Advanced female human character generator producing realistic, diverse, and highly detailed female portraits. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Ожидание
$0.015за запуск·~66 / $1
ПримерыСмотреть всё
An enigmatic woman with piercing emerald green eyes. Her long, dark, braided hair is adorned with intricate silver runes. She wears a flowing, dark velvet cloak, partially obscuring her face. Standing in a dimly lit, ancient stone ruins, with misty fog swirling around her feet. Dramatic backlighting, deep shadows, rich jewel tones, cinematic, dark fantasy art, 8K.
A captivating young woman, elegant and poised. Her eyes, filled with depth, gaze directly at the viewer. She has flowing, soft waves of dark hair and subtle, natural makeup. Wearing a delicate, ethereal silk gown. Shot in a soft, warm studio light with shallow depth of field, subtle bokeh background. Golden hour tones, highly detailed, cinematic portrait, 8K, photorealistic.
A striking cyberpunk woman, confident and edgy. Her short, electric blue hair glows softly under neon city lights. She has intricate facial tattoos and a small, subtle data implant near her ear. Wearing a jacket. Shot at night in a bustling, rainy futuristic city street. Dynamic lighting, high contrast, atmospheric, volumetric fog, digital art, 4K.
A radiant woman, naturally beautiful with a gentle smile. Her long, sun-kissed blonde hair flows in a light breeze. She wears a simple, bohemian-style white linen dress. Set against a blurred backdrop of a sunlit lavender field at sunset. Soft, diffused natural light, warm pastel colors, authentic, dreamlike, film grain, 8K.
A chic, modern woman with a sharp, angular bob haircut. Her expression is cool and composed. She wears an oversized, tailored charcoal grey blazer, emphasizing clean lines. Posed in a minimalist architectural interior with geometric shapes and soft, indirect lighting. Clean lines, editorial photography, high fashion, neutral color palette, crisp details, 8K.
Похожие модели
Female Human API — Quick start
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/female-human with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Female Human below.
HTTP example
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/female-human" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "1024*1024",
"seed": -1,
"output_format": "jpeg",
"enable_base64_output": false,
"enable_sync_mode": false
}'
# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
-H "Authorization: Bearer $WAVESPEED_API_KEY"
# When status is "completed", read the output from data.outputs[0].Node.js example
// npm install wavespeed
const WaveSpeed = require('wavespeed');
const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env
const result = await client.run("wavespeed-ai/female-human", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "1024*1024",
"seed": -1,
"output_format": "jpeg",
"enable_base64_output": false,
"enable_sync_mode": false
});
console.log(result.outputs[0]); // → URL of the generated outputPython example
# pip install wavespeed
import wavespeed
output = wavespeed.run(
"wavespeed-ai/female-human",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "1024*1024",
"seed": -1,
"output_format": "jpeg",
"enable_base64_output": false,
"enable_sync_mode": false
}
)
print(output["outputs"][0]) # → URL of the generated outputFemale Human API — Frequently asked questions
What is the Female Human API?
Female Human is a WaveSpeedAI model for image generation, exposed as a REST API on WaveSpeedAI. Advanced female human character generator producing realistic, diverse, and highly detailed female portraits. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
How do I call the Female Human API?
POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/female-human.
How much does Female Human cost per run?
Female Human starts at $0.015 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.
What inputs does Female Human accept?
Key inputs: `prompt`, `size`, `seed`, `enable_base64_output`, `enable_sync_mode`, `output_format`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/wavespeed-ai/female-human.
How long does Female Human take to generate?
Average end-to-end generation time on WaveSpeedAI is around 8 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.
Can I use Female Human outputs commercially?
Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.