zsxkib
/
flux-dev-inpainting-controlnet
FLUX.1-dev Inpainting ControlNet model
Prediction
zsxkib/flux-dev-inpainting-controlnet:f9cb02cfID4s0xrbym4drj60cj0rvbnbq0fcStatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedby @zsxkibInput
- mask
- image
- prompt
- a person wearing a white shoe, carrying a white bucket with text 'REPLICATE FLUX INPAINTING CONTROLNET' on it
- num_outputs
- 10
- output_format
- png
- guidance_scale
- 3.5
- output_quality
- 80
- negative_prompt
- num_inference_steps
- 28
- true_guidance_scale
- 3.5
- controlnet_conditioning_scale
- 0.9
{ "mask": "https://replicate.delivery/pbxt/Le6GAg8i6DrhZxvjibNmzKy4jPYEKIhH8DBZnUp2WAioguXI/bucket_mask.jpeg", "image": "https://replicate.delivery/pbxt/Le6GAdIHbCc7u5RAFQ09dqJoROHEayxjWQbg9Hx16aY2fa9L/bucket.png", "prompt": "a person wearing a white shoe, carrying a white bucket with text 'REPLICATE FLUX INPAINTING CONTROLNET' on it", "num_outputs": 10, "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "negative_prompt": "", "num_inference_steps": 28, "true_guidance_scale": 3.5, "controlnet_conditioning_scale": 0.9 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment 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 zsxkib/flux-dev-inpainting-controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zsxkib/flux-dev-inpainting-controlnet:f9cb02cfd6b131af7ff9166b4bac5fdd2ed68bc282d2c049b95a23cea485e40d", { input: { mask: "https://replicate.delivery/pbxt/Le6GAg8i6DrhZxvjibNmzKy4jPYEKIhH8DBZnUp2WAioguXI/bucket_mask.jpeg", image: "https://replicate.delivery/pbxt/Le6GAdIHbCc7u5RAFQ09dqJoROHEayxjWQbg9Hx16aY2fa9L/bucket.png", prompt: "a person wearing a white shoe, carrying a white bucket with text 'REPLICATE FLUX INPAINTING CONTROLNET' on it", num_outputs: 10, output_format: "png", guidance_scale: 3.5, output_quality: 80, negative_prompt: "", num_inference_steps: 28, true_guidance_scale: 3.5, controlnet_conditioning_scale: 0.9 } } ); 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 replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun zsxkib/flux-dev-inpainting-controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zsxkib/flux-dev-inpainting-controlnet:f9cb02cfd6b131af7ff9166b4bac5fdd2ed68bc282d2c049b95a23cea485e40d", input={ "mask": "https://replicate.delivery/pbxt/Le6GAg8i6DrhZxvjibNmzKy4jPYEKIhH8DBZnUp2WAioguXI/bucket_mask.jpeg", "image": "https://replicate.delivery/pbxt/Le6GAdIHbCc7u5RAFQ09dqJoROHEayxjWQbg9Hx16aY2fa9L/bucket.png", "prompt": "a person wearing a white shoe, carrying a white bucket with text 'REPLICATE FLUX INPAINTING CONTROLNET' on it", "num_outputs": 10, "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "negative_prompt": "", "num_inference_steps": 28, "true_guidance_scale": 3.5, "controlnet_conditioning_scale": 0.9 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run zsxkib/flux-dev-inpainting-controlnet 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": "f9cb02cfd6b131af7ff9166b4bac5fdd2ed68bc282d2c049b95a23cea485e40d", "input": { "mask": "https://replicate.delivery/pbxt/Le6GAg8i6DrhZxvjibNmzKy4jPYEKIhH8DBZnUp2WAioguXI/bucket_mask.jpeg", "image": "https://replicate.delivery/pbxt/Le6GAdIHbCc7u5RAFQ09dqJoROHEayxjWQbg9Hx16aY2fa9L/bucket.png", "prompt": "a person wearing a white shoe, carrying a white bucket with text \'REPLICATE FLUX INPAINTING CONTROLNET\' on it", "num_outputs": 10, "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "negative_prompt": "", "num_inference_steps": 28, "true_guidance_scale": 3.5, "controlnet_conditioning_scale": 0.9 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/zsxkib/flux-dev-inpainting-controlnet@sha256:f9cb02cfd6b131af7ff9166b4bac5fdd2ed68bc282d2c049b95a23cea485e40d \ -i 'mask="https://replicate.delivery/pbxt/Le6GAg8i6DrhZxvjibNmzKy4jPYEKIhH8DBZnUp2WAioguXI/bucket_mask.jpeg"' \ -i 'image="https://replicate.delivery/pbxt/Le6GAdIHbCc7u5RAFQ09dqJoROHEayxjWQbg9Hx16aY2fa9L/bucket.png"' \ -i $'prompt="a person wearing a white shoe, carrying a white bucket with text \'REPLICATE FLUX INPAINTING CONTROLNET\' on it"' \ -i 'num_outputs=10' \ -i 'output_format="png"' \ -i 'guidance_scale=3.5' \ -i 'output_quality=80' \ -i 'negative_prompt=""' \ -i 'num_inference_steps=28' \ -i 'true_guidance_scale=3.5' \ -i 'controlnet_conditioning_scale=0.9'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/zsxkib/flux-dev-inpainting-controlnet@sha256:f9cb02cfd6b131af7ff9166b4bac5fdd2ed68bc282d2c049b95a23cea485e40dcurl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "mask": "https://replicate.delivery/pbxt/Le6GAg8i6DrhZxvjibNmzKy4jPYEKIhH8DBZnUp2WAioguXI/bucket_mask.jpeg", "image": "https://replicate.delivery/pbxt/Le6GAdIHbCc7u5RAFQ09dqJoROHEayxjWQbg9Hx16aY2fa9L/bucket.png", "prompt": "a person wearing a white shoe, carrying a white bucket with text \'REPLICATE FLUX INPAINTING CONTROLNET\' on it", "num_outputs": 10, "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "negative_prompt": "", "num_inference_steps": 28, "true_guidance_scale": 3.5, "controlnet_conditioning_scale": 0.9 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-09-18T17:42:18.944281Z", "created_at": "2024-09-18T17:38:29.539000Z", "data_removed": false, "error": null, "id": "4s0xrbym4drj60cj0rvbnbq0fc", "input": { "mask": "https://replicate.delivery/pbxt/Le6GAg8i6DrhZxvjibNmzKy4jPYEKIhH8DBZnUp2WAioguXI/bucket_mask.jpeg", "image": "https://replicate.delivery/pbxt/Le6GAdIHbCc7u5RAFQ09dqJoROHEayxjWQbg9Hx16aY2fa9L/bucket.png", "prompt": "a person wearing a white shoe, carrying a white bucket with text 'REPLICATE FLUX INPAINTING CONTROLNET' on it", "num_outputs": 10, "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "negative_prompt": "", "num_inference_steps": 28, "true_guidance_scale": 3.5, "controlnet_conditioning_scale": 0.9 }, "logs": "Using seeds: [3765371973, 895665373, 4238102399, 1156424636, 866625007, 1217664626, 54085831, 2643616561, 334270782, 636282773]\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:06<02:46, 6.16s/it]\n 7%|▋ | 2/28 [00:10<02:05, 4.82s/it]\n 11%|█ | 3/28 [00:16<02:15, 5.43s/it]\n 14%|█▍ | 4/28 [00:22<02:17, 5.72s/it]\n 18%|█▊ | 5/28 [00:28<02:15, 5.88s/it]\n 21%|██▏ | 6/28 [00:34<02:11, 5.98s/it]\n 25%|██▌ | 7/28 [00:40<02:06, 6.04s/it]\n 29%|██▊ | 8/28 [00:47<02:01, 6.09s/it]\n 32%|███▏ | 9/28 [00:53<01:56, 6.12s/it]\n 36%|███▌ | 10/28 [00:59<01:50, 6.14s/it]\n 39%|███▉ | 11/28 [01:05<01:44, 6.16s/it]\n 43%|████▎ | 12/28 [01:11<01:38, 6.17s/it]\n 46%|████▋ | 13/28 [01:18<01:32, 6.18s/it]\n 50%|█████ | 14/28 [01:24<01:26, 6.19s/it]\n 54%|█████▎ | 15/28 [01:30<01:20, 6.19s/it]\n 57%|█████▋ | 16/28 [01:36<01:14, 6.19s/it]\n 61%|██████ | 17/28 [01:42<01:08, 6.19s/it]\n 64%|██████▍ | 18/28 [01:49<01:01, 6.20s/it]\n 68%|██████▊ | 19/28 [01:55<00:55, 6.20s/it]\n 71%|███████▏ | 20/28 [02:01<00:49, 6.20s/it]\n 75%|███████▌ | 21/28 [02:07<00:43, 6.20s/it]\n 79%|███████▊ | 22/28 [02:13<00:37, 6.20s/it]\n 82%|████████▏ | 23/28 [02:20<00:30, 6.20s/it]\n 86%|████████▌ | 24/28 [02:26<00:24, 6.20s/it]\n 89%|████████▉ | 25/28 [02:32<00:18, 6.20s/it]\n 93%|█████████▎| 26/28 [02:38<00:12, 6.20s/it]\n 96%|█████████▋| 27/28 [02:44<00:06, 6.20s/it]\n100%|██████████| 28/28 [02:51<00:00, 6.20s/it]\n100%|██████████| 28/28 [02:51<00:00, 6.11s/it]\n[~] Saving to /tmp/output_0.png...\n[~] Output format: PNG\n[~] Saving to /tmp/output_1.png...\n[~] Output format: PNG\n[~] Saving to /tmp/output_2.png...\n[~] Output format: PNG\n[~] Saving to /tmp/output_3.png...\n[~] Output format: PNG\n[~] Saving to /tmp/output_4.png...\n[~] Output format: PNG\n[~] Saving to /tmp/output_5.png...\n[~] Output format: PNG\n[~] Saving to /tmp/output_6.png...\n[~] Output format: PNG\n[~] Saving to /tmp/output_7.png...\n[~] Output format: PNG\n[~] Saving to /tmp/output_8.png...\n[~] Output format: PNG\n[~] Saving to /tmp/output_9.png...\n[~] Output format: PNG", "metrics": { "predict_time": 181.000114541, "total_time": 229.405281 }, "output": [ "https://replicate.delivery/yhqm/BXeAEBzlV3yYTafsvvs81z4AvR2HNEBPD215wfgVvduwXY8mA/output_0.png", "https://replicate.delivery/yhqm/Wezid0X143yEZCgffBeRvxQKU5A2pzjOsLXaP0GWEfAMfCj3E/output_1.png", "https://replicate.delivery/yhqm/fNFqwbcUm7Q9LihinfCXnmWTe3fpog5Lz96fxMC5TxiLfCj3E/output_2.png", "https://replicate.delivery/yhqm/VXLSVz1bH74CK1qSd1v990NsiftTloQIKSAq8E0fnv95LMemA/output_3.png", "https://replicate.delivery/yhqm/35mLtvj6NfRPWaqDwzqXyw2Igb67Uyy6e5Cu9g2Qc4W5LMemA/output_4.png", "https://replicate.delivery/yhqm/DVAykB6LlxYcN9rqguMpCzIWEm5IKjhNkQLTvaKDJJYeFGvJA/output_5.png", "https://replicate.delivery/yhqm/uYTn7Y2WeB28JSNqnHN0LNY7f6Eu1aX6cIt9MElnFci6LMemA/output_6.png", "https://replicate.delivery/yhqm/HnUYUvmBsqaSEtjnaiHznUrfPJf99RaT5ltOStuXv536LMemA/output_7.png", "https://replicate.delivery/yhqm/mxp5JGUGR8qbCVD7rhbfwZjGdjrmnpic8RzDJvXQ3zE9FGvJA/output_8.png", "https://replicate.delivery/yhqm/hKt4gNptAJ65FtbBk3bSR70Q3Jeeo2ybKzxc0wB44JP6LMemA/output_9.png" ], "started_at": "2024-09-18T17:39:17.944166Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/4s0xrbym4drj60cj0rvbnbq0fc", "cancel": "https://api.replicate.com/v1/predictions/4s0xrbym4drj60cj0rvbnbq0fc/cancel" }, "version": "f9cb02cfd6b131af7ff9166b4bac5fdd2ed68bc282d2c049b95a23cea485e40d" }Generated inUsing seeds: [3765371973, 895665373, 4238102399, 1156424636, 866625007, 1217664626, 54085831, 2643616561, 334270782, 636282773] 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:06<02:46, 6.16s/it] 7%|▋ | 2/28 [00:10<02:05, 4.82s/it] 11%|█ | 3/28 [00:16<02:15, 5.43s/it] 14%|█▍ | 4/28 [00:22<02:17, 5.72s/it] 18%|█▊ | 5/28 [00:28<02:15, 5.88s/it] 21%|██▏ | 6/28 [00:34<02:11, 5.98s/it] 25%|██▌ | 7/28 [00:40<02:06, 6.04s/it] 29%|██▊ | 8/28 [00:47<02:01, 6.09s/it] 32%|███▏ | 9/28 [00:53<01:56, 6.12s/it] 36%|███▌ | 10/28 [00:59<01:50, 6.14s/it] 39%|███▉ | 11/28 [01:05<01:44, 6.16s/it] 43%|████▎ | 12/28 [01:11<01:38, 6.17s/it] 46%|████▋ | 13/28 [01:18<01:32, 6.18s/it] 50%|█████ | 14/28 [01:24<01:26, 6.19s/it] 54%|█████▎ | 15/28 [01:30<01:20, 6.19s/it] 57%|█████▋ | 16/28 [01:36<01:14, 6.19s/it] 61%|██████ | 17/28 [01:42<01:08, 6.19s/it] 64%|██████▍ | 18/28 [01:49<01:01, 6.20s/it] 68%|██████▊ | 19/28 [01:55<00:55, 6.20s/it] 71%|███████▏ | 20/28 [02:01<00:49, 6.20s/it] 75%|███████▌ | 21/28 [02:07<00:43, 6.20s/it] 79%|███████▊ | 22/28 [02:13<00:37, 6.20s/it] 82%|████████▏ | 23/28 [02:20<00:30, 6.20s/it] 86%|████████▌ | 24/28 [02:26<00:24, 6.20s/it] 89%|████████▉ | 25/28 [02:32<00:18, 6.20s/it] 93%|█████████▎| 26/28 [02:38<00:12, 6.20s/it] 96%|█████████▋| 27/28 [02:44<00:06, 6.20s/it] 100%|██████████| 28/28 [02:51<00:00, 6.20s/it] 100%|██████████| 28/28 [02:51<00:00, 6.11s/it] [~] Saving to /tmp/output_0.png... [~] Output format: PNG [~] Saving to /tmp/output_1.png... [~] Output format: PNG [~] Saving to /tmp/output_2.png... [~] Output format: PNG [~] Saving to /tmp/output_3.png... [~] Output format: PNG [~] Saving to /tmp/output_4.png... [~] Output format: PNG [~] Saving to /tmp/output_5.png... [~] Output format: PNG [~] Saving to /tmp/output_6.png... [~] Output format: PNG [~] Saving to /tmp/output_7.png... [~] Output format: PNG [~] Saving to /tmp/output_8.png... [~] Output format: PNG [~] Saving to /tmp/output_9.png... [~] Output format: PNG
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