS>',
    faceRecognition: '<FACE_RECOGNITION>',
    imageDescribe: '<IMAGE_DESCRIBE>',
    imageClassification: '<IMAGE_CLASSIFICATION>',
    imageComparison: '<IMAGE_COMPARISON>',
    size: '<SIZE>',
    sourceResolutionX: '<SOURCE_RESOLUTION_X>',
    sourceResolutionY: '<SOURCE_RESOLUTION_Y>',
    dateTaken: '<DATE_TAKEN>',
    latitude: '<LATITUDE>',
    longitude: '<LONGITUDE>',
    ocr: '<OCR>'
  }
);

const result = await mediaviz.photoUpload.uploadPhotoToMediaviz(
  '<COMPANY_ID>',
  '<USER_ID>',
  '<PROJECT_TABLE_NAME>',
  '<TITLE>',
  {
    fileContent: '<FILE_CONTENT>',
    mimetype: '<MIMETYPE>',
    filePath: '<FILE_PATH>'
  },
  {
    clientSideId: '<CLIENT_SIDE_ID>',
    blur: '<BLUR>',
    colors: '<COLORS>',
    faceRecognition: '<FACE_RECOGNITION>',
    imageDescribe: '<IMAGE_DESCRIBE>',
    imageClassification: '<IMAGE_CLASSIFICATION>',
    imageComparison: '<IMAGE_COMPARISON>',
    size: '<SIZE>',
    sourceResolutionX: '<SOURCE_RESOLUTION_X>',
    sourceResolutionY: '<SOURCE_RESOLUTION_Y>',
    dateTaken: '<DATE_TAKEN>',
    latitude: '<LATITUDE>',
    longitude: '<LONGITUDE>',
    ocr: '<OCR>'
  }
);

const result = await mediaviz.photoUpload.uploadPhotoToMediaviz(
  '<COMPANY_ID>',
  '<USER_ID>',
  '<PROJECT_TABLE_NAME>',
  '<TITLE>',
  {
    fileContent: '<FILE_CONTENT>',
    mimetype: '<MIMETYPE>',
    filePath: '<FILE_PATH>'
  },
  {
    clientSideId: '<CLIENT_SIDE_ID>',
    blur: '<BLUR>',
    colors: '<COLORS>',
    faceRecognition: '<FACE_RECOGNITION>',
    imageDescribe: '<IMAGE_DESCRIBE>',
    imageClassification: '<IMAGE_CLASSIFICATION>',
    imageComparison: '<IMAGE_COMPARISON>',
    size: '<SIZE>',
    sourceResolutionX: '<SOURCE_RESOLUTION_X>',
    sourceResolutionY: '<SOURCE_RESOLUTION_Y>',
    dateTaken: '<DATE_TAKEN>',
    latitude: '<LATITUDE>',
    longitude: '<LONGITUDE>',
    ocr: '<OCR>'
  }
);

result = mediaviz.photo_upload.upload_photo_to_mediaviz(
    '<COMPANY_ID>',
    '<USER_ID>',
    '<PROJECT_TABLE_NAME>',
    '<TITLE>',
    file_content='<FILE_CONTENT>',
    mimetype='<MIMETYPE>',
    file_path='<FILE_PATH>',
    client_side_id='<CLIENT_SIDE_ID>',
    blur='<BLUR>',
    colors='<COLORS>',
    face_recognition='<FACE_RECOGNITION>',
    image_describe='<IMAGE_DESCRIBE>',
    image_classification='<IMAGE_CLASSIFICATION>',
    image_comparison='<IMAGE_COMPARISON>',
    size='<SIZE>',
    source_resolution_x='<SOURCE_RESOLUTION_X>',
    source_resolution_y='<SOURCE_RESOLUTION_Y>',
    date_taken='<DATE_TAKEN>',
    latitude='<LATITUDE>',
    longitude='<LONGITUDE>',
    ocr='<OCR>'
)

$result = $mediaviz->photoUpload->uploadPhotoToMediaviz(
  '<COMPANY_ID>',
  '<USER_ID>',
  '<PROJECT_TABLE_NAME>',
  '<TITLE>',
  [
    'fileContent' => '<FILE_CONTENT>',
    'mimetype' => '<MIMETYPE>',
    'filePath' => '<FILE_PATH>'
  ],
  [
    'clientSideId' => '<CLIENT_SIDE_ID>',
    'blur' => '<BLUR>',
    'colors' => '<COLORS>',
    'faceRecognition' => '<FACE_RECOGNITION>',
    'imageDescribe' => '<IMAGE_DESCRIBE>',
    'imageClassification' => '<IMAGE_CLASSIFICATION>',
    'imageComparison' => '<IMAGE_COMPARISON>',
    'size' => '<SIZE>',
    'sourceResolutionX' => '<SOURCE_RESOLUTION_X>',
    'sourceResolutionY' => '<SOURCE_RESOLUTION_Y>',
    'dateTaken' => '<DATE_TAKEN>',
    'latitude' => '<LATITUDE>',
    'longitude' => '<LONGITUDE>',
    'ocr' => '<OCR>'
  ]
);

curl -X POST 'https://upload.mediaviz.ai/photo_upload' \
  -H 'Authorization: Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VyX2lkIjoidXNyXzAxYWJjMTIzIiwiZXhwIjoxNzQzNjMwMzI5fQ.RwJF-KLLr8K5JgEtIeFiKWELcv-FDLNzMPHJ2St_wAo' \
  -H 'x-company-id: <COMPANY_ID>' \
  -H 'x-user-id: <USER_ID>' \
  -H 'x-project-table-name: <PROJECT_TABLE_NAME>' \
  -H 'x-title: <TITLE>' \
  -H 'x-blur: true' \
  -H 'x-colors: true' \
  -H 'x-face-recognition: true' \
  -H 'x-image-describe: false' \
  -H 'x-image-classification: true' \
  -H 'x-image-comparison: true' \
  -H 'x-ocr: false' \
  -H 'Content-Type: application/json' \
  --data @- <<'JSON'
{
  "file_content": "<FILE_CONTENT>",
  "mimetype": "<MIMETYPE>",
  "file_path": "<FILE_PATH>"
}
JSON