afiaka87/ldm-autoedit:d0d04e11 – Run with an API on Replicate

Version

You're looking at a specific version of this model. Jump to the model overview.

afiaka87 /ldm-autoedit:d0d04e11

Playground API

Input

text

string

Shift + Return to add a new line

(required) Text to use for the model's prediction.

Default: ""

edit

file

(optional) an existing image you want to edit

negative

string

Shift + Return to add a new line

(optional) Negate the model's prediction for this text from the model's prediction for the target text.

Default: ""

aesthetic_rating

integer

(minimum: 0, maximum: 9)

Number between 0 and 9 representing the aesthetic rating. Will initialize the prompt CLIP embed with the respective aesthetic embed.

Default: 9

aesthetic_weight

number

(minimum: 0, maximum: 1)

Weight of the aesthetic embedding in the average prompt embedding.

Default: 0.5

batch_size

integer

(minimum: 1, maximum: 32)

Batch size.

Default: 1

width

integer

Target width

Default: 256

height

integer

Target height

Default: 256

iterations

integer

(minimum: 1, maximum: 30)

Number of iterations to run the model for.

Default: 10

starting_radius

number

(minimum: 0.1)

size of noise blur at the start of editing (larger = coarser changes)

Default: 5

ending_radius

number

(minimum: 0.1, maximum: 5)

size of noise blur at the end of editing (smaller = editing fine details)

Default: 0.1

starting_threshold

number

(minimum: 0.05, maximum: 1)

how much of the image to replace at the start of editing (1 = inpaint the entire image)

Default: 0.6

ending_threshold

number

(minimum: 0.1, maximum: 1)

how much of the image to replace at the end of editing

Default: 0.5

guidance_scale

number

(minimum: -10, maximum: 100)

Controls how much the image should look like the prompt

Default: 5

seed

integer

(minimum: -1)

(optional) Seed for the random number generator.

Default: -1

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

npx create-replicate --model=afiaka87/ldm-autoedit

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 afiaka87/ldm-autoedit using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "afiaka87/ldm-autoedit:d0d04e11830081fcc1066cc5e6306e4ffdcf35c0d95d12c6cbc2b869f17466d0",
  {
    input: {
      seed: -1,
      text: "new york city completely flooded",
      width: 256,
      height: 256,
      negative: "",
      batch_size: 8,
      iterations: 20,
      ending_radius: 0.1,
      guidance_scale: 5,
      starting_radius: 3,
      aesthetic_rating: 9,
      aesthetic_weight: 0.5,
      ending_threshold: 0.5,
      starting_threshold: 0.6
    }
  }
);

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 afiaka87/ldm-autoedit using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "afiaka87/ldm-autoedit:d0d04e11830081fcc1066cc5e6306e4ffdcf35c0d95d12c6cbc2b869f17466d0",
    input={
        "seed": -1,
        "text": "new york city completely flooded",
        "width": 256,
        "height": 256,
        "negative": "",
        "batch_size": 8,
        "iterations": 20,
        "ending_radius": 0.1,
        "guidance_scale": 5,
        "starting_radius": 3,
        "aesthetic_rating": 9,
        "aesthetic_weight": 0.5,
        "ending_threshold": 0.5,
        "starting_threshold": 0.6
    }
)

# The afiaka87/ldm-autoedit model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/afiaka87/ldm-autoedit/api#output-schema
    print(item)

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 afiaka87/ldm-autoedit 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": "afiaka87/ldm-autoedit:d0d04e11830081fcc1066cc5e6306e4ffdcf35c0d95d12c6cbc2b869f17466d0",
    "input": {
      "seed": -1,
      "text": "new york city completely flooded",
      "width": 256,
      "height": 256,
      "negative": "",
      "batch_size": 8,
      "iterations": 20,
      "ending_radius": 0.1,
      "guidance_scale": 5,
      "starting_radius": 3,
      "aesthetic_rating": 9,
      "aesthetic_weight": 0.5,
      "ending_threshold": 0.5,
      "starting_threshold": 0.6
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-06-17T22:12:45.575809Z",
  "created_at": "2022-06-17T19:14:48.140184Z",
  "data_removed": false,
  "error": null,
  "id": "lnri7jpouzdd7c73npp7bt5k5y",
  "input": {
    "seed": -1,
    "text": "new york city completely flooded",
    "width": 256,
    "height": 256,
    "batch_size": "8",
    "iterations": "20",
    "ending_radius": 0.1,
    "guidance_scale": "5",
    "starting_radius": 3,
    "aesthetic_rating": 9,
    "aesthetic_weight": "0.5",
    "ending_threshold": 0.5,
    "starting_threshold": 0.6
  },
  "logs": "Using seed 319970566\nRunning simulation for new york city completely flooded\nEncoding text embeddings with new york city completely flooded dimensions\nUsing aesthetic embedding 9 with weight 0.5\nUsing inpaint model but no image is provided. Initializing with zeros.\nPopulation: 00, batch: 00, score: 0.2321 - first iteration\nPopulation: 00, batch: 01, score: 0.2690 - first iteration\nPopulation: 00, batch: 02, score: 0.2435 - first iteration\nPopulation: 00, batch: 03, score: 0.2721 - first iteration\nPopulation: 00, batch: 04, score: 0.2456 - first iteration\nPopulation: 00, batch: 05, score: 0.2513 - first iteration\nPopulation: 00, batch: 06, score: 0.2099 - first iteration\nPopulation: 00, batch: 07, score: 0.2464 - first iteration\nPopulation: 01, batch: 00, score: 0.2197 - no improvement\nPopulation: 01, batch: 01, score: 0.2195 - no improvement\nPopulation: 01, batch: 02, score: 0.2059 - no improvement\nPopulation: 01, batch: 03, score: 0.2742 - new best, replacing\nPopulation: 01, batch: 04, score: 0.1948 - no improvement\nPopulation: 01, batch: 05, score: 0.2332 - no improvement\nPopulation: 01, batch: 06, score: 0.2409 - new best, replacing\nPopulation: 01, batch: 07, score: 0.1885 - no improvement\nPopulation: 02, batch: 00, score: 0.2307 - no improvement\nPopulation: 02, batch: 01, score: 0.2659 - no improvement\nPopulation: 02, batch: 02, score: 0.2015 - no improvement\nPopulation: 02, batch: 03, score: 0.2596 - no improvement\nPopulation: 02, batch: 04, score: 0.2528 - new best, replacing\nPopulation: 02, batch: 05, score: 0.2577 - new best, replacing\nPopulation: 02, batch: 06, score: 0.2172 - no improvement\nPopulation: 02, batch: 07, score: 0.2784 - new best, replacing\nPopulation: 03, batch: 00, score: 0.2575 - new best, replacing\nPopulation: 03, batch: 01, score: 0.2551 - no improvement\nPopulation: 03, batch: 02, score: 0.2123 - no improvement\nPopulation: 03, batch: 03, score: 0.2359 - no improvement\nPopulation: 03, batch: 04, score: 0.1640 - no improvement\nPopulation: 03, batch: 05, score: 0.2039 - no improvement\nPopulation: 03, batch: 06, score: 0.2175 - no improvement\nPopulation: 03, batch: 07, score: 0.2194 - no improvement\nPopulation: 04, batch: 00, score: 0.2356 - no improvement\nPopulation: 04, batch: 01, score: 0.2373 - no improvement\nPopulation: 04, batch: 02, score: 0.2436 - new best, replacing\nPopulation: 04, batch: 03, score: 0.1799 - no improvement\nPopulation: 04, batch: 04, score: 0.2512 - no improvement\nPopulation: 04, batch: 05, score: 0.2531 - no improvement\nPopulation: 04, batch: 06, score: 0.2440 - new best, replacing\nPopulation: 04, batch: 07, score: 0.2075 - no improvement\nPopulation: 05, batch: 00, score: 0.2042 - no improvement\nPopulation: 05, batch: 01, score: 0.2293 - no improvement\nPopulation: 05, batch: 02, score: 0.2215 - no improvement\nPopulation: 05, batch: 03, score: 0.1763 - no improvement\nPopulation: 05, batch: 04, score: 0.1872 - no improvement\nPopulation: 05, batch: 05, score: 0.2393 - no improvement\nPopulation: 05, batch: 06, score: 0.1795 - no improvement\nPopulation: 05, batch: 07, score: 0.2669 - no improvement\nPopulation: 06, batch: 00, score: 0.2417 - no improvement\nPopulation: 06, batch: 01, score: 0.2546 - no improvement\nPopulation: 06, batch: 02, score: 0.2241 - no improvement\nPopulation: 06, batch: 03, score: 0.2616 - no improvement\nPopulation: 06, batch: 04, score: 0.2387 - no improvement\nPopulation: 06, batch: 05, score: 0.2262 - no improvement\nPopulation: 06, batch: 06, score: 0.1805 - no improvement\nPopulation: 06, batch: 07, score: 0.2203 - no improvement\nPopulation: 07, batch: 00, score: 0.2594 - new best, replacing\nPopulation: 07, batch: 01, score: 0.2134 - no improvement\nPopulation: 07, batch: 02, score: 0.2345 - no improvement\nPopulation: 07, batch: 03, score: 0.1960 - no improvement\nPopulation: 07, batch: 04, score: 0.2309 - no improvement\nPopulation: 07, batch: 05, score: 0.1765 - no improvement\nPopulation: 07, batch: 06, score: 0.2479 - new best, replacing\nPopulation: 07, batch: 07, score: 0.2632 - no improvement\nPopulation: 08, batch: 00, score: 0.2128 - no improvement\nPopulation: 08, batch: 01, score: 0.2006 - no improvement\nPopulation: 08, batch: 02, score: 0.2634 - new best, replacing\nPopulation: 08, batch: 03, score: 0.2098 - no improvement\nPopulation: 08, batch: 04, score: 0.2537 - new best, replacing\nPopulation: 08, batch: 05, score: 0.2092 - no improvement\nPopulation: 08, batch: 06, score: 0.1991 - no improvement\nPopulation: 08, batch: 07, score: 0.2331 - no improvement\nPopulation: 09, batch: 00, score: 0.2534 - no improvement\nPopulation: 09, batch: 01, score: 0.2258 - no improvement\nPopulation: 09, batch: 02, score: 0.2439 - no improvement\nPopulation: 09, batch: 03, score: 0.2231 - no improvement\nPopulation: 09, batch: 04, score: 0.2115 - no improvement\nPopulation: 09, batch: 05, score: 0.1948 - no improvement\nPopulation: 09, batch: 06, score: 0.2480 - new best, replacing\nPopulation: 09, batch: 07, score: 0.2123 - no improvement\nPopulation: 10, batch: 00, score: 0.2416 - no improvement\nPopulation: 10, batch: 01, score: 0.1903 - no improvement\nPopulation: 10, batch: 02, score: 0.1687 - no improvement\nPopulation: 10, batch: 03, score: 0.2367 - no improvement\nPopulation: 10, batch: 04, score: 0.1970 - no improvement\nPopulation: 10, batch: 05, score: 0.2277 - no improvement\nPopulation: 10, batch: 06, score: 0.2293 - no improvement\nPopulation: 10, batch: 07, score: 0.2269 - no improvement\nPopulation: 11, batch: 00, score: 0.2344 - no improvement\nPopulation: 11, batch: 01, score: 0.1815 - no improvement\nPopulation: 11, batch: 02, score: 0.2390 - no improvement\nPopulation: 11, batch: 03, score: 0.2152 - no improvement\nPopulation: 11, batch: 04, score: 0.2705 - new best, replacing\nPopulation: 11, batch: 05, score: 0.2594 - new best, replacing\nPopulation: 11, batch: 06, score: 0.2681 - new best, replacing\nPopulation: 11, batch: 07, score: 0.2214 - no improvement\nPopulation: 12, batch: 00, score: 0.1791 - no improvement\nPopulation: 12, batch: 01, score: 0.1462 - no improvement\nPopulation: 12, batch: 02, score: 0.2466 - no improvement\nPopulation: 12, batch: 03, score: 0.2606 - no improvement\nPopulation: 12, batch: 04, score: 0.2558 - no improvement\nPopulation: 12, batch: 05, score: 0.2077 - no improvement\nPopulation: 12, batch: 06, score: 0.2274 - no improvement\nPopulation: 12, batch: 07, score: 0.1566 - no improvement\nPopulation: 13, batch: 00, score: 0.1646 - no improvement\nPopulation: 13, batch: 01, score: 0.2091 - no improvement\nPopulation: 13, batch: 02, score: 0.2259 - no improvement\nPopulation: 13, batch: 03, score: 0.1968 - no improvement\nPopulation: 13, batch: 04, score: 0.1815 - no improvement\nPopulation: 13, batch: 05, score: 0.2707 - new best, replacing\nPopulation: 13, batch: 06, score: 0.2093 - no improvement\nPopulation: 13, batch: 07, score: 0.2379 - no improvement\nPopulation: 14, batch: 00, score: 0.2417 - no improvement\nPopulation: 14, batch: 01, score: 0.2123 - no improvement\nPopulation: 14, batch: 02, score: 0.2621 - no improvement\nPopulation: 14, batch: 03, score: 0.2265 - no improvement\nPopulation: 14, batch: 04, score: 0.2324 - no improvement\nPopulation: 14, batch: 05, score: 0.2448 - no improvement\nPopulation: 14, batch: 06, score: 0.2493 - no improvement\nPopulation: 14, batch: 07, score: 0.2735 - no improvement\nPopulation: 15, batch: 00, score: 0.2594 - no improvement\nPopulation: 15, batch: 01, score: 0.1612 - no improvement\nPopulation: 15, batch: 02, score: 0.2433 - no improvement\nPopulation: 15, batch: 03, score: 0.2404 - no improvement\nPopulation: 15, batch: 04, score: 0.2012 - no improvement\nPopulation: 15, batch: 05, score: 0.2447 - no improvement\nPopulation: 15, batch: 06, score: 0.2301 - no improvement\nPopulation: 15, batch: 07, score: 0.1743 - no improvement\nPopulation: 16, batch: 00, score: 0.2655 - new best, replacing\nPopulation: 16, batch: 01, score: 0.1834 - no improvement\nPopulation: 16, batch: 02, score: 0.2349 - no improvement\nPopulation: 16, batch: 03, score: 0.2386 - no improvement\nPopulation: 16, batch: 04, score: 0.2124 - no improvement\nPopulation: 16, batch: 05, score: 0.2237 - no improvement\nPopulation: 16, batch: 06, score: 0.2070 - no improvement\nPopulation: 16, batch: 07, score: 0.2414 - no improvement\nPopulation: 17, batch: 00, score: 0.2654 - no improvement\nPopulation: 17, batch: 01, score: 0.2449 - no improvement\nPopulation: 17, batch: 02, score: 0.2614 - no improvement\nPopulation: 17, batch: 03, score: 0.2317 - no improvement\nPopulation: 17, batch: 04, score: 0.2586 - no improvement\nPopulation: 17, batch: 05, score: 0.2151 - no improvement\nPopulation: 17, batch: 06, score: 0.2692 - new best, replacing\nPopulation: 17, batch: 07, score: 0.2458 - no improvement\nPopulation: 18, batch: 00, score: 0.2488 - no improvement\nPopulation: 18, batch: 01, score: 0.1992 - no improvement\nPopulation: 18, batch: 02, score: 0.2390 - no improvement\nPopulation: 18, batch: 03, score: 0.1938 - no improvement\nPopulation: 18, batch: 04, score: 0.2575 - no improvement\nPopulation: 18, batch: 05, score: 0.2330 - no improvement\nPopulation: 18, batch: 06, score: 0.2420 - no improvement\nPopulation: 18, batch: 07, score: 0.2627 - no improvement\nPopulation: 19, batch: 00, score: 0.2351 - no improvement\nPopulation: 19, batch: 01, score: 0.2673 - no improvement\nPopulation: 19, batch: 02, score: 0.2246 - no improvement\nPopulation: 19, batch: 03, score: 0.2070 - no improvement\nPopulation: 19, batch: 04, score: 0.2719 - new best, replacing\nPopulation: 19, batch: 05, score: 0.2245 - no improvement\nPopulation: 19, batch: 06, score: 0.2218 - no improvement\nPopulation: 19, batch: 07, score: 0.2362 - no improvement",
  "metrics": {
    "predict_time": 221.867528,
    "total_time": 10677.435625
  },
  "output": [
    [
      "https://replicate.delivery/mgxm/e665ea1a-2291-41b4-ad02-5bd2a3ce7697/new_york_city_completely_flooded_iter_000_batch_000_score_0.png",
      "https://replicate.delivery/mgxm/a5183755-db4d-44e3-b950-2d64d840ec15/new_york_city_completely_flooded_iter_000_batch_001_score_0.png",
      "https://replicate.delivery/mgxm/17df4351-ae6d-4c53-aee6-579a21a32fb6/new_york_city_completely_flooded_iter_000_batch_002_score_0.png",
      "https://replicate.delivery/mgxm/812f647d-c5fe-4672-ad0e-c4cdf045576f/new_york_city_completely_flooded_iter_000_batch_003_score_0.png",
      "https://replicate.delivery/mgxm/8db89ed7-0034-4657-9e5e-7fa4a3a5964e/new_york_city_completely_flooded_iter_000_batch_004_score_0.png",
      "https://replicate.delivery/mgxm/1d4ee48e-2e2a-4568-9243-c6e129bbfc56/new_york_city_completely_flooded_iter_000_batch_005_score_0.png",
      "https://replicate.delivery/mgxm/d4a55fad-5c0e-45cb-89ab-fcd89ac91102/new_york_city_completely_flooded_iter_000_batch_006_score_0.png",
      "https://replicate.delivery/mgxm/b298499d-32b6-4fca-9582-eff01abe73c5/new_york_city_completely_flooded_iter_000_batch_007_score_0.png"
    ],
    [
      "https://replicate.delivery/mgxm/6e1b5fa0-c66b-4e52-875d-b40c2e265c42/new_york_city_completely_flooded_iter_001_batch_000_score_0.png",
      "https://replicate.delivery/mgxm/162e1cb5-a321-4c98-a89e-bd3f1e4f51fb/new_york_city_completely_flooded_iter_001_batch_001_score_0.png",
      "https://replicate.delivery/mgxm/ab577251-7a25-4d87-958e-ac852c86d07b/new_york_city_completely_flooded_iter_001_batch_002_score_0.png",
      "https://replicate.delivery/mgxm/952fa8c6-b547-4ca4-9df1-2ff7612cb1d5/new_york_city_completely_flooded_iter_001_batch_003_score_0.png",
      "https://replicate.delivery/mgxm/d3fb6148-986e-41bb-9e5d-eb3dd0d18c52/new_york_city_completely_flooded_iter_001_batch_004_score_0.png",
      "https://replicate.delivery/mgxm/0bffded0-39ef-4e37-8d28-2a1c83b83a59/new_york_city_completely_flooded_iter_001_batch_005_score_0.png",
      "https://replicate.delivery/mgxm/ba04b106-3840-4dfd-9a72-75e503ad752a/new_york_city_completely_flooded_iter_001_batch_006_score_0.png",
      "https://replicate.delivery/mgxm/fdf5f05a-541a-4944-9427-859a315c74e8/new_york_city_completely_flooded_iter_001_batch_007_score_0.png"
    ],
    [
      "https://replicate.delivery/mgxm/74e7a921-88eb-4502-848e-07f5774585e5/new_york_city_completely_flooded_iter_002_batch_000_score_0.png",
      "https://replicate.delivery/mgxm/7477b0ad-a8a3-4697-be5a-7bb307f8e627/new_york_city_completely_flooded_iter_002_batch_001_score_0.png",
      "https://replicate.delivery/mgxm/8cb11309-ef0c-48b1-9047-822a10c31a30/new_york_city_completely_flooded_iter_002_batch_002_score_0.png",
      "https://replicate.delivery/mgxm/8f59e0b8-3962-47aa-b3a3-18261c495717/new_york_city_completely_flooded_iter_002_batch_003_score_0.png",
      "https://replicate.delivery/mgxm/1c92a2fd-8524-43c4-921c-e1614d7a1a17/new_york_city_completely_flooded_iter_002_batch_004_score_0.png",
      "https://replicate.delivery/mgxm/4e79affc-8ed6-4887-8c63-8d31b740edcd/new_york_city_completely_flooded_iter_002_batch_005_score_0.png",
      "https://replicate.delivery/mgxm/5273f895-890d-4731-880a-4ae025c3c137/new_york_city_completely_flooded_iter_002_batch_006_score_0.png",
      "https://replicate.delivery/mgxm/42300edf-5a11-4825-970e-78be3a6fb3b8/new_york_city_completely_flooded_iter_002_batch_007_score_0.png"
    ],
    [
      "https://replicate.delivery/mgxm/e04c672d-452b-40d7-a47e-d09776371b8d/new_york_city_completely_flooded_iter_003_batch_000_score_0.png",
      "https://replicate.delivery/mgxm/e4a61aac-d617-413a-b413-b00043b1a547/new_york_city_completely_flooded_iter_003_batch_001_score_0.png",
      "https://replicate.delivery/mgxm/4087b5ae-efdd-4063-91d1-a1df7fbe5a9e/new_york_city_completely_flooded_iter_003_batch_002_score_0.png",
      "https://replicate.delivery/mgxm/e6c30a1f-0137-4761-a5ec-1cb7b6bdab40/new_york_city_completely_flooded_iter_003_batch_003_score_0.png",
      "https://replicate.delivery/mgxm/00eebb69-2205-4fb6-92d8-73c285c0f7c7/new_york_city_completely_flooded_iter_003_batch_004_score_0.png",
      "https://replicate.delivery/mgxm/d54be450-9068-4d97-b2d3-d4543238ae14/new_york_city_completely_flooded_iter_003_batch_005_score_0.png",
      "https://replicate.delivery/mgxm/35db94ac-8992-4668-95c5-da6054fa7e68/new_york_city_completely_flooded_iter_003_batch_006_score_0.png",
      "https://replicate.delivery/mgxm/e8bfc8f7-89f5-4634-a3d5-23257bc04bb2/new_york_city_completely_flooded_iter_003_batch_007_score_0.png"
    ],
    [
      "https://replicate.delivery/mgxm/a3bb48fb-7512-47c1-a800-4b0ee298af4c/new_york_city_completely_flooded_iter_004_batch_000_score_0.png",
      "https://replicate.delivery/mgxm/c9d0ab6f-644f-4fd2-be62-10eb3b471ac9/new_york_city_completely_flooded_iter_004_batch_001_score_0.png",
      "https://replicate.delivery/mgxm/a6d95ad0-3119-4288-806d-15e04e8bb78f/new_york_city_completely_flooded_iter_004_batch_002_score_0.png",
      "https://replicate.delivery/mgxm/da4f9e96-228d-483c-8ab8-82071cf54ad8/new_york_city_completely_flooded_iter_004_batch_003_score_0.png",
      "https://replicate.delivery/mgxm/826c05b0-ad03-4d1d-be3e-cbde62da808a/new_york_city_completely_flooded_iter_004_batch_004_score_0.png",
      "https://replicate.delivery/mgxm/41558c9b-bdbf-4119-b092-58f3bad8a1f4/new_york_city_completely_flooded_iter_004_batch_005_score_0.png",
      "https://replicate.delivery/mgxm/ece15757-2d93-4994-9522-9dc786a02128/new_york_city_completely_flooded_iter_004_batch_006_score_0.png",
      "https://replicate.delivery/mgxm/4745e52a-713c-4c37-a4ff-b137c3f68c20/new_york_city_completely_flooded_iter_004_batch_007_score_0.png"
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      "https://replicate.delivery/mgxm/908ae783-e292-4dce-9509-59f02688803d/new_york_city_completely_flooded_iter_019_batch_006_score_0.png",
      "https://replicate.delivery/mgxm/20eed2d1-7700-44ba-bc84-4e514892d4b1/new_york_city_completely_flooded_iter_019_batch_007_score_0.png"
    ]
  ],
  "started_at": "2022-06-17T22:09:03.708281Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/lnri7jpouzdd7c73npp7bt5k5y",
    "cancel": "https://api.replicate.com/v1/predictions/lnri7jpouzdd7c73npp7bt5k5y/cancel"
  },
  "version": "d0d04e11830081fcc1066cc5e6306e4ffdcf35c0d95d12c6cbc2b869f17466d0"
}

Generated in

3 minutes 42 seconds

Tweak it Report

Using seed 319970566
Running simulation for new york city completely flooded
Encoding text embeddings with new york city completely flooded dimensions
Using aesthetic embedding 9 with weight 0.5
Using inpaint model but no image is provided. Initializing with zeros.
Population: 00, batch: 00, score: 0.2321 - first iteration
Population: 00, batch: 01, score: 0.2690 - first iteration
Population: 00, batch: 02, score: 0.2435 - first iteration
Population: 00, batch: 03, score: 0.2721 - first iteration
Population: 00, batch: 04, score: 0.2456 - first iteration
Population: 00, batch: 05, score: 0.2513 - first iteration
Population: 00, batch: 06, score: 0.2099 - first iteration
Population: 00, batch: 07, score: 0.2464 - first iteration
Population: 01, batch: 00, score: 0.2197 - no improvement
Population: 01, batch: 01, score: 0.2195 - no improvement
Population: 01, batch: 02, score: 0.2059 - no improvement
Population: 01, batch: 03, score: 0.2742 - new best, replacing
Population: 01, batch: 04, score: 0.1948 - no improvement
Population: 01, batch: 05, score: 0.2332 - no improvement
Population: 01, batch: 06, score: 0.2409 - new best, replacing
Population: 01, batch: 07, score: 0.1885 - no improvement
Population: 02, batch: 00, score: 0.2307 - no improvement
Population: 02, batch: 01, score: 0.2659 - no improvement
Population: 02, batch: 02, score: 0.2015 - no improvement
Population: 02, batch: 03, score: 0.2596 - no improvement
Population: 02, batch: 04, score: 0.2528 - new best, replacing
Population: 02, batch: 05, score: 0.2577 - new best, replacing
Population: 02, batch: 06, score: 0.2172 - no improvement
Population: 02, batch: 07, score: 0.2784 - new best, replacing
Population: 03, batch: 00, score: 0.2575 - new best, replacing
Population: 03, batch: 01, score: 0.2551 - no improvement
Population: 03, batch: 02, score: 0.2123 - no improvement
Population: 03, batch: 03, score: 0.2359 - no improvement
Population: 03, batch: 04, score: 0.1640 - no improvement
Population: 03, batch: 05, score: 0.2039 - no improvement
Population: 03, batch: 06, score: 0.2175 - no improvement
Population: 03, batch: 07, score: 0.2194 - no improvement
Population: 04, batch: 00, score: 0.2356 - no improvement
Population: 04, batch: 01, score: 0.2373 - no improvement
Population: 04, batch: 02, score: 0.2436 - new best, replacing
Population: 04, batch: 03, score: 0.1799 - no improvement
Population: 04, batch: 04, score: 0.2512 - no improvement
Population: 04, batch: 05, score: 0.2531 - no improvement
Population: 04, batch: 06, score: 0.2440 - new best, replacing
Population: 04, batch: 07, score: 0.2075 - no improvement
Population: 05, batch: 00, score: 0.2042 - no improvement
Population: 05, batch: 01, score: 0.2293 - no improvement
Population: 05, batch: 02, score: 0.2215 - no improvement
Population: 05, batch: 03, score: 0.1763 - no improvement
Population: 05, batch: 04, score: 0.1872 - no improvement
Population: 05, batch: 05, score: 0.2393 - no improvement
Population: 05, batch: 06, score: 0.1795 - no improvement
Population: 05, batch: 07, score: 0.2669 - no improvement
Population: 06, batch: 00, score: 0.2417 - no improvement
Population: 06, batch: 01, score: 0.2546 - no improvement
Population: 06, batch: 02, score: 0.2241 - no improvement
Population: 06, batch: 03, score: 0.2616 - no improvement
Population: 06, batch: 04, score: 0.2387 - no improvement
Population: 06, batch: 05, score: 0.2262 - no improvement
Population: 06, batch: 06, score: 0.1805 - no improvement
Population: 06, batch: 07, score: 0.2203 - no improvement
Population: 07, batch: 00, score: 0.2594 - new best, replacing
Population: 07, batch: 01, score: 0.2134 - no improvement
Population: 07, batch: 02, score: 0.2345 - no improvement
Population: 07, batch: 03, score: 0.1960 - no improvement
Population: 07, batch: 04, score: 0.2309 - no improvement
Population: 07, batch: 05, score: 0.1765 - no improvement
Population: 07, batch: 06, score: 0.2479 - new best, replacing
Population: 07, batch: 07, score: 0.2632 - no improvement
Population: 08, batch: 00, score: 0.2128 - no improvement
Population: 08, batch: 01, score: 0.2006 - no improvement
Population: 08, batch: 02, score: 0.2634 - new best, replacing
Population: 08, batch: 03, score: 0.2098 - no improvement
Population: 08, batch: 04, score: 0.2537 - new best, replacing
Population: 08, batch: 05, score: 0.2092 - no improvement
Population: 08, batch: 06, score: 0.1991 - no improvement
Population: 08, batch: 07, score: 0.2331 - no improvement
Population: 09, batch: 00, score: 0.2534 - no improvement
Population: 09, batch: 01, score: 0.2258 - no improvement
Population: 09, batch: 02, score: 0.2439 - no improvement
Population: 09, batch: 03, score: 0.2231 - no improvement
Population: 09, batch: 04, score: 0.2115 - no improvement
Population: 09, batch: 05, score: 0.1948 - no improvement
Population: 09, batch: 06, score: 0.2480 - new best, replacing
Population: 09, batch: 07, score: 0.2123 - no improvement
Population: 10, batch: 00, score: 0.2416 - no improvement
Population: 10, batch: 01, score: 0.1903 - no improvement
Population: 10, batch: 02, score: 0.1687 - no improvement
Population: 10, batch: 03, score: 0.2367 - no improvement
Population: 10, batch: 04, score: 0.1970 - no improvement
Population: 10, batch: 05, score: 0.2277 - no improvement
Population: 10, batch: 06, score: 0.2293 - no improvement
Population: 10, batch: 07, score: 0.2269 - no improvement
Population: 11, batch: 00, score: 0.2344 - no improvement
Population: 11, batch: 01, score: 0.1815 - no improvement
Population: 11, batch: 02, score: 0.2390 - no improvement
Population: 11, batch: 03, score: 0.2152 - no improvement
Population: 11, batch: 04, score: 0.2705 - new best, replacing
Population: 11, batch: 05, score: 0.2594 - new best, replacing
Population: 11, batch: 06, score: 0.2681 - new best, replacing
Population: 11, batch: 07, score: 0.2214 - no improvement
Population: 12, batch: 00, score: 0.1791 - no improvement
Population: 12, batch: 01, score: 0.1462 - no improvement
Population: 12, batch: 02, score: 0.2466 - no improvement
Population: 12, batch: 03, score: 0.2606 - no improvement
Population: 12, batch: 04, score: 0.2558 - no improvement
Population: 12, batch: 05, score: 0.2077 - no improvement
Population: 12, batch: 06, score: 0.2274 - no improvement
Population: 12, batch: 07, score: 0.1566 - no improvement
Population: 13, batch: 00, score: 0.1646 - no improvement
Population: 13, batch: 01, score: 0.2091 - no improvement
Population: 13, batch: 02, score: 0.2259 - no improvement
Population: 13, batch: 03, score: 0.1968 - no improvement
Population: 13, batch: 04, score: 0.1815 - no improvement
Population: 13, batch: 05, score: 0.2707 - new best, replacing
Population: 13, batch: 06, score: 0.2093 - no improvement
Population: 13, batch: 07, score: 0.2379 - no improvement
Population: 14, batch: 00, score: 0.2417 - no improvement
Population: 14, batch: 01, score: 0.2123 - no improvement
Population: 14, batch: 02, score: 0.2621 - no improvement
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Population: 14, batch: 04, score: 0.2324 - no improvement
Population: 14, batch: 05, score: 0.2448 - no improvement
Population: 14, batch: 06, score: 0.2493 - no improvement
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Population: 15, batch: 00, score: 0.2594 - no improvement
Population: 15, batch: 01, score: 0.1612 - no improvement
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Population: 15, batch: 07, score: 0.1743 - no improvement
Population: 16, batch: 00, score: 0.2655 - new best, replacing
Population: 16, batch: 01, score: 0.1834 - no improvement
Population: 16, batch: 02, score: 0.2349 - no improvement
Population: 16, batch: 03, score: 0.2386 - no improvement
Population: 16, batch: 04, score: 0.2124 - no improvement
Population: 16, batch: 05, score: 0.2237 - no improvement
Population: 16, batch: 06, score: 0.2070 - no improvement
Population: 16, batch: 07, score: 0.2414 - no improvement
Population: 17, batch: 00, score: 0.2654 - no improvement
Population: 17, batch: 01, score: 0.2449 - no improvement
Population: 17, batch: 02, score: 0.2614 - no improvement
Population: 17, batch: 03, score: 0.2317 - no improvement
Population: 17, batch: 04, score: 0.2586 - no improvement
Population: 17, batch: 05, score: 0.2151 - no improvement
Population: 17, batch: 06, score: 0.2692 - new best, replacing
Population: 17, batch: 07, score: 0.2458 - no improvement
Population: 18, batch: 00, score: 0.2488 - no improvement
Population: 18, batch: 01, score: 0.1992 - no improvement
Population: 18, batch: 02, score: 0.2390 - no improvement
Population: 18, batch: 03, score: 0.1938 - no improvement
Population: 18, batch: 04, score: 0.2575 - no improvement
Population: 18, batch: 05, score: 0.2330 - no improvement
Population: 18, batch: 06, score: 0.2420 - no improvement
Population: 18, batch: 07, score: 0.2627 - no improvement
Population: 19, batch: 00, score: 0.2351 - no improvement
Population: 19, batch: 01, score: 0.2673 - no improvement
Population: 19, batch: 02, score: 0.2246 - no improvement
Population: 19, batch: 03, score: 0.2070 - no improvement
Population: 19, batch: 04, score: 0.2719 - new best, replacing
Population: 19, batch: 05, score: 0.2245 - no improvement
Population: 19, batch: 06, score: 0.2218 - no improvement
Population: 19, batch: 07, score: 0.2362 - no improvement