capim-labs / helbert_costa
- Public
- 35 runs
Prediction
capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47ID2qq67dr6m5rme0cnvr2bsqsxbwStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- uma foto do Helbert na praia
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "uma foto do Helbert na praia", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
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 capim-labs/helbert_costa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47", { input: { model: "dev", prompt: "uma foto do Helbert na praia", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // 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
Import the client:import replicate
Run capim-labs/helbert_costa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47", input={ "model": "dev", "prompt": "uma foto do Helbert na praia", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run capim-labs/helbert_costa 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": "capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47", "input": { "model": "dev", "prompt": "uma foto do Helbert na praia", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-03-28T18:29:31.105433Z", "created_at": "2025-03-28T18:29:20.673000Z", "data_removed": false, "error": null, "id": "2qq67dr6m5rme0cnvr2bsqsxbw", "input": { "model": "dev", "prompt": "uma foto do Helbert na praia", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "free=28098682990592\nDownloading weights\n2025-03-28T18:29:20Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpbiuvplmb/weights url=https://replicate.delivery/xezq/ePobUGdCbuWPIak1VSPbU1ACxlCnIAFIt2V9u1RR3kGH3kOKA/trained_model.tar\n2025-03-28T18:29:22Z | INFO | [ Complete ] dest=/tmp/tmpbiuvplmb/weights size=\"172 MB\" total_elapsed=2.256s url=https://replicate.delivery/xezq/ePobUGdCbuWPIak1VSPbU1ACxlCnIAFIt2V9u1RR3kGH3kOKA/trained_model.tar\nDownloaded weights in 2.28s\nLoaded LoRAs in 2.83s\nUsing seed: 2476\nPrompt: uma foto do Helbert na praia\n[!] txt2img mode\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.80it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.30it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.06it/s]\n 14%|█▍ | 4/28 [00:00<00:06, 3.96it/s]\n 18%|█▊ | 5/28 [00:01<00:05, 3.90it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.87it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.85it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.84it/s]\n 32%|███▏ | 9/28 [00:02<00:04, 3.83it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.82it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.82it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.81it/s]\n 46%|████▋ | 13/28 [00:03<00:03, 3.81it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.81it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.81it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.81it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.81it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.80it/s]\n 68%|██████▊ | 19/28 [00:04<00:02, 3.80it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.81it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.80it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.80it/s]\n 82%|████████▏ | 23/28 [00:05<00:01, 3.80it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.80it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.81it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.80it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.81it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.80it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.83it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 10.427406542, "total_time": 10.432433 }, "output": [ "https://replicate.delivery/xezq/9CwtmMfAiLVrVafte3rcuzTIe9ldsy0vMxBfsFVzHIHbROpjC/out-0.webp" ], "started_at": "2025-03-28T18:29:20.678027Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-p4lh33rshzoxwoqgkohwthpli23gesktgto3kkcj7hvzbovsdpqq", "get": "https://api.replicate.com/v1/predictions/2qq67dr6m5rme0cnvr2bsqsxbw", "cancel": "https://api.replicate.com/v1/predictions/2qq67dr6m5rme0cnvr2bsqsxbw/cancel" }, "version": "450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47" }
Generated infree=28098682990592 Downloading weights 2025-03-28T18:29:20Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpbiuvplmb/weights url=https://replicate.delivery/xezq/ePobUGdCbuWPIak1VSPbU1ACxlCnIAFIt2V9u1RR3kGH3kOKA/trained_model.tar 2025-03-28T18:29:22Z | INFO | [ Complete ] dest=/tmp/tmpbiuvplmb/weights size="172 MB" total_elapsed=2.256s url=https://replicate.delivery/xezq/ePobUGdCbuWPIak1VSPbU1ACxlCnIAFIt2V9u1RR3kGH3kOKA/trained_model.tar Downloaded weights in 2.28s Loaded LoRAs in 2.83s Using seed: 2476 Prompt: uma foto do Helbert na praia [!] txt2img mode 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.80it/s] 7%|▋ | 2/28 [00:00<00:06, 4.30it/s] 11%|█ | 3/28 [00:00<00:06, 4.06it/s] 14%|█▍ | 4/28 [00:00<00:06, 3.96it/s] 18%|█▊ | 5/28 [00:01<00:05, 3.90it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.87it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.85it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.84it/s] 32%|███▏ | 9/28 [00:02<00:04, 3.83it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.82it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.82it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.81it/s] 46%|████▋ | 13/28 [00:03<00:03, 3.81it/s] 50%|█████ | 14/28 [00:03<00:03, 3.81it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.81it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.81it/s] 61%|██████ | 17/28 [00:04<00:02, 3.81it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.80it/s] 68%|██████▊ | 19/28 [00:04<00:02, 3.80it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.81it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.80it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.80it/s] 82%|████████▏ | 23/28 [00:05<00:01, 3.80it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.80it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.81it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.80it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.81it/s] 100%|██████████| 28/28 [00:07<00:00, 3.80it/s] 100%|██████████| 28/28 [00:07<00:00, 3.83it/s] Total safe images: 1 out of 1
Prediction
capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47ID3w1a3qqcp5rm80cnvr2bc0ssgrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- uma foto do Helbert na cidade a noite
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "uma foto do Helbert na cidade a noite", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
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 capim-labs/helbert_costa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47", { input: { model: "dev", prompt: "uma foto do Helbert na cidade a noite", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // 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
Import the client:import replicate
Run capim-labs/helbert_costa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47", input={ "model": "dev", "prompt": "uma foto do Helbert na cidade a noite", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run capim-labs/helbert_costa 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": "capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47", "input": { "model": "dev", "prompt": "uma foto do Helbert na cidade a noite", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-03-28T18:30:29.791460Z", "created_at": "2025-03-28T18:30:19.569000Z", "data_removed": false, "error": null, "id": "3w1a3qqcp5rm80cnvr2bc0ssgr", "input": { "model": "dev", "prompt": "uma foto do Helbert na cidade a noite", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "free=27245086576640\nDownloading weights\n2025-03-28T18:30:19Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpjjgzykxv/weights url=https://replicate.delivery/xezq/ePobUGdCbuWPIak1VSPbU1ACxlCnIAFIt2V9u1RR3kGH3kOKA/trained_model.tar\n2025-03-28T18:30:21Z | INFO | [ Complete ] dest=/tmp/tmpjjgzykxv/weights size=\"172 MB\" total_elapsed=2.065s url=https://replicate.delivery/xezq/ePobUGdCbuWPIak1VSPbU1ACxlCnIAFIt2V9u1RR3kGH3kOKA/trained_model.tar\nDownloaded weights in 2.09s\nLoaded LoRAs in 2.64s\nUsing seed: 57378\nPrompt: uma foto do Helbert na cidade a noite\n[!] txt2img mode\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.81it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.32it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.07it/s]\n 14%|█▍ | 4/28 [00:00<00:06, 3.96it/s]\n 18%|█▊ | 5/28 [00:01<00:05, 3.91it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.87it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.85it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.84it/s]\n 32%|███▏ | 9/28 [00:02<00:04, 3.83it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.82it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.82it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.82it/s]\n 46%|████▋ | 13/28 [00:03<00:03, 3.82it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.82it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.81it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.81it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.81it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.81it/s]\n 68%|██████▊ | 19/28 [00:04<00:02, 3.81it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.81it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.81it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.81it/s]\n 82%|████████▏ | 23/28 [00:05<00:01, 3.81it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.81it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.81it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.81it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.81it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.81it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.84it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 10.213777169, "total_time": 10.22246 }, "output": [ "https://replicate.delivery/xezq/6lPC2nwSg7KXLZKQwXbWQ1wBNUQMuaWGTYhtlZ2q3JQxcSHF/out-0.webp" ], "started_at": "2025-03-28T18:30:19.577682Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-6tjgyzxxyeceggalosto4cw7jdkw5ykqw4m5ohpvgx7l5qrmjura", "get": "https://api.replicate.com/v1/predictions/3w1a3qqcp5rm80cnvr2bc0ssgr", "cancel": "https://api.replicate.com/v1/predictions/3w1a3qqcp5rm80cnvr2bc0ssgr/cancel" }, "version": "450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47" }
Generated infree=27245086576640 Downloading weights 2025-03-28T18:30:19Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpjjgzykxv/weights url=https://replicate.delivery/xezq/ePobUGdCbuWPIak1VSPbU1ACxlCnIAFIt2V9u1RR3kGH3kOKA/trained_model.tar 2025-03-28T18:30:21Z | INFO | [ Complete ] dest=/tmp/tmpjjgzykxv/weights size="172 MB" total_elapsed=2.065s url=https://replicate.delivery/xezq/ePobUGdCbuWPIak1VSPbU1ACxlCnIAFIt2V9u1RR3kGH3kOKA/trained_model.tar Downloaded weights in 2.09s Loaded LoRAs in 2.64s Using seed: 57378 Prompt: uma foto do Helbert na cidade a noite [!] txt2img mode 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.81it/s] 7%|▋ | 2/28 [00:00<00:06, 4.32it/s] 11%|█ | 3/28 [00:00<00:06, 4.07it/s] 14%|█▍ | 4/28 [00:00<00:06, 3.96it/s] 18%|█▊ | 5/28 [00:01<00:05, 3.91it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.87it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.85it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.84it/s] 32%|███▏ | 9/28 [00:02<00:04, 3.83it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.82it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.82it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.82it/s] 46%|████▋ | 13/28 [00:03<00:03, 3.82it/s] 50%|█████ | 14/28 [00:03<00:03, 3.82it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.81it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.81it/s] 61%|██████ | 17/28 [00:04<00:02, 3.81it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.81it/s] 68%|██████▊ | 19/28 [00:04<00:02, 3.81it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.81it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.81it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.81it/s] 82%|████████▏ | 23/28 [00:05<00:01, 3.81it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.81it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.81it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.81it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.81it/s] 100%|██████████| 28/28 [00:07<00:00, 3.81it/s] 100%|██████████| 28/28 [00:07<00:00, 3.84it/s] Total safe images: 1 out of 1
Prediction
capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47ID9c5aw8ahasrma0cnvr38t6skhrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- uma foto do Helbert no parque a tarde, com uma camisa florida
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "uma foto do Helbert no parque a tarde, com uma camisa florida", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
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 capim-labs/helbert_costa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47", { input: { model: "dev", prompt: "uma foto do Helbert no parque a tarde, com uma camisa florida", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // 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
Import the client:import replicate
Run capim-labs/helbert_costa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47", input={ "model": "dev", "prompt": "uma foto do Helbert no parque a tarde, com uma camisa florida", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run capim-labs/helbert_costa 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": "capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47", "input": { "model": "dev", "prompt": "uma foto do Helbert no parque a tarde, com uma camisa florida", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-03-28T18:31:59.791159Z", "created_at": "2025-03-28T18:31:50.870000Z", "data_removed": false, "error": null, "id": "9c5aw8ahasrma0cnvr38t6skhr", "input": { "model": "dev", "prompt": "uma foto do Helbert no parque a tarde, com uma camisa florida", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "free=26996763222016\nDownloading weights\n2025-03-28T18:31:50Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp9xhyiasu/weights url=https://replicate.delivery/xezq/ePobUGdCbuWPIak1VSPbU1ACxlCnIAFIt2V9u1RR3kGH3kOKA/trained_model.tar\n2025-03-28T18:31:51Z | INFO | [ Complete ] dest=/tmp/tmp9xhyiasu/weights size=\"172 MB\" total_elapsed=0.725s url=https://replicate.delivery/xezq/ePobUGdCbuWPIak1VSPbU1ACxlCnIAFIt2V9u1RR3kGH3kOKA/trained_model.tar\nDownloaded weights in 0.75s\nLoaded LoRAs in 1.31s\nUsing seed: 14742\nPrompt: uma foto do Helbert no parque a tarde, com uma camisa florida\n[!] txt2img mode\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.81it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.31it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.07it/s]\n 14%|█▍ | 4/28 [00:00<00:06, 3.97it/s]\n 18%|█▊ | 5/28 [00:01<00:05, 3.91it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.88it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.86it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.83it/s]\n 32%|███▏ | 9/28 [00:02<00:04, 3.83it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.82it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.82it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.82it/s]\n 46%|████▋ | 13/28 [00:03<00:03, 3.82it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.82it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.82it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.82it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.82it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.81it/s]\n 68%|██████▊ | 19/28 [00:04<00:02, 3.82it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.82it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.81it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.81it/s]\n 82%|████████▏ | 23/28 [00:05<00:01, 3.82it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.81it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.81it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.81it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.81it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.81it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.84it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 8.913089241, "total_time": 8.921159 }, "output": [ "https://replicate.delivery/xezq/tYEtqLFbySZZFlCEC8aHNdzMv9b1hn7XNARfYf80Y69foT6oA/out-0.webp" ], "started_at": "2025-03-28T18:31:50.878070Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-2rixfw6vkzot2bxhgmgi3n2ndfdblchf7atmnnfi74upf3v24c7q", "get": "https://api.replicate.com/v1/predictions/9c5aw8ahasrma0cnvr38t6skhr", "cancel": "https://api.replicate.com/v1/predictions/9c5aw8ahasrma0cnvr38t6skhr/cancel" }, "version": "450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47" }
Generated infree=26996763222016 Downloading weights 2025-03-28T18:31:50Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp9xhyiasu/weights url=https://replicate.delivery/xezq/ePobUGdCbuWPIak1VSPbU1ACxlCnIAFIt2V9u1RR3kGH3kOKA/trained_model.tar 2025-03-28T18:31:51Z | INFO | [ Complete ] dest=/tmp/tmp9xhyiasu/weights size="172 MB" total_elapsed=0.725s url=https://replicate.delivery/xezq/ePobUGdCbuWPIak1VSPbU1ACxlCnIAFIt2V9u1RR3kGH3kOKA/trained_model.tar Downloaded weights in 0.75s Loaded LoRAs in 1.31s Using seed: 14742 Prompt: uma foto do Helbert no parque a tarde, com uma camisa florida [!] txt2img mode 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.81it/s] 7%|▋ | 2/28 [00:00<00:06, 4.31it/s] 11%|█ | 3/28 [00:00<00:06, 4.07it/s] 14%|█▍ | 4/28 [00:00<00:06, 3.97it/s] 18%|█▊ | 5/28 [00:01<00:05, 3.91it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.88it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.86it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.83it/s] 32%|███▏ | 9/28 [00:02<00:04, 3.83it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.82it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.82it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.82it/s] 46%|████▋ | 13/28 [00:03<00:03, 3.82it/s] 50%|█████ | 14/28 [00:03<00:03, 3.82it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.82it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.82it/s] 61%|██████ | 17/28 [00:04<00:02, 3.82it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.81it/s] 68%|██████▊ | 19/28 [00:04<00:02, 3.82it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.82it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.81it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.81it/s] 82%|████████▏ | 23/28 [00:05<00:01, 3.82it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.81it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.81it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.81it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.81it/s] 100%|██████████| 28/28 [00:07<00:00, 3.81it/s] 100%|██████████| 28/28 [00:07<00:00, 3.84it/s] Total safe images: 1 out of 1
Prediction
capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47ID05rzt3frcxrma0cnvr5bn1k698StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- uma foto do Helbert forte sem camisa na academia
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "uma foto do Helbert forte sem camisa na academia", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
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 capim-labs/helbert_costa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47", { input: { model: "dev", prompt: "uma foto do Helbert forte sem camisa na academia", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // 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
Import the client:import replicate
Run capim-labs/helbert_costa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47", input={ "model": "dev", "prompt": "uma foto do Helbert forte sem camisa na academia", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run capim-labs/helbert_costa 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": "capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47", "input": { "model": "dev", "prompt": "uma foto do Helbert forte sem camisa na academia", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-03-28T18:37:06.014960Z", "created_at": "2025-03-28T18:36:55.783000Z", "data_removed": false, "error": null, "id": "05rzt3frcxrma0cnvr5bn1k698", "input": { "model": "dev", "prompt": "uma foto do Helbert forte sem camisa na academia", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "free=25733694205952\nDownloading weights\n2025-03-28T18:36:55Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmptbs83mc2/weights url=https://replicate.delivery/xezq/ePobUGdCbuWPIak1VSPbU1ACxlCnIAFIt2V9u1RR3kGH3kOKA/trained_model.tar\n2025-03-28T18:36:57Z | INFO | [ Complete ] dest=/tmp/tmptbs83mc2/weights size=\"172 MB\" total_elapsed=2.063s url=https://replicate.delivery/xezq/ePobUGdCbuWPIak1VSPbU1ACxlCnIAFIt2V9u1RR3kGH3kOKA/trained_model.tar\nDownloaded weights in 2.08s\nLoaded LoRAs in 2.66s\nUsing seed: 40218\nPrompt: uma foto do Helbert forte sem camisa na academia\n[!] txt2img mode\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.81it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.32it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.07it/s]\n 14%|█▍ | 4/28 [00:00<00:06, 3.97it/s]\n 18%|█▊ | 5/28 [00:01<00:05, 3.92it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.88it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.86it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.85it/s]\n 32%|███▏ | 9/28 [00:02<00:04, 3.84it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.84it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.83it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.82it/s]\n 46%|████▋ | 13/28 [00:03<00:03, 3.82it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.82it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.82it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.82it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.82it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.82it/s]\n 68%|██████▊ | 19/28 [00:04<00:02, 3.82it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.82it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.82it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.82it/s]\n 82%|████████▏ | 23/28 [00:05<00:01, 3.82it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.82it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.81it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.81it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.81it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.82it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.84it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 10.214441016, "total_time": 10.23196 }, "output": [ "https://replicate.delivery/xezq/ovpWQnloKi6dCtnpbjc2OCmAhaTx0WbKssWyOMMj9xrUekOKA/out-0.webp" ], "started_at": "2025-03-28T18:36:55.800519Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-ynregf5w6og3ljcn7l2vabpj4aw4gum4q4fpo2g5s6r2tyeea6xq", "get": "https://api.replicate.com/v1/predictions/05rzt3frcxrma0cnvr5bn1k698", "cancel": "https://api.replicate.com/v1/predictions/05rzt3frcxrma0cnvr5bn1k698/cancel" }, "version": "450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47" }
Generated infree=25733694205952 Downloading weights 2025-03-28T18:36:55Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmptbs83mc2/weights url=https://replicate.delivery/xezq/ePobUGdCbuWPIak1VSPbU1ACxlCnIAFIt2V9u1RR3kGH3kOKA/trained_model.tar 2025-03-28T18:36:57Z | INFO | [ Complete ] dest=/tmp/tmptbs83mc2/weights size="172 MB" total_elapsed=2.063s url=https://replicate.delivery/xezq/ePobUGdCbuWPIak1VSPbU1ACxlCnIAFIt2V9u1RR3kGH3kOKA/trained_model.tar Downloaded weights in 2.08s Loaded LoRAs in 2.66s Using seed: 40218 Prompt: uma foto do Helbert forte sem camisa na academia [!] txt2img mode 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.81it/s] 7%|▋ | 2/28 [00:00<00:06, 4.32it/s] 11%|█ | 3/28 [00:00<00:06, 4.07it/s] 14%|█▍ | 4/28 [00:00<00:06, 3.97it/s] 18%|█▊ | 5/28 [00:01<00:05, 3.92it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.88it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.86it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.85it/s] 32%|███▏ | 9/28 [00:02<00:04, 3.84it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.84it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.83it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.82it/s] 46%|████▋ | 13/28 [00:03<00:03, 3.82it/s] 50%|█████ | 14/28 [00:03<00:03, 3.82it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.82it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.82it/s] 61%|██████ | 17/28 [00:04<00:02, 3.82it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.82it/s] 68%|██████▊ | 19/28 [00:04<00:02, 3.82it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.82it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.82it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.82it/s] 82%|████████▏ | 23/28 [00:05<00:01, 3.82it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.82it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.81it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.81it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.81it/s] 100%|██████████| 28/28 [00:07<00:00, 3.82it/s] 100%|██████████| 28/28 [00:07<00:00, 3.84it/s] Total safe images: 1 out of 1
Prediction
capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47IDx2n6n2a2h1rm80cnvr98gxc194StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Retrato realista de Helbert, um piloto destemido, com olhar determinado e traços marcantes, vestindo um uniforme de piloto clássico. Helbert está no cockpit de um avião vintage, cercado por instrumentos de voo detalhados e luz suave do pôr do sol entrando pela janela. O fundo revela um céu amplo com nuvens delicadas e cores quentes, conferindo à cena uma atmosfera cinematográfica e inspiradora.
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "Retrato realista de Helbert, um piloto destemido, com olhar determinado e traços marcantes, vestindo um uniforme de piloto clássico. Helbert está no cockpit de um avião vintage, cercado por instrumentos de voo detalhados e luz suave do pôr do sol entrando pela janela. O fundo revela um céu amplo com nuvens delicadas e cores quentes, conferindo à cena uma atmosfera cinematográfica e inspiradora.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
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 capim-labs/helbert_costa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47", { input: { model: "dev", prompt: "Retrato realista de Helbert, um piloto destemido, com olhar determinado e traços marcantes, vestindo um uniforme de piloto clássico. Helbert está no cockpit de um avião vintage, cercado por instrumentos de voo detalhados e luz suave do pôr do sol entrando pela janela. O fundo revela um céu amplo com nuvens delicadas e cores quentes, conferindo à cena uma atmosfera cinematográfica e inspiradora.", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // 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
Import the client:import replicate
Run capim-labs/helbert_costa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47", input={ "model": "dev", "prompt": "Retrato realista de Helbert, um piloto destemido, com olhar determinado e traços marcantes, vestindo um uniforme de piloto clássico. Helbert está no cockpit de um avião vintage, cercado por instrumentos de voo detalhados e luz suave do pôr do sol entrando pela janela. O fundo revela um céu amplo com nuvens delicadas e cores quentes, conferindo à cena uma atmosfera cinematográfica e inspiradora.", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run capim-labs/helbert_costa 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": "capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47", "input": { "model": "dev", "prompt": "Retrato realista de Helbert, um piloto destemido, com olhar determinado e traços marcantes, vestindo um uniforme de piloto clássico. Helbert está no cockpit de um avião vintage, cercado por instrumentos de voo detalhados e luz suave do pôr do sol entrando pela janela. O fundo revela um céu amplo com nuvens delicadas e cores quentes, conferindo à cena uma atmosfera cinematográfica e inspiradora.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-03-28T18:45:02.719857Z", "created_at": "2025-03-28T18:44:53.512000Z", "data_removed": false, "error": null, "id": "x2n6n2a2h1rm80cnvr98gxc194", "input": { "model": "dev", "prompt": "Retrato realista de Helbert, um piloto destemido, com olhar determinado e traços marcantes, vestindo um uniforme de piloto clássico. Helbert está no cockpit de um avião vintage, cercado por instrumentos de voo detalhados e luz suave do pôr do sol entrando pela janela. O fundo revela um céu amplo com nuvens delicadas e cores quentes, conferindo à cena uma atmosfera cinematográfica e inspiradora.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Loaded LoRAs in 0.57s\nUsing seed: 55499\nPrompt: Retrato realista de Helbert, um piloto destemido, com olhar determinado e traços marcantes, vestindo um uniforme de piloto clássico. Helbert está no cockpit de um avião vintage, cercado por instrumentos de voo detalhados e luz suave do pôr do sol entrando pela janela. O fundo revela um céu amplo com nuvens delicadas e cores quentes, conferindo à cena uma atmosfera cinematográfica e inspiradora.\n[!] txt2img mode\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.79it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.30it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.06it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.95it/s]\n 18%|█▊ | 5/28 [00:01<00:05, 3.90it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.86it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.85it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.83it/s]\n 32%|███▏ | 9/28 [00:02<00:04, 3.82it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.82it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.81it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.81it/s]\n 46%|████▋ | 13/28 [00:03<00:03, 3.81it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.81it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.81it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.80it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.80it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.80it/s]\n 68%|██████▊ | 19/28 [00:04<00:02, 3.80it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.80it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.80it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.80it/s]\n 82%|████████▏ | 23/28 [00:05<00:01, 3.80it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.80it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.80it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.80it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.80it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.80it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.83it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 8.162837384, "total_time": 9.207857 }, "output": [ "https://replicate.delivery/xezq/rG0eHT2JubUyKqOeL4ibC1r9HXZXe1kxcNBWC4pawPMdBU6oA/out-0.webp" ], "started_at": "2025-03-28T18:44:54.557019Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-ati75qqgmpsia5wosdpusm3e53ezqi3r4dy76q4rhhtznlie66aq", "get": "https://api.replicate.com/v1/predictions/x2n6n2a2h1rm80cnvr98gxc194", "cancel": "https://api.replicate.com/v1/predictions/x2n6n2a2h1rm80cnvr98gxc194/cancel" }, "version": "450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47" }
Generated inLoaded LoRAs in 0.57s Using seed: 55499 Prompt: Retrato realista de Helbert, um piloto destemido, com olhar determinado e traços marcantes, vestindo um uniforme de piloto clássico. Helbert está no cockpit de um avião vintage, cercado por instrumentos de voo detalhados e luz suave do pôr do sol entrando pela janela. O fundo revela um céu amplo com nuvens delicadas e cores quentes, conferindo à cena uma atmosfera cinematográfica e inspiradora. [!] txt2img mode 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.79it/s] 7%|▋ | 2/28 [00:00<00:06, 4.30it/s] 11%|█ | 3/28 [00:00<00:06, 4.06it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.95it/s] 18%|█▊ | 5/28 [00:01<00:05, 3.90it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.86it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.85it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.83it/s] 32%|███▏ | 9/28 [00:02<00:04, 3.82it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.82it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.81it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.81it/s] 46%|████▋ | 13/28 [00:03<00:03, 3.81it/s] 50%|█████ | 14/28 [00:03<00:03, 3.81it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.81it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.80it/s] 61%|██████ | 17/28 [00:04<00:02, 3.80it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.80it/s] 68%|██████▊ | 19/28 [00:04<00:02, 3.80it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.80it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.80it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.80it/s] 82%|████████▏ | 23/28 [00:05<00:01, 3.80it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.80it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.80it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.80it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.80it/s] 100%|██████████| 28/28 [00:07<00:00, 3.80it/s] 100%|██████████| 28/28 [00:07<00:00, 3.83it/s] Total safe images: 1 out of 1
Prediction
capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47IDkygask6xp9rma0cnvr9tjcwsq0StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- A highly detailed and realistic photograph of Helbert, a skilled pilot with a determined expression, sitting in the cockpit of an aircraft. He is wearing a professional pilot uniform with a headset, his hands confidently on the controls. The cockpit is filled with intricate flight instruments, illuminated by natural light. Through the windshield, a stunning view of the sky with scattered clouds and a warm sunset glow creates a cinematic atmosphere. The image has a sharp focus on Helbert's face and the cockpit details, with a slightly blurred background for depth.
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "A highly detailed and realistic photograph of Helbert, a skilled pilot with a determined expression, sitting in the cockpit of an aircraft. He is wearing a professional pilot uniform with a headset, his hands confidently on the controls. The cockpit is filled with intricate flight instruments, illuminated by natural light. Through the windshield, a stunning view of the sky with scattered clouds and a warm sunset glow creates a cinematic atmosphere. The image has a sharp focus on Helbert's face and the cockpit details, with a slightly blurred background for depth.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
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 capim-labs/helbert_costa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47", { input: { model: "dev", prompt: "A highly detailed and realistic photograph of Helbert, a skilled pilot with a determined expression, sitting in the cockpit of an aircraft. He is wearing a professional pilot uniform with a headset, his hands confidently on the controls. The cockpit is filled with intricate flight instruments, illuminated by natural light. Through the windshield, a stunning view of the sky with scattered clouds and a warm sunset glow creates a cinematic atmosphere. The image has a sharp focus on Helbert's face and the cockpit details, with a slightly blurred background for depth.", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // 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
Import the client:import replicate
Run capim-labs/helbert_costa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47", input={ "model": "dev", "prompt": "A highly detailed and realistic photograph of Helbert, a skilled pilot with a determined expression, sitting in the cockpit of an aircraft. He is wearing a professional pilot uniform with a headset, his hands confidently on the controls. The cockpit is filled with intricate flight instruments, illuminated by natural light. Through the windshield, a stunning view of the sky with scattered clouds and a warm sunset glow creates a cinematic atmosphere. The image has a sharp focus on Helbert's face and the cockpit details, with a slightly blurred background for depth.", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run capim-labs/helbert_costa 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": "capim-labs/helbert_costa:450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47", "input": { "model": "dev", "prompt": "A highly detailed and realistic photograph of Helbert, a skilled pilot with a determined expression, sitting in the cockpit of an aircraft. He is wearing a professional pilot uniform with a headset, his hands confidently on the controls. The cockpit is filled with intricate flight instruments, illuminated by natural light. Through the windshield, a stunning view of the sky with scattered clouds and a warm sunset glow creates a cinematic atmosphere. The image has a sharp focus on Helbert\'s face and the cockpit details, with a slightly blurred background for depth.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-03-28T18:46:51.347468Z", "created_at": "2025-03-28T18:46:38.770000Z", "data_removed": false, "error": null, "id": "kygask6xp9rma0cnvr9tjcwsq0", "input": { "model": "dev", "prompt": "A highly detailed and realistic photograph of Helbert, a skilled pilot with a determined expression, sitting in the cockpit of an aircraft. He is wearing a professional pilot uniform with a headset, his hands confidently on the controls. The cockpit is filled with intricate flight instruments, illuminated by natural light. Through the windshield, a stunning view of the sky with scattered clouds and a warm sunset glow creates a cinematic atmosphere. The image has a sharp focus on Helbert's face and the cockpit details, with a slightly blurred background for depth.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "free=25986925391872\nDownloading weights\n2025-03-28T18:46:38Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpv12aqdoo/weights url=https://replicate.delivery/xezq/ePobUGdCbuWPIak1VSPbU1ACxlCnIAFIt2V9u1RR3kGH3kOKA/trained_model.tar\n2025-03-28T18:46:41Z | INFO | [ Complete ] dest=/tmp/tmpv12aqdoo/weights size=\"172 MB\" total_elapsed=2.351s url=https://replicate.delivery/xezq/ePobUGdCbuWPIak1VSPbU1ACxlCnIAFIt2V9u1RR3kGH3kOKA/trained_model.tar\nDownloaded weights in 2.37s\nLoaded LoRAs in 4.90s\nUsing seed: 44253\nPrompt: A highly detailed and realistic photograph of Helbert, a skilled pilot with a determined expression, sitting in the cockpit of an aircraft. He is wearing a professional pilot uniform with a headset, his hands confidently on the controls. The cockpit is filled with intricate flight instruments, illuminated by natural light. Through the windshield, a stunning view of the sky with scattered clouds and a warm sunset glow creates a cinematic atmosphere. The image has a sharp focus on Helbert's face and the cockpit details, with a slightly blurred background for depth.\n[!] txt2img mode\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.80it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.31it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.07it/s]\n 14%|█▍ | 4/28 [00:00<00:06, 3.97it/s]\n 18%|█▊ | 5/28 [00:01<00:05, 3.91it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.88it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.86it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.84it/s]\n 32%|███▏ | 9/28 [00:02<00:04, 3.84it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.83it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.82it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.82it/s]\n 46%|████▋ | 13/28 [00:03<00:03, 3.81it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.81it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.81it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.81it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.81it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.81it/s]\n 68%|██████▊ | 19/28 [00:04<00:02, 3.81it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.81it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.81it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.81it/s]\n 82%|████████▏ | 23/28 [00:05<00:01, 3.81it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.81it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.81it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.81it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.81it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.81it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.84it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 12.471639538, "total_time": 12.577468 }, "output": [ "https://replicate.delivery/xezq/hjKFgGmHK7LyLZnlrjpcMi3bVTTQ75lOzTJeDVebu1HbCKdUA/out-0.webp" ], "started_at": "2025-03-28T18:46:38.875828Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-kbx2zad54xrfmqcewo6q4pu7inifhf6ml3zyvd2nih2jgyhxnaqq", "get": "https://api.replicate.com/v1/predictions/kygask6xp9rma0cnvr9tjcwsq0", "cancel": "https://api.replicate.com/v1/predictions/kygask6xp9rma0cnvr9tjcwsq0/cancel" }, "version": "450ba9c397c8379eaf3b4a34e4553f0a2d4140f14330207ebb7ca02a23197a47" }
Generated infree=25986925391872 Downloading weights 2025-03-28T18:46:38Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpv12aqdoo/weights url=https://replicate.delivery/xezq/ePobUGdCbuWPIak1VSPbU1ACxlCnIAFIt2V9u1RR3kGH3kOKA/trained_model.tar 2025-03-28T18:46:41Z | INFO | [ Complete ] dest=/tmp/tmpv12aqdoo/weights size="172 MB" total_elapsed=2.351s url=https://replicate.delivery/xezq/ePobUGdCbuWPIak1VSPbU1ACxlCnIAFIt2V9u1RR3kGH3kOKA/trained_model.tar Downloaded weights in 2.37s Loaded LoRAs in 4.90s Using seed: 44253 Prompt: A highly detailed and realistic photograph of Helbert, a skilled pilot with a determined expression, sitting in the cockpit of an aircraft. He is wearing a professional pilot uniform with a headset, his hands confidently on the controls. The cockpit is filled with intricate flight instruments, illuminated by natural light. Through the windshield, a stunning view of the sky with scattered clouds and a warm sunset glow creates a cinematic atmosphere. The image has a sharp focus on Helbert's face and the cockpit details, with a slightly blurred background for depth. [!] txt2img mode 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.80it/s] 7%|▋ | 2/28 [00:00<00:06, 4.31it/s] 11%|█ | 3/28 [00:00<00:06, 4.07it/s] 14%|█▍ | 4/28 [00:00<00:06, 3.97it/s] 18%|█▊ | 5/28 [00:01<00:05, 3.91it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.88it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.86it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.84it/s] 32%|███▏ | 9/28 [00:02<00:04, 3.84it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.83it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.82it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.82it/s] 46%|████▋ | 13/28 [00:03<00:03, 3.81it/s] 50%|█████ | 14/28 [00:03<00:03, 3.81it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.81it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.81it/s] 61%|██████ | 17/28 [00:04<00:02, 3.81it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.81it/s] 68%|██████▊ | 19/28 [00:04<00:02, 3.81it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.81it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.81it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.81it/s] 82%|████████▏ | 23/28 [00:05<00:01, 3.81it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.81it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.81it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.81it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.81it/s] 100%|██████████| 28/28 [00:07<00:00, 3.81it/s] 100%|██████████| 28/28 [00:07<00:00, 3.84it/s] Total safe images: 1 out of 1
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