timothybrooks/instruct-pix2pix:30c1d0b9 – Run with an API on Replicate

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timothybrooks /instruct-pix2pix:30c1d0b9

Playground API

Input

image

*file

An image which will be repainted according to prompt

prompt

*string

Shift + Return to add a new line

Prompt to guide the image generation

negative_prompt

string

Shift + Return to add a new line

The prompt or prompts not to guide the image generation (what you do not want to see in the generation). Ignored when not using guidance.

num_outputs

integer

Number of images to output

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: 100

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

image_guidance_scale

number

(minimum: 1)

Image guidance scale is to push the generated image towards the inital image. Higher image guidance scale encourages to generate images that are closely linked to the source image, usually at the expense of lower image quality.

Default: 1.5

scheduler

string

Choose a scheduler.

Default: "K_EULER_ANCESTRAL"

seed

integer

Random seed. Leave blank to randomize the seed

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

npx create-replicate --model=timothybrooks/instruct-pix2pix

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 timothybrooks/instruct-pix2pix using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "timothybrooks/instruct-pix2pix:30c1d0b916a6f8efce20493f5d61ee27491ab2a60437c13c588468b9810ec23f",
  {
    input: {
      image: "https://replicate.delivery/pbxt/IBnrzJD8Vvz3rD7yF5W8ODnpeA5wcoNpP1RRiDutqW1nG8eF/example.jpeg",
      prompt: "turn him into cyborg",
      scheduler: "K_EULER_ANCESTRAL",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 100,
      image_guidance_scale: 1.5
    }
  }
);
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 timothybrooks/instruct-pix2pix using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "timothybrooks/instruct-pix2pix:30c1d0b916a6f8efce20493f5d61ee27491ab2a60437c13c588468b9810ec23f",
    input={
        "image": "https://replicate.delivery/pbxt/IBnrzJD8Vvz3rD7yF5W8ODnpeA5wcoNpP1RRiDutqW1nG8eF/example.jpeg",
        "prompt": "turn him into cyborg",
        "scheduler": "K_EULER_ANCESTRAL",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 100,
        "image_guidance_scale": 1.5
    }
)
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 timothybrooks/instruct-pix2pix 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": "30c1d0b916a6f8efce20493f5d61ee27491ab2a60437c13c588468b9810ec23f",
    "input": {
      "image": "https://replicate.delivery/pbxt/IBnrzJD8Vvz3rD7yF5W8ODnpeA5wcoNpP1RRiDutqW1nG8eF/example.jpeg",
      "prompt": "turn him into cyborg",
      "scheduler": "K_EULER_ANCESTRAL",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 100,
      "image_guidance_scale": 1.5
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Install Cog

brew install cog

If you don’t have Homebrew, there are other installation options available.

Pull and run timothybrooks/instruct-pix2pix using Cog (this will download the full model and run it in your local environment):

cog predict r8.im/timothybrooks/instruct-pix2pix@sha256:30c1d0b916a6f8efce20493f5d61ee27491ab2a60437c13c588468b9810ec23f \
  -i 'image="https://replicate.delivery/pbxt/IBnrzJD8Vvz3rD7yF5W8ODnpeA5wcoNpP1RRiDutqW1nG8eF/example.jpeg"' \
  -i 'prompt="turn him into cyborg"' \
  -i 'scheduler="K_EULER_ANCESTRAL"' \
  -i 'num_outputs=1' \
  -i 'guidance_scale=7.5' \
  -i 'num_inference_steps=100' \
  -i 'image_guidance_scale=1.5'

To learn more, take a look at the Cog documentation.

Pull and run timothybrooks/instruct-pix2pix using Docker (this will download the full model and run it in your local environment):

docker run -d -p 5000:5000 --gpus=all r8.im/timothybrooks/instruct-pix2pix@sha256:30c1d0b916a6f8efce20493f5d61ee27491ab2a60437c13c588468b9810ec23f
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "image": "https://replicate.delivery/pbxt/IBnrzJD8Vvz3rD7yF5W8ODnpeA5wcoNpP1RRiDutqW1nG8eF/example.jpeg",
      "prompt": "turn him into cyborg",
      "scheduler": "K_EULER_ANCESTRAL",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 100,
      "image_guidance_scale": 1.5
    }
  }' \
  http://localhost:5000/predictions

Output

{
  "completed_at": "2023-01-24T00:12:09.338020Z",
  "created_at": "2023-01-24T00:12:01.075581Z",
  "data_removed": false,
  "error": null,
  "id": "j5myyosmjbcpjcqesowun6idie",
  "input": {
    "image": "https://replicate.delivery/pbxt/IBnrzJD8Vvz3rD7yF5W8ODnpeA5wcoNpP1RRiDutqW1nG8eF/example.jpeg",
    "prompt": "turn him into cyborg",
    "scheduler": "K_EULER_ANCESTRAL",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 100,
    "image_guidance_scale": 1.5
  },
  "logs": "Using seed: 49287\n  0%|          | 0/100 [00:00<?, ?it/s]\n  2%|▏         | 2/100 [00:00<00:08, 11.55it/s]\n  4%|▍         | 4/100 [00:00<00:07, 13.57it/s]\n  6%|▌         | 6/100 [00:00<00:06, 14.33it/s]\n  8%|▊         | 8/100 [00:00<00:06, 14.36it/s]\n 10%|█         | 10/100 [00:00<00:06, 14.37it/s]\n 12%|█▏        | 12/100 [00:00<00:06, 14.28it/s]\n 14%|█▍        | 14/100 [00:01<00:06, 13.74it/s]\n 16%|█▌        | 16/100 [00:01<00:06, 13.40it/s]\n 18%|█▊        | 18/100 [00:01<00:06, 13.54it/s]\n 20%|██        | 20/100 [00:01<00:05, 13.78it/s]\n 22%|██▏       | 22/100 [00:01<00:05, 14.24it/s]\n 24%|██▍       | 24/100 [00:01<00:05, 14.35it/s]\n 26%|██▌       | 26/100 [00:01<00:05, 14.23it/s]\n 28%|██▊       | 28/100 [00:02<00:05, 14.06it/s]\n 30%|███       | 30/100 [00:02<00:04, 14.07it/s]\n 32%|███▏      | 32/100 [00:02<00:04, 14.57it/s]\n 34%|███▍      | 34/100 [00:02<00:04, 14.28it/s]\n 36%|███▌      | 36/100 [00:02<00:04, 14.23it/s]\n 38%|███▊      | 38/100 [00:02<00:04, 14.30it/s]\n 40%|████      | 40/100 [00:02<00:04, 14.16it/s]\n 42%|████▏     | 42/100 [00:02<00:04, 14.41it/s]\n 44%|████▍     | 44/100 [00:03<00:03, 14.42it/s]\n 46%|████▌     | 46/100 [00:03<00:03, 14.46it/s]\n 48%|████▊     | 48/100 [00:03<00:03, 14.72it/s]\n 50%|█████     | 50/100 [00:03<00:03, 14.77it/s]\n 52%|█████▏    | 52/100 [00:03<00:03, 14.87it/s]\n 54%|█████▍    | 54/100 [00:03<00:03, 14.31it/s]\n 56%|█████▌    | 56/100 [00:03<00:02, 14.74it/s]\n 58%|█████▊    | 58/100 [00:04<00:02, 14.89it/s]\n 60%|██████    | 60/100 [00:04<00:02, 15.05it/s]\n 62%|██████▏   | 62/100 [00:04<00:02, 15.12it/s]\n 64%|██████▍   | 64/100 [00:04<00:02, 15.25it/s]\n 66%|██████▌   | 66/100 [00:04<00:02, 15.39it/s]\n 68%|██████▊   | 68/100 [00:04<00:02, 15.39it/s]\n 70%|███████   | 70/100 [00:04<00:01, 15.48it/s]\n 72%|███████▏  | 72/100 [00:04<00:01, 15.60it/s]\n 74%|███████▍  | 74/100 [00:05<00:01, 15.86it/s]\n 76%|███████▌  | 76/100 [00:05<00:01, 15.79it/s]\n 78%|███████▊  | 78/100 [00:05<00:01, 15.65it/s]\n 80%|████████  | 80/100 [00:05<00:01, 15.12it/s]\n 82%|████████▏ | 82/100 [00:05<00:01, 15.35it/s]\n 84%|████████▍ | 84/100 [00:05<00:01, 15.28it/s]\n 86%|████████▌ | 86/100 [00:05<00:00, 15.38it/s]\n 88%|████████▊ | 88/100 [00:05<00:00, 15.53it/s]\n 90%|█████████ | 90/100 [00:06<00:00, 15.26it/s]\n 92%|█████████▏| 92/100 [00:06<00:00, 14.85it/s]\n 94%|█████████▍| 94/100 [00:06<00:00, 14.59it/s]\n 96%|█████████▌| 96/100 [00:06<00:00, 14.70it/s]\n 98%|█████████▊| 98/100 [00:06<00:00, 14.25it/s]\n100%|██████████| 100/100 [00:06<00:00, 14.10it/s]\n100%|██████████| 100/100 [00:06<00:00, 14.61it/s]",
  "metrics": {
    "predict_time": 8.209128,
    "total_time": 8.262439
  },
  "output": [
    "https://replicate.delivery/pbxt/kfL8fyBkHllh4kfEJbulrcnzWywUzZ2Fl1GkpXlb4n8xiaugA/out-0.png"
  ],
  "started_at": "2023-01-24T00:12:01.128892Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/j5myyosmjbcpjcqesowun6idie",
    "cancel": "https://api.replicate.com/v1/predictions/j5myyosmjbcpjcqesowun6idie/cancel"
  },
  "version": "30c1d0b916a6f8efce20493f5d61ee27491ab2a60437c13c588468b9810ec23f"
}

Generated in

8.2 seconds

Tweak itReport

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