zsxkib/flux-dev-inpainting-controlnet
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flux-dev-inpainting-controlnet
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zsxkib/flux-dev-inpainting-controlnet
FLUX.1-dev Inpainting ControlNet model
zsxkib/hello-world
A "Hello World" model for me to get to grips with `cog` and Replicate
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Transform your text into a beautiful two-tone color gradient that represents your emotions.
zsxkib/clip-age-predictor
Age prediction using CLIP - Patched version of `https://replicate.com/andreasjansson/clip-age-predictor` that works with the new version of cog!
zsxkib/lil-flan-bias-logits-warper
Logit Warping via Biases for Google's FLAN-T5-small
zsxkib/draggan
🐲 DragGAN 🐉 - "Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold"
zsxkib/st-mfnet
📽️ Increase Framerate 🎬 ST-MFNet: A Spatio-Temporal Multi-Flow Network for Frame Interpolation
zsxkib/animate-diff
🎨 AnimateDiff (w/ MotionLoRAs for Panning, Zooming, etc): Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning
zsxkib/diffbir
✨DiffBIR: Towards Blind Image Restoration with Generative Diffusion Prior
zsxkib/animatediff-prompt-travel
🎨AnimateDiff Prompt Travel🧭 Seamlessly Navigate and Animate Between Text-to-Image Prompts for Dynamic Visual Narratives
zsxkib/animatediff-illusions
Monster Labs' Controlnet QR Code Monster v2 For SD-1.5 on top of AnimateDiff Prompt Travel (Motion Module SD 1.5 v2)
zsxkib/film-frame-interpolation-for-large-motion
FILM: Frame Interpolation for Large Motion, In ECCV 2022.
zsxkib/stable-diffusion-safety-checker
Identifies NSFW images
zsxkib/realistic-voice-cloning
Create song covers with any RVC v2 trained AI voice from audio files.
zsxkib/create-rvc-dataset
Create your own Realistic Voice Cloning (RVC v2) dataset using a YouTube link
zsxkib/patch-fusion
Super High Quality Depth Maps 🗺️: An End-to-End Tile-Based Framework 🏗️ for High-Resolution Monocular Metric Depth Estimation 🔍📏
zsxkib/moore-animateanyone
Unofficial Re-Trained AnimateAnyone (Image + DWPose Video → Animated Video of Image)
zsxkib/instant-id
Make realistic images of real people instantly
zsxkib/uform-gen
🖼️ Super fast 1.5B Image Captioning/VQA Multimodal LLM (Image-to-Text) 🖋️
zsxkib/yolo-world
Real-Time Open-Vocabulary Object Detection
zsxkib/talknet-asd
🗣️ TalkNet-ASD: Detect who is speaking in a video
Prediction
zsxkib/flux-dev-inpainting-controlnet:f9cb02cfd6b131af7ff9166b4bac5fdd2ed68bc282d2c049b95a23cea485e40dID4s0xrbym4drj60cj0rvbnbq0fcStatusSucceededSourceWebHardwareA100 (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 replicateImport 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 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 } } ); // 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 replicateImport 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 } ) # 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.
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": "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 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
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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