jagilley/stable-diffusion-depth2img:68f699d3 – Run with an API on Replicate

Version

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jagilley /stable-diffusion-depth2img:68f699d3

Input

prompt

string

Shift + Return to add a new line

wanderer above a cyberpunk city, 4k digital art rendering by caspar david friedrichwanderer above a cyberpunk city, 4k digital art rendering by caspar david friedrich

The prompt to guide the image generation.

Default: "Wanderer above the sea of fog, digital art"

negative_prompt

string

Shift + Return to add a new line

Keywords to exclude from the resulting image

input_image

*file

Preview

Input image to be used as the starting point

prompt_strength

number

Prompt strength when providing the image. 1.0 corresponds to full destruction of information in init image.

Default: 0.8

num_outputs

integer

(minimum: 1, maximum: 8)

Number of images to generate

Default: 1

num_inference_steps

integer

(minimum: 1, maximum: 500)

The number of denoising steps. More denoising steps usually lead to a higher quality image at the expense of slower inference.

Default: 50

guidance_scale

number

(minimum: 1, maximum: 20)

Scale for classifier-free guidance. Higher guidance scale encourages to generate images that are closely linked to the text prompt, usually at the expense of lower image quality.

Default: 7.5

scheduler

string

Choose a scheduler

Default: "DPMSolverMultistep"

seed

integer

Random seed. Leave blank to randomize the seed

depth_image

file

Depth image (optional). Specifies the depth of each pixel in the input image.

Run this model in Node.js with one line of code:

npx create-replicate --model=jagilley/stable-diffusion-depth2img

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run jagilley/stable-diffusion-depth2img using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jagilley/stable-diffusion-depth2img:68f699d395bc7c17008283a7cef6d92edc832d8dc59eb41a6cafec7fc70b85bc",
  {
    input: {
      seed: -1,
      prompt: "wanderer above a cyberpunk city, 4k digital art rendering by caspar david friedrich",
      scheduler: "DPMSolverMultistep",
      input_image: "https://replicate.delivery/pbxt/ICo443xcFQGIK4lawWN3ytMNDZsmZS6fZfjGYwFP6Dc5Vfnq/wanderer.jpeg",
      num_outputs: 1,
      guidance_scale: 7.5,
      prompt_strength: 0.8,
      num_inference_steps: 50
    }
  }
);
console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run jagilley/stable-diffusion-depth2img using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jagilley/stable-diffusion-depth2img:68f699d395bc7c17008283a7cef6d92edc832d8dc59eb41a6cafec7fc70b85bc",
    input={
        "seed": -1,
        "prompt": "wanderer above a cyberpunk city, 4k digital art rendering by caspar david friedrich",
        "scheduler": "DPMSolverMultistep",
        "input_image": "https://replicate.delivery/pbxt/ICo443xcFQGIK4lawWN3ytMNDZsmZS6fZfjGYwFP6Dc5Vfnq/wanderer.jpeg",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "prompt_strength": 0.8,
        "num_inference_steps": 50
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run jagilley/stable-diffusion-depth2img using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "68f699d395bc7c17008283a7cef6d92edc832d8dc59eb41a6cafec7fc70b85bc",
    "input": {
      "seed": -1,
      "prompt": "wanderer above a cyberpunk city, 4k digital art rendering by caspar david friedrich",
      "scheduler": "DPMSolverMultistep",
      "input_image": "https://replicate.delivery/pbxt/ICo443xcFQGIK4lawWN3ytMNDZsmZS6fZfjGYwFP6Dc5Vfnq/wanderer.jpeg",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "prompt_strength": 0.8,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

{
  "completed_at": "2023-01-26T20:01:57.999236Z",
  "created_at": "2023-01-26T20:01:36.420191Z",
  "data_removed": false,
  "error": null,
  "id": "xadvta5lnreybcutg6njr6lulq",
  "input": {
    "seed": -1,
    "prompt": "wanderer above a cyberpunk city, 4k digital art rendering by caspar david friedrich",
    "scheduler": "DPMSolverMultistep",
    "input_image": "https://replicate.delivery/pbxt/ICo443xcFQGIK4lawWN3ytMNDZsmZS6fZfjGYwFP6Dc5Vfnq/wanderer.jpeg",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "prompt_strength": 0.8,
    "num_inference_steps": 50
  },
  "logs": "Using seed: -1\n  0%|          | 0/40 [00:00<?, ?it/s]\n  2%|▎         | 1/40 [00:04<03:14,  4.99s/it]\n  8%|▊         | 3/40 [00:05<00:49,  1.35s/it]\n 12%|█▎        | 5/40 [00:05<00:24,  1.46it/s]\n 18%|█▊        | 7/40 [00:05<00:13,  2.37it/s]\n 22%|██▎       | 9/40 [00:05<00:08,  3.48it/s]\n 28%|██▊       | 11/40 [00:05<00:06,  4.78it/s]\n 32%|███▎      | 13/40 [00:05<00:04,  6.23it/s]\n 38%|███▊      | 15/40 [00:05<00:03,  7.75it/s]\n 42%|████▎     | 17/40 [00:06<00:02,  9.23it/s]\n 48%|████▊     | 19/40 [00:06<00:01, 10.56it/s]\n 52%|█████▎    | 21/40 [00:06<00:01, 11.78it/s]\n 57%|█████▊    | 23/40 [00:06<00:01, 12.76it/s]\n 62%|██████▎   | 25/40 [00:06<00:01, 13.49it/s]\n 68%|██████▊   | 27/40 [00:06<00:00, 14.10it/s]\n 72%|███████▎  | 29/40 [00:06<00:00, 14.60it/s]\n 78%|███████▊  | 31/40 [00:06<00:00, 14.96it/s]\n 82%|████████▎ | 33/40 [00:07<00:00, 15.19it/s]\n 88%|████████▊ | 35/40 [00:07<00:00, 15.31it/s]\n 92%|█████████▎| 37/40 [00:07<00:00, 15.46it/s]\n 98%|█████████▊| 39/40 [00:07<00:00, 15.50it/s]\n100%|██████████| 40/40 [00:07<00:00,  5.35it/s]",
  "metrics": {
    "predict_time": 11.80156,
    "total_time": 21.579045
  },
  "output": [
    "https://replicate.delivery/pbxt/7MKZB7KJhVbxL1DKSiDYQ7eInHCKYgBi9zPeKkJbjri14IYQA/out-0.png"
  ],
  "started_at": "2023-01-26T20:01:46.197676Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/xadvta5lnreybcutg6njr6lulq",
    "cancel": "https://api.replicate.com/v1/predictions/xadvta5lnreybcutg6njr6lulq/cancel"
  },
  "version": "d488378e301ffa295b360e6a34e0a504b772449c75f570a9f4e5089d05f660df"
}

Generated in

11.8 seconds

Tweak itReport

This example was created by a different version, jagilley/stable-diffusion-depth2img:d488378e.