qr2ai
/
outline
From Sketch to Reality: Transforming Outlines into Lifelike Images
- Public
- 46.1K runs
-
A100 (80GB)
Prediction
qr2ai/outline:6f713aebIDq5c36e43k5rj60ck14hatd9324StatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- seed
- 0
- width
- 1024
- height
- 1024
- prompt
- Modern skyscraper, glass facade, urban skyline, clear day.
- sampler
- Euler a
- blur_size
- 3
- use_canny
- lora_input
- lora_scale
- kernel_size
- 3
- num_outputs
- 1
- sketch_type
- HedPidNet
- suffix_prompt
- Futuristic Concept, Cutting-Edge Technology, Historical Landmark, Timeless Aesthetics, sharp focus, 8k, uhd, file grain, masterpiece
- guidance_scale
- 7.5
- weight_primary
- 0.7
- generate_square
- negative_prompt
- deformed, animation, anime, cartoon, comic, cropped, out of frame, low res, draft, cgi, low quality render, thumbnail
- weight_secondary
- 0.6
- erosion_iterations
- 2
- dilation_iterations
- 1
- num_inference_steps
- 35
- adapter_conditioning_scale
- 0.9
{ "seed": 0, "image": "https://replicate.delivery/pbxt/Lcg9dtkX66pSWfULefLA7UMExDQoonK9lmdA9y1R6kbEF9Q6/outline.png", "width": 1024, "height": 1024, "prompt": "Modern skyscraper, glass facade, urban skyline, clear day.", "sampler": "Euler a", "blur_size": 3, "use_canny": false, "lora_input": "", "lora_scale": "", "kernel_size": 3, "num_outputs": 1, "sketch_type": "HedPidNet", "suffix_prompt": "Futuristic Concept, Cutting-Edge Technology, Historical Landmark, Timeless Aesthetics, sharp focus, 8k, uhd, file grain, masterpiece", "guidance_scale": 7.5, "weight_primary": 0.7, "generate_square": false, "negative_prompt": "deformed, animation, anime, cartoon, comic, cropped, out of frame, low res, draft, cgi, low quality render, thumbnail", "weight_secondary": 0.6, "erosion_iterations": 2, "dilation_iterations": 1, "num_inference_steps": 35, "adapter_conditioning_scale": 0.9 }
Install Replicate’s Node.js client library:npm install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run qr2ai/outline using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "qr2ai/outline:6f713aeb58eb5034ad353de02d7dd56c9efa79f2214e6b89a790dad8ca67ef49", { input: { seed: 0, image: "https://replicate.delivery/pbxt/Lcg9dtkX66pSWfULefLA7UMExDQoonK9lmdA9y1R6kbEF9Q6/outline.png", width: 1024, height: 1024, prompt: "Modern skyscraper, glass facade, urban skyline, clear day.", sampler: "Euler a", blur_size: 3, use_canny: false, lora_input: "", lora_scale: "", kernel_size: 3, num_outputs: 1, sketch_type: "HedPidNet", suffix_prompt: "Futuristic Concept, Cutting-Edge Technology, Historical Landmark, Timeless Aesthetics, sharp focus, 8k, uhd, file grain, masterpiece", guidance_scale: 7.5, weight_primary: 0.7, generate_square: false, negative_prompt: "deformed, animation, anime, cartoon, comic, cropped, out of frame, low res, draft, cgi, low quality render, thumbnail", weight_secondary: 0.6, erosion_iterations: 2, dilation_iterations: 1, num_inference_steps: 35, adapter_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 replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the client:import replicate
Run qr2ai/outline using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "qr2ai/outline:6f713aeb58eb5034ad353de02d7dd56c9efa79f2214e6b89a790dad8ca67ef49", input={ "seed": 0, "image": "https://replicate.delivery/pbxt/Lcg9dtkX66pSWfULefLA7UMExDQoonK9lmdA9y1R6kbEF9Q6/outline.png", "width": 1024, "height": 1024, "prompt": "Modern skyscraper, glass facade, urban skyline, clear day.", "sampler": "Euler a", "blur_size": 3, "use_canny": False, "lora_input": "", "lora_scale": "", "kernel_size": 3, "num_outputs": 1, "sketch_type": "HedPidNet", "suffix_prompt": "Futuristic Concept, Cutting-Edge Technology, Historical Landmark, Timeless Aesthetics, sharp focus, 8k, uhd, file grain, masterpiece", "guidance_scale": 7.5, "weight_primary": 0.7, "generate_square": False, "negative_prompt": "deformed, animation, anime, cartoon, comic, cropped, out of frame, low res, draft, cgi, low quality render, thumbnail", "weight_secondary": 0.6, "erosion_iterations": 2, "dilation_iterations": 1, "num_inference_steps": 35, "adapter_conditioning_scale": 0.9 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run qr2ai/outline 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": "6f713aeb58eb5034ad353de02d7dd56c9efa79f2214e6b89a790dad8ca67ef49", "input": { "seed": 0, "image": "https://replicate.delivery/pbxt/Lcg9dtkX66pSWfULefLA7UMExDQoonK9lmdA9y1R6kbEF9Q6/outline.png", "width": 1024, "height": 1024, "prompt": "Modern skyscraper, glass facade, urban skyline, clear day.", "sampler": "Euler a", "blur_size": 3, "use_canny": false, "lora_input": "", "lora_scale": "", "kernel_size": 3, "num_outputs": 1, "sketch_type": "HedPidNet", "suffix_prompt": "Futuristic Concept, Cutting-Edge Technology, Historical Landmark, Timeless Aesthetics, sharp focus, 8k, uhd, file grain, masterpiece", "guidance_scale": 7.5, "weight_primary": 0.7, "generate_square": false, "negative_prompt": "deformed, animation, anime, cartoon, comic, cropped, out of frame, low res, draft, cgi, low quality render, thumbnail", "weight_secondary": 0.6, "erosion_iterations": 2, "dilation_iterations": 1, "num_inference_steps": 35, "adapter_conditioning_scale": 0.9 } }' \ https://api.replicate.com/v1/predictions
To 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 cog
If 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/qr2ai/outline@sha256:6f713aeb58eb5034ad353de02d7dd56c9efa79f2214e6b89a790dad8ca67ef49 \ -i 'seed=0' \ -i 'image="https://replicate.delivery/pbxt/Lcg9dtkX66pSWfULefLA7UMExDQoonK9lmdA9y1R6kbEF9Q6/outline.png"' \ -i 'width=1024' \ -i 'height=1024' \ -i 'prompt="Modern skyscraper, glass facade, urban skyline, clear day."' \ -i 'sampler="Euler a"' \ -i 'blur_size=3' \ -i 'use_canny=false' \ -i 'lora_input=""' \ -i 'lora_scale=""' \ -i 'kernel_size=3' \ -i 'num_outputs=1' \ -i 'sketch_type="HedPidNet"' \ -i 'suffix_prompt="Futuristic Concept, Cutting-Edge Technology, Historical Landmark, Timeless Aesthetics, sharp focus, 8k, uhd, file grain, masterpiece"' \ -i 'guidance_scale=7.5' \ -i 'weight_primary=0.7' \ -i 'generate_square=false' \ -i 'negative_prompt="deformed, animation, anime, cartoon, comic, cropped, out of frame, low res, draft, cgi, low quality render, thumbnail"' \ -i 'weight_secondary=0.6' \ -i 'erosion_iterations=2' \ -i 'dilation_iterations=1' \ -i 'num_inference_steps=35' \ -i 'adapter_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/qr2ai/outline@sha256:6f713aeb58eb5034ad353de02d7dd56c9efa79f2214e6b89a790dad8ca67ef49
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "seed": 0, "image": "https://replicate.delivery/pbxt/Lcg9dtkX66pSWfULefLA7UMExDQoonK9lmdA9y1R6kbEF9Q6/outline.png", "width": 1024, "height": 1024, "prompt": "Modern skyscraper, glass facade, urban skyline, clear day.", "sampler": "Euler a", "blur_size": 3, "use_canny": false, "lora_input": "", "lora_scale": "", "kernel_size": 3, "num_outputs": 1, "sketch_type": "HedPidNet", "suffix_prompt": "Futuristic Concept, Cutting-Edge Technology, Historical Landmark, Timeless Aesthetics, sharp focus, 8k, uhd, file grain, masterpiece", "guidance_scale": 7.5, "weight_primary": 0.7, "generate_square": false, "negative_prompt": "deformed, animation, anime, cartoon, comic, cropped, out of frame, low res, draft, cgi, low quality render, thumbnail", "weight_secondary": 0.6, "erosion_iterations": 2, "dilation_iterations": 1, "num_inference_steps": 35, "adapter_conditioning_scale": 0.9 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-11-08T00:18:12.061381Z", "created_at": "2024-11-08T00:17:57.145000Z", "data_removed": false, "error": null, "id": "q5c36e43k5rj60ck14hatd9324", "input": { "seed": 0, "image": "https://replicate.delivery/pbxt/Lcg9dtkX66pSWfULefLA7UMExDQoonK9lmdA9y1R6kbEF9Q6/outline.png", "width": 1024, "height": 1024, "prompt": "Modern skyscraper, glass facade, urban skyline, clear day.", "sampler": "Euler a", "blur_size": 3, "use_canny": false, "lora_input": "", "lora_scale": "", "kernel_size": 3, "num_outputs": 1, "sketch_type": "HedPidNet", "suffix_prompt": "Futuristic Concept, Cutting-Edge Technology, Historical Landmark, Timeless Aesthetics, sharp focus, 8k, uhd, file grain, masterpiece", "guidance_scale": 7.5, "weight_primary": 0.7, "generate_square": false, "negative_prompt": "deformed, animation, anime, cartoon, comic, cropped, out of frame, low res, draft, cgi, low quality render, thumbnail", "weight_secondary": 0.6, "erosion_iterations": 2, "dilation_iterations": 1, "num_inference_steps": 35, "adapter_conditioning_scale": 0.9 }, "logs": "INFO:root:Image loaded successfully.\nINFO:root:HED sketch generated successfully.\nINFO:root:PidiNet sketch generated successfully.\nINFO:root:Combined HED and PidiNet sketches with weights 0.5384615384615385/0.46153846153846156.\nINFO:root:Random seed generated: 707529904\n 0%| | 0/35 [00:00<?, ?it/s]\n 3%|▎ | 1/35 [00:00<00:05, 5.67it/s]\n 6%|▌ | 2/35 [00:00<00:04, 7.09it/s]\n 9%|▊ | 3/35 [00:00<00:04, 7.71it/s]\n 11%|█▏ | 4/35 [00:00<00:03, 8.05it/s]\n 14%|█▍ | 5/35 [00:00<00:03, 8.25it/s]\n 17%|█▋ | 6/35 [00:00<00:03, 8.38it/s]\n 20%|██ | 7/35 [00:00<00:03, 8.46it/s]\n 23%|██▎ | 8/35 [00:00<00:03, 8.50it/s]\n 26%|██▌ | 9/35 [00:01<00:03, 8.52it/s]\n 29%|██▊ | 10/35 [00:01<00:02, 8.56it/s]\n 31%|███▏ | 11/35 [00:01<00:02, 8.58it/s]\n 34%|███▍ | 12/35 [00:01<00:02, 8.60it/s]\n 37%|███▋ | 13/35 [00:01<00:02, 8.61it/s]\n 40%|████ | 14/35 [00:01<00:02, 8.62it/s]\n 43%|████▎ | 15/35 [00:01<00:02, 8.62it/s]\n 46%|████▌ | 16/35 [00:01<00:02, 8.63it/s]\n 49%|████▊ | 17/35 [00:02<00:02, 8.63it/s]\n 51%|█████▏ | 18/35 [00:02<00:01, 8.63it/s]\n 54%|█████▍ | 19/35 [00:02<00:01, 8.63it/s]\n 57%|█████▋ | 20/35 [00:02<00:01, 8.63it/s]\n 60%|██████ | 21/35 [00:02<00:01, 8.63it/s]\n 63%|██████▎ | 22/35 [00:02<00:01, 8.64it/s]\n 66%|██████▌ | 23/35 [00:02<00:01, 8.64it/s]\n 69%|██████▊ | 24/35 [00:02<00:01, 8.64it/s]\n 71%|███████▏ | 25/35 [00:02<00:01, 8.64it/s]\n 74%|███████▍ | 26/35 [00:03<00:01, 8.64it/s]\n 77%|███████▋ | 27/35 [00:03<00:00, 8.64it/s]\n 80%|████████ | 28/35 [00:03<00:00, 8.64it/s]\n 83%|████████▎ | 29/35 [00:03<00:00, 8.63it/s]\n 86%|████████▌ | 30/35 [00:03<00:00, 8.63it/s]\n 89%|████████▊ | 31/35 [00:03<00:00, 8.64it/s]\n 91%|█████████▏| 32/35 [00:03<00:00, 8.64it/s]\n 94%|█████████▍| 33/35 [00:03<00:00, 8.54it/s]\n 97%|█████████▋| 34/35 [00:04<00:00, 8.57it/s]\n100%|██████████| 35/35 [00:04<00:00, 8.59it/s]\n100%|██████████| 35/35 [00:04<00:00, 8.49it/s]\nINFO:root:Image generation completed successfully.", "metrics": { "predict_time": 9.275241489999999, "total_time": 14.916381 }, "output": [ "https://replicate.delivery/yhqm/bUwt9mqcX9ZENB2KyEUWxGqEm2HCKNtReiC7tqjTcUeErwuTA/output_0.png" ], "started_at": "2024-11-08T00:18:02.786140Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/qoxq-46kfyl4iue3l43swtbhbyrmlfblbz235obwiy7tfhfwc3tuwbkwq", "get": "https://api.replicate.com/v1/predictions/q5c36e43k5rj60ck14hatd9324", "cancel": "https://api.replicate.com/v1/predictions/q5c36e43k5rj60ck14hatd9324/cancel" }, "version": "6f713aeb58eb5034ad353de02d7dd56c9efa79f2214e6b89a790dad8ca67ef49" }
Generated inINFO:root:Image loaded successfully. INFO:root:HED sketch generated successfully. INFO:root:PidiNet sketch generated successfully. INFO:root:Combined HED and PidiNet sketches with weights 0.5384615384615385/0.46153846153846156. INFO:root:Random seed generated: 707529904 0%| | 0/35 [00:00<?, ?it/s] 3%|▎ | 1/35 [00:00<00:05, 5.67it/s] 6%|▌ | 2/35 [00:00<00:04, 7.09it/s] 9%|▊ | 3/35 [00:00<00:04, 7.71it/s] 11%|█▏ | 4/35 [00:00<00:03, 8.05it/s] 14%|█▍ | 5/35 [00:00<00:03, 8.25it/s] 17%|█▋ | 6/35 [00:00<00:03, 8.38it/s] 20%|██ | 7/35 [00:00<00:03, 8.46it/s] 23%|██▎ | 8/35 [00:00<00:03, 8.50it/s] 26%|██▌ | 9/35 [00:01<00:03, 8.52it/s] 29%|██▊ | 10/35 [00:01<00:02, 8.56it/s] 31%|███▏ | 11/35 [00:01<00:02, 8.58it/s] 34%|███▍ | 12/35 [00:01<00:02, 8.60it/s] 37%|███▋ | 13/35 [00:01<00:02, 8.61it/s] 40%|████ | 14/35 [00:01<00:02, 8.62it/s] 43%|████▎ | 15/35 [00:01<00:02, 8.62it/s] 46%|████▌ | 16/35 [00:01<00:02, 8.63it/s] 49%|████▊ | 17/35 [00:02<00:02, 8.63it/s] 51%|█████▏ | 18/35 [00:02<00:01, 8.63it/s] 54%|█████▍ | 19/35 [00:02<00:01, 8.63it/s] 57%|█████▋ | 20/35 [00:02<00:01, 8.63it/s] 60%|██████ | 21/35 [00:02<00:01, 8.63it/s] 63%|██████▎ | 22/35 [00:02<00:01, 8.64it/s] 66%|██████▌ | 23/35 [00:02<00:01, 8.64it/s] 69%|██████▊ | 24/35 [00:02<00:01, 8.64it/s] 71%|███████▏ | 25/35 [00:02<00:01, 8.64it/s] 74%|███████▍ | 26/35 [00:03<00:01, 8.64it/s] 77%|███████▋ | 27/35 [00:03<00:00, 8.64it/s] 80%|████████ | 28/35 [00:03<00:00, 8.64it/s] 83%|████████▎ | 29/35 [00:03<00:00, 8.63it/s] 86%|████████▌ | 30/35 [00:03<00:00, 8.63it/s] 89%|████████▊ | 31/35 [00:03<00:00, 8.64it/s] 91%|█████████▏| 32/35 [00:03<00:00, 8.64it/s] 94%|█████████▍| 33/35 [00:03<00:00, 8.54it/s] 97%|█████████▋| 34/35 [00:04<00:00, 8.57it/s] 100%|██████████| 35/35 [00:04<00:00, 8.59it/s] 100%|██████████| 35/35 [00:04<00:00, 8.49it/s] INFO:root:Image generation completed successfully.
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