Model API'si

Birefnet Background Removal V2

BiRefNet V2 ile nesneyi arka plandan ayırabilirsin.

Model kimliği

Her istekte bunu kullan

birefnet/v2

Çalıştır

Girdiye ücret teklifi al, bu teklifle üretimi başlat, ardından işin durumunu sorgula. Önce RAYWAKE_API_KEY değişkenini ayarla; ayrıntılar için Kimlik doğrulama sayfasına bak.

# 1. Price the exact input (quotes are valid for up to 10 minutes)
curl -s https://api.raywake.com/v1/quotes \
  -H "Authorization: Bearer $RAYWAKE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "birefnet/v2",
  "input": {
    "image_url": "https://example.com/input.png"
  }
}'

# 2. Start the generation with the quote_id from step 1
curl -s https://api.raywake.com/v1/generate \
  -H "Authorization: Bearer $RAYWAKE_API_KEY" \
  -H "Content-Type: application/json" \
  -H "Idempotency-Key: $(uuidgen)" \
  -d '{"model": "birefnet/v2", "quote_id": "QUOTE_ID", "input": {"image_url":"https://example.com/input.png"}}'

# 3. Poll until the status is terminal
curl -s https://api.raywake.com/v1/jobs/JOB_ID \
  -H "Authorization: Bearer $RAYWAKE_API_KEY"

Girdi

birefnet/v2 girdi alanları
Alan	Tür	Açıklama
`model`	string (enum)	Model to use for background removal. The 'General Use (Light)' model is the original model used in the BiRefNet repository. The 'General Use (Light 2K)' model is the original model used in the BiRefNet repository but trained with 2K images. The 'General Use (Heavy)' model is a slower but more accurate model. The 'Matting' model is a model trained specifically for matting images. The 'Portrait' model is a model trained specifically for portrait images. The 'General Use (Dynamic)' model supports dynamic resolutions from 256x256 to 2304x2304. The 'General Use (Light)' model is recommended for most use cases. The corresponding models are as follows: - 'General Use (Light)': BiRefNet - 'General Use (Light 2K)': BiRefNet_lite-2K - 'General Use (Heavy)': BiRefNet_lite - 'Matting': BiRefNet-matting - 'Portrait': BiRefNet-portrait - 'General Use (Dynamic)': BiRefNet_dynamic Varsayılan: `General Use (Light)` Seçenekler: `General Use (Light)`, `General Use (Light 2K)`, `General Use (Heavy)`, `Matting`, `Portrait`, `General Use (Dynamic)`
`operating_resolution`	string (enum)	The resolution to operate on. The higher the resolution, the more accurate the output will be for high res input images. The '2304x2304' option is only available for the 'General Use (Dynamic)' model. Varsayılan: `1024x1024` Seçenekler: `1024x1024`, `2048x2048`, `2304x2304`
`output_mask`	boolean	Whether to output the mask used to remove the background Varsayılan: `false`
`refine_foreground`	boolean	Whether to refine the foreground using the estimated mask Varsayılan: `true`
`sync_mode`	boolean	If `True`, the media will be returned as a data URI and the output data won't be available in the request history. Varsayılan: `false`
`image_url`zorunlu	string (image URL)	URL of the image to remove background from
`output_format`	string (enum)	The format of the output image Varsayılan: `png` Seçenekler: `webp`, `png`, `gif`
`mask_only`	boolean	Whether to return only the segmentation mask without applying it to the image. When set to `True`, only the mask will be returned and foreground refinement will be skipped. Useful for reducing computation and data transfer when only the mask is needed. Varsayılan: `false`

Çıktı

Başarılı bir iş, sonuçlarını outputs altında listeler; dosyalar bizim tarafımızda saklanır. Tüm alanlar için İşler sayfasına bak.

İş yanıtından bir bölüm

"outputs": [
  { "type": "image", "url": "https://…", "mime_type": "image/png", "thumbnail_url": "https://…" }
]

Fiyatlandırma

en fazla$0,28/ üretim

Girdinin kesin ücreti ücret teklifinden gelir. Bakiye nasıl kesinleşir?