jschoormans / interior-v2
Remodels interior (Updated 5 months, 3 weeks ago)
- Public
- 2.4K runs
Prediction
jschoormans/interior-v2:db5c430268e1bb117f2f0547decafeed3252868cf051ab28f5e1e317b645d743IDm14db5wjrdrgm0cjv3jrvhvx24StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- image
- prompt
- Living room, scandinavian interior, photograph, clean, beautiful, high quality, 8k
- strength
- 0.999999
- guidance_scale
- 7
- max_resolution
- 1051
- negative_prompt
- (worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth
- mask_prompt_window
- window, doorway
- mask_prompt_ceiling
- ceiling
- num_inference_steps
- 30
- control_guidance_end
- 0.8
- mask_prompt_furniture
- furniture, couch, table, chair, desk, bed, sofa, cupboard, shelf, cabinet, bookcase, dresser, nightstand, armchair, decoration, plant, flower, pillow, lamp, TV
- control_guidance_start
- 0
- keep_furniture_structure
- controlnet_conditioning_scale
- 0.03
{ "image": "https://replicate.delivery/pbxt/LscMB7dbg6KGk8OI5HbaPFLUukh15hFww9X9S5W5NF4u7OUm/149_1440.jpg", "prompt": "Living room, scandinavian interior, photograph, clean, beautiful, high quality, 8k", "strength": 0.999999, "guidance_scale": 7, "max_resolution": 1051, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "mask_prompt_window": "window, doorway", "mask_prompt_ceiling": "ceiling", "num_inference_steps": 30, "control_guidance_end": 0.8, "mask_prompt_furniture": "furniture, couch, table, chair, desk, bed, sofa, cupboard, shelf, cabinet, bookcase, dresser, nightstand, armchair, decoration, plant, flower, pillow, lamp, TV", "control_guidance_start": 0, "keep_furniture_structure": false, "controlnet_conditioning_scale": 0.03 }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 jschoormans/interior-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "jschoormans/interior-v2:db5c430268e1bb117f2f0547decafeed3252868cf051ab28f5e1e317b645d743", { input: { image: "https://replicate.delivery/pbxt/LscMB7dbg6KGk8OI5HbaPFLUukh15hFww9X9S5W5NF4u7OUm/149_1440.jpg", prompt: "Living room, scandinavian interior, photograph, clean, beautiful, high quality, 8k", strength: 0.999999, guidance_scale: 7, max_resolution: 1051, negative_prompt: "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", mask_prompt_window: "window, doorway", mask_prompt_ceiling: "ceiling", num_inference_steps: 30, control_guidance_end: 0.8, mask_prompt_furniture: "furniture, couch, table, chair, desk, bed, sofa, cupboard, shelf, cabinet, bookcase, dresser, nightstand, armchair, decoration, plant, flower, pillow, lamp, TV", control_guidance_start: 0, keep_furniture_structure: false, controlnet_conditioning_scale: 0.03 } } ); // 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 jschoormans/interior-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "jschoormans/interior-v2:db5c430268e1bb117f2f0547decafeed3252868cf051ab28f5e1e317b645d743", input={ "image": "https://replicate.delivery/pbxt/LscMB7dbg6KGk8OI5HbaPFLUukh15hFww9X9S5W5NF4u7OUm/149_1440.jpg", "prompt": "Living room, scandinavian interior, photograph, clean, beautiful, high quality, 8k", "strength": 0.999999, "guidance_scale": 7, "max_resolution": 1051, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "mask_prompt_window": "window, doorway", "mask_prompt_ceiling": "ceiling", "num_inference_steps": 30, "control_guidance_end": 0.8, "mask_prompt_furniture": "furniture, couch, table, chair, desk, bed, sofa, cupboard, shelf, cabinet, bookcase, dresser, nightstand, armchair, decoration, plant, flower, pillow, lamp, TV", "control_guidance_start": 0, "keep_furniture_structure": False, "controlnet_conditioning_scale": 0.03 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run jschoormans/interior-v2 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": "jschoormans/interior-v2:db5c430268e1bb117f2f0547decafeed3252868cf051ab28f5e1e317b645d743", "input": { "image": "https://replicate.delivery/pbxt/LscMB7dbg6KGk8OI5HbaPFLUukh15hFww9X9S5W5NF4u7OUm/149_1440.jpg", "prompt": "Living room, scandinavian interior, photograph, clean, beautiful, high quality, 8k", "strength": 0.999999, "guidance_scale": 7, "max_resolution": 1051, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "mask_prompt_window": "window, doorway", "mask_prompt_ceiling": "ceiling", "num_inference_steps": 30, "control_guidance_end": 0.8, "mask_prompt_furniture": "furniture, couch, table, chair, desk, bed, sofa, cupboard, shelf, cabinet, bookcase, dresser, nightstand, armchair, decoration, plant, flower, pillow, lamp, TV", "control_guidance_start": 0, "keep_furniture_structure": false, "controlnet_conditioning_scale": 0.03 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-29T15:31:46.193799Z", "created_at": "2024-10-29T15:29:36.963000Z", "data_removed": false, "error": null, "id": "m14db5wjrdrgm0cjv3jrvhvx24", "input": { "image": "https://replicate.delivery/pbxt/LscMB7dbg6KGk8OI5HbaPFLUukh15hFww9X9S5W5NF4u7OUm/149_1440.jpg", "prompt": "Living room, scandinavian interior, photograph, clean, beautiful, high quality, 8k", "strength": 0.999999, "guidance_scale": 7, "max_resolution": 1051, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "mask_prompt_window": "window, doorway", "mask_prompt_ceiling": "ceiling", "num_inference_steps": 30, "control_guidance_end": 0.8, "mask_prompt_furniture": "furniture, couch, table, chair, desk, bed, sofa, cupboard, shelf, cabinet, bookcase, dresser, nightstand, armchair, decoration, plant, flower, pillow, lamp, TV", "control_guidance_start": 0, "keep_furniture_structure": false, "controlnet_conditioning_scale": 0.03 }, "logs": "positive_prompt: window\nUserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.5 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.\nUserWarning: None of the inputs have requires_grad=True. Gradients will be None\npositive_prompt: doorway\nDone!\npositive_prompt: ceiling\nDone!\npositive_prompt: furniture\npositive_prompt: couch\npositive_prompt: table\npositive_prompt: chair\npositive_prompt: desk\npositive_prompt: bed\npositive_prompt: sofa\npositive_prompt: cupboard\npositive_prompt: shelf\npositive_prompt: cabinet\npositive_prompt: bookcase\npositive_prompt: dresser\npositive_prompt: nightstand\npositive_prompt: armchair\npositive_prompt: decoration\npositive_prompt: plant\npositive_prompt: flower\npositive_prompt: pillow\npositive_prompt: lamp\npositive_prompt: TV\nDone!\n`last_sigmas_type='zero'` is not supported for `lower_order_final=False`. Changing scheduler {self.config} to have `lower_order_final` set to True.\n 0%| | 0/29 [00:00<?, ?it/s]\n 3%|▎ | 1/29 [00:03<01:31, 3.27s/it]\n 7%|▋ | 2/29 [00:03<00:39, 1.48s/it]\n 10%|█ | 3/29 [00:03<00:24, 1.04it/s]\n 14%|█▍ | 4/29 [00:04<00:17, 1.40it/s]\n 17%|█▋ | 5/29 [00:04<00:13, 1.73it/s]\n 21%|██ | 6/29 [00:04<00:11, 2.02it/s]\n 24%|██▍ | 7/29 [00:05<00:09, 2.26it/s]\n 28%|██▊ | 8/29 [00:05<00:08, 2.44it/s]\n 31%|███ | 9/29 [00:05<00:07, 2.59it/s]\n 34%|███▍ | 10/29 [00:06<00:07, 2.70it/s]\n 38%|███▊ | 11/29 [00:06<00:06, 2.78it/s]\n 41%|████▏ | 12/29 [00:06<00:05, 2.84it/s]\n 45%|████▍ | 13/29 [00:07<00:05, 2.88it/s]\n 48%|████▊ | 14/29 [00:07<00:05, 2.91it/s]\n 52%|█████▏ | 15/29 [00:07<00:04, 2.93it/s]\n 55%|█████▌ | 16/29 [00:08<00:04, 2.94it/s]\n 59%|█████▊ | 17/29 [00:08<00:04, 2.95it/s]\n 62%|██████▏ | 18/29 [00:08<00:03, 2.96it/s]\n 66%|██████▌ | 19/29 [00:09<00:03, 2.96it/s]\n 69%|██████▉ | 20/29 [00:09<00:03, 2.96it/s]\n 72%|███████▏ | 21/29 [00:09<00:02, 2.96it/s]\n 76%|███████▌ | 22/29 [00:10<00:02, 2.97it/s]\n 79%|███████▉ | 23/29 [00:10<00:02, 2.96it/s]\n 83%|████████▎ | 24/29 [00:10<00:01, 2.96it/s]\n 86%|████████▌ | 25/29 [00:11<00:01, 2.96it/s]\n 90%|████████▉ | 26/29 [00:11<00:01, 2.96it/s]\n 93%|█████████▎| 27/29 [00:11<00:00, 2.96it/s]\n 97%|█████████▋| 28/29 [00:12<00:00, 2.96it/s]\n100%|██████████| 29/29 [00:12<00:00, 2.96it/s]\n100%|██████████| 29/29 [00:12<00:00, 2.30it/s]\nTime taken: 36.87832283973694 seconds", "metrics": { "predict_time": 40.255916079, "total_time": 129.230799 }, "output": [ "https://replicate.delivery/pbxt/Qy2teTcZNx2lESNXLJ7QGJeKwzdBXm2u0NW54wEb2J0fOWXnA/output.png", "https://replicate.delivery/pbxt/WYP8JcfoINRDGan2PxHECkZia3fX51LgzMKmbsrJPjNhHrrTA/control.png", "https://replicate.delivery/pbxt/icX4CIkNTo5JOtpzaYzfM6Qc4w29V36pTergijq53qbhHrrTA/inverted_mask_window.png", "https://replicate.delivery/pbxt/fQEbrbQm5L3gUqH9v6sPTSKeBem8LXoRsalv8u64rpICPWXnA/inverted_mask_ceiling.png", "https://replicate.delivery/pbxt/i6HXINgKqGIlHtFmf2OYe83ahNISNvhblReseJuHcSyEeYddC/mask_furniture.png" ], "started_at": "2024-10-29T15:31:05.937883Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/m14db5wjrdrgm0cjv3jrvhvx24", "cancel": "https://api.replicate.com/v1/predictions/m14db5wjrdrgm0cjv3jrvhvx24/cancel" }, "version": "db5c430268e1bb117f2f0547decafeed3252868cf051ab28f5e1e317b645d743" }Generated inpositive_prompt: window UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.5 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants. UserWarning: None of the inputs have requires_grad=True. Gradients will be None positive_prompt: doorway Done! positive_prompt: ceiling Done! positive_prompt: furniture positive_prompt: couch positive_prompt: table positive_prompt: chair positive_prompt: desk positive_prompt: bed positive_prompt: sofa positive_prompt: cupboard positive_prompt: shelf positive_prompt: cabinet positive_prompt: bookcase positive_prompt: dresser positive_prompt: nightstand positive_prompt: armchair positive_prompt: decoration positive_prompt: plant positive_prompt: flower positive_prompt: pillow positive_prompt: lamp positive_prompt: TV Done! `last_sigmas_type='zero'` is not supported for `lower_order_final=False`. Changing scheduler {self.config} to have `lower_order_final` set to True. 0%| | 0/29 [00:00<?, ?it/s] 3%|▎ | 1/29 [00:03<01:31, 3.27s/it] 7%|▋ | 2/29 [00:03<00:39, 1.48s/it] 10%|█ | 3/29 [00:03<00:24, 1.04it/s] 14%|█▍ | 4/29 [00:04<00:17, 1.40it/s] 17%|█▋ | 5/29 [00:04<00:13, 1.73it/s] 21%|██ | 6/29 [00:04<00:11, 2.02it/s] 24%|██▍ | 7/29 [00:05<00:09, 2.26it/s] 28%|██▊ | 8/29 [00:05<00:08, 2.44it/s] 31%|███ | 9/29 [00:05<00:07, 2.59it/s] 34%|███▍ | 10/29 [00:06<00:07, 2.70it/s] 38%|███▊ | 11/29 [00:06<00:06, 2.78it/s] 41%|████▏ | 12/29 [00:06<00:05, 2.84it/s] 45%|████▍ | 13/29 [00:07<00:05, 2.88it/s] 48%|████▊ | 14/29 [00:07<00:05, 2.91it/s] 52%|█████▏ | 15/29 [00:07<00:04, 2.93it/s] 55%|█████▌ | 16/29 [00:08<00:04, 2.94it/s] 59%|█████▊ | 17/29 [00:08<00:04, 2.95it/s] 62%|██████▏ | 18/29 [00:08<00:03, 2.96it/s] 66%|██████▌ | 19/29 [00:09<00:03, 2.96it/s] 69%|██████▉ | 20/29 [00:09<00:03, 2.96it/s] 72%|███████▏ | 21/29 [00:09<00:02, 2.96it/s] 76%|███████▌ | 22/29 [00:10<00:02, 2.97it/s] 79%|███████▉ | 23/29 [00:10<00:02, 2.96it/s] 83%|████████▎ | 24/29 [00:10<00:01, 2.96it/s] 86%|████████▌ | 25/29 [00:11<00:01, 2.96it/s] 90%|████████▉ | 26/29 [00:11<00:01, 2.96it/s] 93%|█████████▎| 27/29 [00:11<00:00, 2.96it/s] 97%|█████████▋| 28/29 [00:12<00:00, 2.96it/s] 100%|██████████| 29/29 [00:12<00:00, 2.96it/s] 100%|██████████| 29/29 [00:12<00:00, 2.30it/s] Time taken: 36.87832283973694 seconds
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