Prediction

Model

hodeehum/flux-dev-lora-trainer4:aad4684a

9k18p0pyh5rm80cm2nfah536mr

Status

Succeeded

Source

Web

Hardware

H100

Total duration

47.8s

Created

12 months ago

Webhook

–

Input

prompt: tjk in a high-resolution, documentary photo as a 34-year-old woman with blonde, chin-length hair, sitting on the grass in a field of flowers.
aspect_ratio: 1:1
height: 1024
width: 1024
prompt_strength: 0.8
model: dev
num_outputs: 4
num_inference_steps: 50
guidance_scale: 10
output_format: png
output_quality: 100
go_fast: false
megapixels: 1
lora_scale: 1
extra_lora_scale: 1

{
  "aspect_ratio": "1:1",
  "extra_lora_scale": 1,
  "go_fast": false,
  "guidance_scale": 10,
  "height": 1024,
  "lora_scale": 1,
  "megapixels": "1",
  "model": "dev",
  "num_inference_steps": 50,
  "num_outputs": 4,
  "output_format": "png",
  "output_quality": 100,
  "prompt": "tjk in a high-resolution, documentary photo as a 34-year-old woman with blonde, chin-length hair, sitting on the grass in a field of flowers.",
  "prompt_strength": 0.8,
  "width": 1024
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_0QP**********************************

This is your API token. Keep it to yourself.

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

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

Run hodeehum/flux-dev-lora-trainer4 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "hodeehum/flux-dev-lora-trainer4:aad4684a4809bd363dc7de8368ecd4b9f6361cbed7bd4cf6dd62753989554db9",
  {
    input: {
      aspect_ratio: "1:1",
      extra_lora_scale: 1,
      go_fast: false,
      guidance_scale: 10,
      height: 1024,
      lora_scale: 1,
      megapixels: "1",
      model: "dev",
      num_inference_steps: 50,
      num_outputs: 4,
      output_format: "png",
      output_quality: 100,
      prompt: "tjk in a high-resolution, documentary photo as a 34-year-old woman with blonde, chin-length hair, sitting on the grass in a field of flowers.",
      prompt_strength: 0.8,
      width: 1024
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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=r8_0QP**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run hodeehum/flux-dev-lora-trainer4 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "hodeehum/flux-dev-lora-trainer4:aad4684a4809bd363dc7de8368ecd4b9f6361cbed7bd4cf6dd62753989554db9",
    input={
        "aspect_ratio": "1:1",
        "extra_lora_scale": 1,
        "go_fast": False,
        "guidance_scale": 10,
        "height": 1024,
        "lora_scale": 1,
        "megapixels": "1",
        "model": "dev",
        "num_inference_steps": 50,
        "num_outputs": 4,
        "output_format": "png",
        "output_quality": 100,
        "prompt": "tjk in a high-resolution, documentary photo as a 34-year-old woman with blonde, chin-length hair, sitting on the grass in a field of flowers.",
        "prompt_strength": 0.8,
        "width": 1024
    }
)

# To access the file URL:
print(output[0].url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output[0].read())

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=r8_0QP**********************************

This is your API token. Keep it to yourself.

Run hodeehum/flux-dev-lora-trainer4 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": "hodeehum/flux-dev-lora-trainer4:aad4684a4809bd363dc7de8368ecd4b9f6361cbed7bd4cf6dd62753989554db9",
    "input": {
      "aspect_ratio": "1:1",
      "extra_lora_scale": 1,
      "go_fast": false,
      "guidance_scale": 10,
      "height": 1024,
      "lora_scale": 1,
      "megapixels": "1",
      "model": "dev",
      "num_inference_steps": 50,
      "num_outputs": 4,
      "output_format": "png",
      "output_quality": 100,
      "prompt": "tjk in a high-resolution, documentary photo as a 34-year-old woman with blonde, chin-length hair, sitting on the grass in a field of flowers.",
      "prompt_strength": 0.8,
      "width": 1024
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "id": "9k18p0pyh5rm80cm2nfah536mr",
  "model": "hodeehum/flux-dev-lora-trainer4",
  "version": "aad4684a4809bd363dc7de8368ecd4b9f6361cbed7bd4cf6dd62753989554db9",
  "input": {
    "aspect_ratio": "1:1",
    "extra_lora_scale": 1,
    "go_fast": false,
    "guidance_scale": 10,
    "height": 1024,
    "lora_scale": 1,
    "megapixels": "1",
    "model": "dev",
    "num_inference_steps": 50,
    "num_outputs": 4,
    "output_format": "png",
    "output_quality": 100,
    "prompt": "tjk in a high-resolution, documentary photo as a 34-year-old woman with blonde, chin-length hair, sitting on the grass in a field of flowers.",
    "prompt_strength": 0.8,
    "width": 1024
  },
  "logs": "2024-12-30 02:22:07.395 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2024-12-30 02:22:07.396 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]\nApplying LoRA:  92%|█████████▏| 281/304 [00:00<00:00, 2809.05it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2725.77it/s]\n2024-12-30 02:22:07.508 | SUCCESS  | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s\nfree=29917324013568\nDownloading weights\n2024-12-30T02:22:07Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmp9yn5ybf8/weights url=https://replicate.delivery/xezq/8dGAsHRoxHqLAdnlX3lFxgbtGWbCbcdInekMZhHmmOhf76fnA/trained_model.tar\n2024-12-30T02:22:10Z | INFO  | [ Complete ] dest=/tmp/tmp9yn5ybf8/weights size=\"1.1 GB\" total_elapsed=2.933s url=https://replicate.delivery/xezq/8dGAsHRoxHqLAdnlX3lFxgbtGWbCbcdInekMZhHmmOhf76fnA/trained_model.tar\nDownloaded weights in 2.99s\n2024-12-30 02:22:10.499 | INFO     | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/c18631d797443ecf\n2024-12-30 02:22:10.726 | INFO     | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2024-12-30 02:22:10.726 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2024-12-30 02:22:10.726 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]\nApplying LoRA:  94%|█████████▍| 287/304 [00:00<00:00, 2868.35it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2759.76it/s]\n2024-12-30 02:22:10.837 | SUCCESS  | fp8.lora_loading:load_lora:539 - LoRA applied in 0.34s\nUsing seed: 2405\n0it [00:00, ?it/s]\n1it [00:00,  8.40it/s]\n2it [00:00,  5.89it/s]\n3it [00:00,  5.37it/s]\n4it [00:00,  5.15it/s]\n5it [00:00,  5.02it/s]\n6it [00:01,  4.94it/s]\n7it [00:01,  4.91it/s]\n8it [00:01,  4.89it/s]\n9it [00:01,  4.87it/s]\n10it [00:01,  4.86it/s]\n11it 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[00:10,  4.86it/s]\n0it [00:00, ?it/s]\n1it [00:00,  4.82it/s]\n2it [00:00,  4.79it/s]\n3it [00:00,  4.80it/s]\n4it [00:00,  4.81it/s]\n5it [00:01,  4.81it/s]\n6it [00:01,  4.80it/s]\n7it [00:01,  4.80it/s]\n8it [00:01,  4.80it/s]\n9it [00:01,  4.81it/s]\n10it [00:02,  4.82it/s]\n11it [00:02,  4.81it/s]\n12it [00:02,  4.81it/s]\n13it [00:02,  4.81it/s]\n14it [00:02,  4.81it/s]\n15it [00:03,  4.81it/s]\n16it [00:03,  4.81it/s]\n17it [00:03,  4.81it/s]\n18it [00:03,  4.81it/s]\n19it [00:03,  4.81it/s]\n20it [00:04,  4.81it/s]\n21it [00:04,  4.81it/s]\n22it [00:04,  4.81it/s]\n23it [00:04,  4.81it/s]\n24it [00:04,  4.81it/s]\n25it [00:05,  4.81it/s]\n26it [00:05,  4.80it/s]\n27it [00:05,  4.80it/s]\n28it [00:05,  4.80it/s]\n29it [00:06,  4.81it/s]\n30it [00:06,  4.81it/s]\n31it [00:06,  4.81it/s]\n32it [00:06,  4.81it/s]\n33it [00:06,  4.81it/s]\n34it [00:07,  4.80it/s]\n35it [00:07,  4.80it/s]\n36it [00:07,  4.80it/s]\n37it [00:07,  4.81it/s]\n38it [00:07,  4.81it/s]\n39it [00:08,  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4.81it/s]\n28it [00:05,  4.80it/s]\n29it [00:06,  4.80it/s]\n30it [00:06,  4.80it/s]\n31it [00:06,  4.80it/s]\n32it [00:06,  4.81it/s]\n33it [00:06,  4.81it/s]\n34it [00:07,  4.81it/s]\n35it [00:07,  4.80it/s]\n36it [00:07,  4.80it/s]\n37it [00:07,  4.80it/s]\n38it [00:07,  4.80it/s]\n39it [00:08,  4.80it/s]\n40it [00:08,  4.81it/s]\n41it [00:08,  4.81it/s]\n42it [00:08,  4.80it/s]\n43it [00:08,  4.81it/s]\n44it [00:09,  4.81it/s]\n45it [00:09,  4.80it/s]\n46it [00:09,  4.81it/s]\n47it [00:09,  4.81it/s]\n48it [00:09,  4.81it/s]\n49it [00:10,  4.81it/s]\n50it [00:10,  4.81it/s]\n50it [00:10,  4.81it/s]\n0it [00:00, ?it/s]\n1it [00:00,  4.84it/s]\n2it [00:00,  4.81it/s]\n3it [00:00,  4.81it/s]\n4it [00:00,  4.80it/s]\n5it [00:01,  4.78it/s]\n6it [00:01,  4.80it/s]\n7it [00:01,  4.79it/s]\n8it [00:01,  4.79it/s]\n9it [00:01,  4.79it/s]\n10it [00:02,  4.78it/s]\n11it [00:02,  4.79it/s]\n12it [00:02,  4.79it/s]\n13it [00:02,  4.80it/s]\n14it [00:02,  4.80it/s]\n15it [00:03,  4.79it/s]\n16it [00:03,  4.80it/s]\n17it [00:03,  4.80it/s]\n18it [00:03,  4.81it/s]\n19it [00:03,  4.81it/s]\n20it [00:04,  4.80it/s]\n21it [00:04,  4.79it/s]\n22it [00:04,  4.80it/s]\n23it [00:04,  4.81it/s]\n24it [00:05,  4.81it/s]\n25it [00:05,  4.80it/s]\n26it [00:05,  4.80it/s]\n27it [00:05,  4.81it/s]\n28it [00:05,  4.80it/s]\n29it [00:06,  4.80it/s]\n30it [00:06,  4.80it/s]\n31it [00:06,  4.79it/s]\n32it [00:06,  4.79it/s]\n33it [00:06,  4.80it/s]\n34it [00:07,  4.81it/s]\n35it [00:07,  4.81it/s]\n36it [00:07,  4.80it/s]\n37it [00:07,  4.80it/s]\n38it [00:07,  4.81it/s]\n39it [00:08,  4.81it/s]\n40it [00:08,  4.81it/s]\n41it [00:08,  4.79it/s]\n42it [00:08,  4.79it/s]\n43it [00:08,  4.80it/s]\n44it [00:09,  4.81it/s]\n45it [00:09,  4.81it/s]\n46it [00:09,  4.81it/s]\n47it [00:09,  4.81it/s]\n48it [00:09,  4.80it/s]\n49it [00:10,  4.80it/s]\n50it [00:10,  4.81it/s]\n50it [00:10,  4.80it/s]\nTotal safe images: 4 out of 4",
  "output": [
    "https://replicate.delivery/xezq/QrUZhRHAUIpODpDLiWSV5egBqsGXLskNqWMYWPyCV5GfX7fnA/out-0.png",
    "https://replicate.delivery/xezq/e628aBBjfws1GUSujVG0vBRpP9Z9XmF2yGLASTKu2Poev2fPB/out-1.png",
    "https://replicate.delivery/xezq/r8JXbghaoMZAKxNe5TxrrzQmESY76ISNVvAfB2Y1yxkev2fPB/out-2.png",
    "https://replicate.delivery/xezq/ldfyKN05W0w6ICnBxAiWrzy7HrovPoXqdo0uFOP5jzfev2fPB/out-3.png"
  ],
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2024-12-30T02:22:06.473Z",
  "started_at": "2024-12-30T02:22:07.396883Z",
  "completed_at": "2024-12-30T02:22:54.25416Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/9k18p0pyh5rm80cm2nfah536mr/cancel",
    "get": "https://api.replicate.com/v1/predictions/9k18p0pyh5rm80cm2nfah536mr",
    "stream": "https://stream.replicate.com/v1/files/bcwr-ez6plal2s437ricjmfvvvbr77h5neqnavrgkybq2m427yy6rvwuq",
    "web": "https://replicate.com/p/9k18p0pyh5rm80cm2nfah536mr"
  },
  "metrics": {
    "predict_time": 46.857277524,
    "total_time": 47.78116
  }
}

Generated in

46.9 seconds

Tweak it Report

2024-12-30 02:22:07.395 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2024-12-30 02:22:07.396 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 92%|█████████▏| 281/304 [00:00<00:00, 2809.05it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2725.77it/s] 2024-12-30 02:22:07.508 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s free=29917324013568 Downloading weights 2024-12-30T02:22:07Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp9yn5ybf8/weights url=https://replicate.delivery/xezq/8dGAsHRoxHqLAdnlX3lFxgbtGWbCbcdInekMZhHmmOhf76fnA/trained_model.tar 2024-12-30T02:22:10Z | INFO | [ Complete ] dest=/tmp/tmp9yn5ybf8/weights size="1.1 GB" total_elapsed=2.933s url=https://replicate.delivery/xezq/8dGAsHRoxHqLAdnlX3lFxgbtGWbCbcdInekMZhHmmOhf76fnA/trained_model.tar Downloaded weights in 2.99s 2024-12-30 02:22:10.499 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/c18631d797443ecf 2024-12-30 02:22:10.726 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2024-12-30 02:22:10.726 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2024-12-30 02:22:10.726 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 94%|█████████▍| 287/304 [00:00<00:00, 2868.35it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2759.76it/s] 2024-12-30 02:22:10.837 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.34s Using seed: 2405 0it [00:00, ?it/s] 1it [00:00, 8.40it/s] 2it [00:00, 5.89it/s] 3it [00:00, 5.37it/s] 4it [00:00, 5.15it/s] 5it [00:00, 5.02it/s] 6it [00:01, 4.94it/s] 7it [00:01, 4.91it/s] 8it [00:01, 4.89it/s] 9it [00:01, 4.87it/s] 10it [00:01, 4.86it/s] 11it [00:02, 4.84it/s] 12it [00:02, 4.83it/s] 13it [00:02, 4.83it/s] 14it [00:02, 4.83it/s] 15it [00:03, 4.83it/s] 16it [00:03, 4.82it/s] 17it [00:03, 4.82it/s] 18it [00:03, 4.82it/s] 19it [00:03, 4.82it/s] 20it [00:04, 4.82it/s] 21it [00:04, 4.82it/s] 22it [00:04, 4.81it/s] 23it [00:04, 4.82it/s] 24it [00:04, 4.81it/s] 25it [00:05, 4.81it/s] 26it [00:05, 4.81it/s] 27it [00:05, 4.81it/s] 28it [00:05, 4.81it/s] 29it [00:05, 4.82it/s] 30it [00:06, 4.82it/s] 31it [00:06, 4.82it/s] 32it [00:06, 4.82it/s] 33it [00:06, 4.82it/s] 34it [00:06, 4.82it/s] 35it [00:07, 4.82it/s] 36it [00:07, 4.81it/s] 37it [00:07, 4.81it/s] 38it [00:07, 4.81it/s] 39it [00:08, 4.82it/s] 40it [00:08, 4.82it/s] 41it [00:08, 4.81it/s] 42it [00:08, 4.81it/s] 43it [00:08, 4.81it/s] 44it [00:09, 4.81it/s] 45it [00:09, 4.81it/s] 46it [00:09, 4.81it/s] 47it [00:09, 4.81it/s] 48it [00:09, 4.82it/s] 49it [00:10, 4.82it/s] 50it [00:10, 4.82it/s] 50it [00:10, 4.86it/s] 0it [00:00, ?it/s] 1it [00:00, 4.82it/s] 2it [00:00, 4.79it/s] 3it [00:00, 4.80it/s] 4it [00:00, 4.81it/s] 5it [00:01, 4.81it/s] 6it [00:01, 4.80it/s] 7it [00:01, 4.80it/s] 8it [00:01, 4.80it/s] 9it [00:01, 4.81it/s] 10it [00:02, 4.82it/s] 11it [00:02, 4.81it/s] 12it [00:02, 4.81it/s] 13it [00:02, 4.81it/s] 14it [00:02, 4.81it/s] 15it [00:03, 4.81it/s] 16it [00:03, 4.81it/s] 17it [00:03, 4.81it/s] 18it [00:03, 4.81it/s] 19it [00:03, 4.81it/s] 20it [00:04, 4.81it/s] 21it [00:04, 4.81it/s] 22it [00:04, 4.81it/s] 23it [00:04, 4.81it/s] 24it [00:04, 4.81it/s] 25it [00:05, 4.81it/s] 26it [00:05, 4.80it/s] 27it [00:05, 4.80it/s] 28it [00:05, 4.80it/s] 29it [00:06, 4.81it/s] 30it [00:06, 4.81it/s] 31it [00:06, 4.81it/s] 32it [00:06, 4.81it/s] 33it [00:06, 4.81it/s] 34it [00:07, 4.80it/s] 35it [00:07, 4.80it/s] 36it [00:07, 4.80it/s] 37it [00:07, 4.81it/s] 38it [00:07, 4.81it/s] 39it [00:08, 4.81it/s] 40it [00:08, 4.80it/s] 41it [00:08, 4.80it/s] 42it [00:08, 4.80it/s] 43it [00:08, 4.80it/s] 44it [00:09, 4.80it/s] 45it [00:09, 4.81it/s] 46it [00:09, 4.81it/s] 47it [00:09, 4.80it/s] 48it [00:09, 4.81it/s] 49it [00:10, 4.81it/s] 50it [00:10, 4.81it/s] 50it [00:10, 4.81it/s] 0it [00:00, ?it/s] 1it [00:00, 4.83it/s] 2it [00:00, 4.81it/s] 3it [00:00, 4.82it/s] 4it [00:00, 4.82it/s] 5it [00:01, 4.81it/s] 6it [00:01, 4.81it/s] 7it [00:01, 4.81it/s] 8it [00:01, 4.81it/s] 9it [00:01, 4.80it/s] 10it [00:02, 4.81it/s] 11it [00:02, 4.81it/s] 12it [00:02, 4.81it/s] 13it [00:02, 4.81it/s] 14it [00:02, 4.81it/s] 15it [00:03, 4.81it/s] 16it [00:03, 4.81it/s] 17it [00:03, 4.81it/s] 18it [00:03, 4.81it/s] 19it [00:03, 4.80it/s] 20it [00:04, 4.80it/s] 21it [00:04, 4.80it/s] 22it [00:04, 4.80it/s] 23it [00:04, 4.81it/s] 24it [00:04, 4.81it/s] 25it [00:05, 4.81it/s] 26it [00:05, 4.81it/s] 27it [00:05, 4.81it/s] 28it [00:05, 4.80it/s] 29it [00:06, 4.80it/s] 30it [00:06, 4.80it/s] 31it [00:06, 4.80it/s] 32it [00:06, 4.81it/s] 33it [00:06, 4.81it/s] 34it [00:07, 4.81it/s] 35it [00:07, 4.80it/s] 36it [00:07, 4.80it/s] 37it [00:07, 4.80it/s] 38it [00:07, 4.80it/s] 39it [00:08, 4.80it/s] 40it [00:08, 4.81it/s] 41it [00:08, 4.81it/s] 42it [00:08, 4.80it/s] 43it [00:08, 4.81it/s] 44it [00:09, 4.81it/s] 45it [00:09, 4.80it/s] 46it [00:09, 4.81it/s] 47it [00:09, 4.81it/s] 48it [00:09, 4.81it/s] 49it [00:10, 4.81it/s] 50it [00:10, 4.81it/s] 50it [00:10, 4.81it/s] 0it [00:00, ?it/s] 1it [00:00, 4.84it/s] 2it [00:00, 4.81it/s] 3it [00:00, 4.81it/s] 4it [00:00, 4.80it/s] 5it [00:01, 4.78it/s] 6it [00:01, 4.80it/s] 7it [00:01, 4.79it/s] 8it [00:01, 4.79it/s] 9it [00:01, 4.79it/s] 10it [00:02, 4.78it/s] 11it [00:02, 4.79it/s] 12it [00:02, 4.79it/s] 13it [00:02, 4.80it/s] 14it [00:02, 4.80it/s] 15it [00:03, 4.79it/s] 16it [00:03, 4.80it/s] 17it [00:03, 4.80it/s] 18it [00:03, 4.81it/s] 19it [00:03, 4.81it/s] 20it [00:04, 4.80it/s] 21it [00:04, 4.79it/s] 22it [00:04, 4.80it/s] 23it [00:04, 4.81it/s] 24it [00:05, 4.81it/s] 25it [00:05, 4.80it/s] 26it [00:05, 4.80it/s] 27it [00:05, 4.81it/s] 28it [00:05, 4.80it/s] 29it [00:06, 4.80it/s] 30it [00:06, 4.80it/s] 31it [00:06, 4.79it/s] 32it [00:06, 4.79it/s] 33it [00:06, 4.80it/s] 34it [00:07, 4.81it/s] 35it [00:07, 4.81it/s] 36it [00:07, 4.80it/s] 37it [00:07, 4.80it/s] 38it [00:07, 4.81it/s] 39it [00:08, 4.81it/s] 40it [00:08, 4.81it/s] 41it [00:08, 4.79it/s] 42it [00:08, 4.79it/s] 43it [00:08, 4.80it/s] 44it [00:09, 4.81it/s] 45it [00:09, 4.81it/s] 46it [00:09, 4.81it/s] 47it [00:09, 4.81it/s] 48it [00:09, 4.80it/s] 49it [00:10, 4.80it/s] 50it [00:10, 4.81it/s] 50it [00:10, 4.80it/s] Total safe images: 4 out of 4