awesome-genmedia Z Image | Turbo | Controlnet
Generate images guided by ControlNet conditioning using turbo-speed inference. Supports canny edge, depth, and pose preprocessing modes with configurable control strength and timing.
Quick Start
Requires an each::labs API key. Get one at eachlabs.ai.
curl -X POST https://api.eachlabs.ai/v1/prediction \
-H "Content-Type: application/json" \
-H "X-API-Key: $EACHLABS_API_KEY" \
-d '{
"model": "z-image-turbo-controlnet",
"version": "0.0.1",
"input": {
"prompt": "a futuristic cityscape at sunset, cyberpunk style",
"image_url": "https://example.com/reference.jpg",
"preprocess": "canny",
"control_scale": 0.9,
"image_size": "landscape_16_9",
"num_inference_steps": 8
}
}'
Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
| acceleration | string | none | The acceleration level to use. enum: none, regular, high |
| control_end | number | 0.4 | The end of the controlnet conditioning. |
| control_scale | number | 0.9 | The scale of the controlnet conditioning. |
| control_start | number | 0 | The start of the controlnet conditioning. |
| enable_prompt_expansion | boolean | false | Whether to enable prompt expansion. Increases price by 0.0025. |
| enable_safety_checker | boolean | true | If set to true, the safety checker will be enabled. |
| image_size | string | auto | The size of the generated image. enum: square_hd, square, portrait_4_3, portrait_16_9, landscape_4_3, landscape_16_9, auto |
| image_url | string | URL of Image for ControlNet generation. | |
| num_images | integer | 1 | The number of images to generate. |
| num_inference_steps | integer | 8 | The number of inference steps to perform. |
| output_format | string | png | The format of the generated image. enum: jpeg, png, webp |
| preprocess | string | none | What kind of preprocessing to apply to the image. enum: none, canny, depth, pose |
| prompt | string | The prompt to generate an image from. | |
| seed | integer | The same seed and prompt produce the same output. |
Examples
Canny edge-guided generation:
curl -X POST https://api.eachlabs.ai/v1/prediction \
-H "Content-Type: application/json" \
-H "X-API-Key: $EACHLABS_API_KEY" \
-d '{
"model": "z-image-turbo-controlnet",
"version": "0.0.1",
"input": {
"prompt": "elegant watercolor painting of a garden",
"image_url": "https://example.com/garden-photo.jpg",
"preprocess": "canny",
"control_scale": 0.8,
"control_start": 0,
"control_end": 0.5,
"image_size": "square_hd",
"output_format": "png"
}
}'
Depth-guided generation with acceleration:
curl -X POST https://api.eachlabs.ai/v1/prediction \
-H "Content-Type: application/json" \
-H "X-API-Key: $EACHLABS_API_KEY" \
-d '{
"model": "z-image-turbo-controlnet",
"version": "0.0.1",
"input": {
"prompt": "a snowy mountain village, highly detailed",
"image_url": "https://example.com/village.jpg",
"preprocess": "depth",
"acceleration": "high",
"control_scale": 0.7,
"num_images": 2,
"image_size": "landscape_4_3"
}
}'
Pose-guided generation:
curl -X POST https://api.eachlabs.ai/v1/prediction \
-H "Content-Type: application/json" \
-H "X-API-Key: $EACHLABS_API_KEY" \
-d '{
"model": "z-image-turbo-controlnet",
"version": "0.0.1",
"input": {
"prompt": "professional dancer in a flowing red dress, studio lighting",
"image_url": "https://example.com/pose-reference.jpg",
"preprocess": "pose",
"control_scale": 0.9,
"image_size": "portrait_4_3",
"seed": 42
}
}'
Related Models
- Z Image | Turbo | Text to Image - Text-only image generation without ControlNet
- Z Image | Turbo | Image to Image - Image-to-image transformation