arielreplicate / robust_video_matting
extract foreground of a video
Prediction
arielreplicate/robust_video_matting:2d2de06a76a837a4ba92b6164bf8bfd3ddb524a1fb64b0d8ae055af17fa22503IDiqaowdlwcnbxresiand63tzn5aStatusSucceededSourceWebHardware–Total durationCreatedInput
- input_video
- output_type
- green-screen
{ "input_video": "https://replicate.delivery/pbxt/HqiGGuuwynO7sCHpcQdYQsIf04NotwOrDdbhBf4M6Pou6MGg/butter.mp4", "output_type": "green-screen" }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 arielreplicate/robust_video_matting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "arielreplicate/robust_video_matting:2d2de06a76a837a4ba92b6164bf8bfd3ddb524a1fb64b0d8ae055af17fa22503", { input: { input_video: "https://replicate.delivery/pbxt/HqiGGuuwynO7sCHpcQdYQsIf04NotwOrDdbhBf4M6Pou6MGg/butter.mp4", output_type: "green-screen" } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);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 arielreplicate/robust_video_matting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "arielreplicate/robust_video_matting:2d2de06a76a837a4ba92b6164bf8bfd3ddb524a1fb64b0d8ae055af17fa22503", input={ "input_video": "https://replicate.delivery/pbxt/HqiGGuuwynO7sCHpcQdYQsIf04NotwOrDdbhBf4M6Pou6MGg/butter.mp4", "output_type": "green-screen" } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())To learn more, take a look at the guide on getting started with Python.
Run arielreplicate/robust_video_matting 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": "arielreplicate/robust_video_matting:2d2de06a76a837a4ba92b6164bf8bfd3ddb524a1fb64b0d8ae055af17fa22503", "input": { "input_video": "https://replicate.delivery/pbxt/HqiGGuuwynO7sCHpcQdYQsIf04NotwOrDdbhBf4M6Pou6MGg/butter.mp4", "output_type": "green-screen" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-11-25T14:17:06.618254Z", "created_at": "2022-11-25T14:11:53.705436Z", "data_removed": false, "error": null, "id": "iqaowdlwcnbxresiand63tzn5a", "input": { "input_video": "https://replicate.delivery/pbxt/HqiGGuuwynO7sCHpcQdYQsIf04NotwOrDdbhBf4M6Pou6MGg/butter.mp4", "output_type": "green-screen" }, "logs": "0%| | 0/382 [00:00<?, ?it/s]/root/.pyenv/versions/3.8.15/lib/python3.8/site-packages/torch/nn/functional.py:718: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at /pytorch/c10/core/TensorImpl.h:1156.)\nreturn torch.max_pool2d(input, kernel_size, stride, padding, dilation, ceil_mode)\n 3%|▎ | 12/382 [00:02<01:25, 4.30it/s]\n 6%|▋ | 24/382 [00:04<01:10, 5.05it/s]\n 9%|▉ | 36/382 [00:07<01:05, 5.29it/s]\n 13%|█▎ | 48/382 [00:10<01:19, 4.19it/s]\n 16%|█▌ | 60/382 [00:14<01:22, 3.92it/s]\n 19%|█▉ | 72/382 [00:17<01:22, 3.74it/s]\n 22%|██▏ | 84/382 [00:20<01:16, 3.88it/s]\n 25%|██▌ | 96/382 [00:23<01:12, 3.96it/s]\n 28%|██▊ | 108/382 [00:26<01:06, 4.10it/s]\n 31%|███▏ | 120/382 [00:28<01:03, 4.13it/s]\n 35%|███▍ | 132/382 [00:31<00:59, 4.23it/s]\n 38%|███▊ | 144/382 [00:34<00:57, 4.12it/s]\n 41%|████ | 156/382 [00:37<00:55, 4.07it/s]\n 44%|████▍ | 168/382 [00:40<00:53, 4.04it/s]\n 47%|████▋ | 180/382 [00:43<00:49, 4.07it/s]\n 50%|█████ | 192/382 [00:46<00:46, 4.11it/s]\n 53%|█████▎ | 204/382 [00:49<00:42, 4.16it/s]\n 57%|█████▋ | 216/382 [00:52<00:40, 4.05it/s]\n 60%|█████▉ | 228/382 [00:55<00:38, 4.05it/s]\n 63%|██████▎ | 240/382 [00:58<00:35, 4.02it/s]\n 66%|██████▌ | 252/382 [01:01<00:31, 4.11it/s]\n 69%|██████▉ | 264/382 [01:04<00:28, 4.17it/s]\n 72%|███████▏ | 276/382 [01:06<00:24, 4.28it/s]\n 75%|███████▌ | 288/382 [01:09<00:22, 4.22it/s]\n 79%|███████▊ | 300/382 [01:12<00:19, 4.23it/s]\n 82%|████████▏ | 312/382 [01:15<00:16, 4.26it/s]\n 85%|████████▍ | 324/382 [01:17<00:13, 4.28it/s]\n 88%|████████▊ | 336/382 [01:20<00:10, 4.24it/s]\n 91%|█████████ | 348/382 [01:23<00:07, 4.25it/s]\n 94%|█████████▍| 360/382 [01:26<00:05, 4.20it/s]\n 97%|█████████▋| 372/382 [01:29<00:02, 4.20it/s]\n100%|██████████| 382/382 [01:31<00:00, 4.20it/s]", "metrics": { "predict_time": 97.211127, "total_time": 312.912818 }, "output": "https://replicate.delivery/pbxt/V3iFlL5JotpbLtkUqGcnrpsiRfXume3Jm0020Iu0hX0hBoDQA/green-screen.mp4", "started_at": "2022-11-25T14:15:29.407127Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/iqaowdlwcnbxresiand63tzn5a", "cancel": "https://api.replicate.com/v1/predictions/iqaowdlwcnbxresiand63tzn5a/cancel" }, "version": "2d2de06a76a837a4ba92b6164bf8bfd3ddb524a1fb64b0d8ae055af17fa22503" }Generated in0%| | 0/382 [00:00<?, ?it/s]/root/.pyenv/versions/3.8.15/lib/python3.8/site-packages/torch/nn/functional.py:718: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at /pytorch/c10/core/TensorImpl.h:1156.) return torch.max_pool2d(input, kernel_size, stride, padding, dilation, ceil_mode) 3%|▎ | 12/382 [00:02<01:25, 4.30it/s] 6%|▋ | 24/382 [00:04<01:10, 5.05it/s] 9%|▉ | 36/382 [00:07<01:05, 5.29it/s] 13%|█▎ | 48/382 [00:10<01:19, 4.19it/s] 16%|█▌ | 60/382 [00:14<01:22, 3.92it/s] 19%|█▉ | 72/382 [00:17<01:22, 3.74it/s] 22%|██▏ | 84/382 [00:20<01:16, 3.88it/s] 25%|██▌ | 96/382 [00:23<01:12, 3.96it/s] 28%|██▊ | 108/382 [00:26<01:06, 4.10it/s] 31%|███▏ | 120/382 [00:28<01:03, 4.13it/s] 35%|███▍ | 132/382 [00:31<00:59, 4.23it/s] 38%|███▊ | 144/382 [00:34<00:57, 4.12it/s] 41%|████ | 156/382 [00:37<00:55, 4.07it/s] 44%|████▍ | 168/382 [00:40<00:53, 4.04it/s] 47%|████▋ | 180/382 [00:43<00:49, 4.07it/s] 50%|█████ | 192/382 [00:46<00:46, 4.11it/s] 53%|█████▎ | 204/382 [00:49<00:42, 4.16it/s] 57%|█████▋ | 216/382 [00:52<00:40, 4.05it/s] 60%|█████▉ | 228/382 [00:55<00:38, 4.05it/s] 63%|██████▎ | 240/382 [00:58<00:35, 4.02it/s] 66%|██████▌ | 252/382 [01:01<00:31, 4.11it/s] 69%|██████▉ | 264/382 [01:04<00:28, 4.17it/s] 72%|███████▏ | 276/382 [01:06<00:24, 4.28it/s] 75%|███████▌ | 288/382 [01:09<00:22, 4.22it/s] 79%|███████▊ | 300/382 [01:12<00:19, 4.23it/s] 82%|████████▏ | 312/382 [01:15<00:16, 4.26it/s] 85%|████████▍ | 324/382 [01:17<00:13, 4.28it/s] 88%|████████▊ | 336/382 [01:20<00:10, 4.24it/s] 91%|█████████ | 348/382 [01:23<00:07, 4.25it/s] 94%|█████████▍| 360/382 [01:26<00:05, 4.20it/s] 97%|█████████▋| 372/382 [01:29<00:02, 4.20it/s] 100%|██████████| 382/382 [01:31<00:00, 4.20it/s]Prediction
arielreplicate/robust_video_matting:2d2de06a76a837a4ba92b6164bf8bfd3ddb524a1fb64b0d8ae055af17fa22503IDc4zkevc27fhntpw3ekgb2ok2sqStatusSucceededSourceWebHardware–Total durationCreatedInput
- input_video
- output_type
- green-screen
{ "input_video": "https://replicate.delivery/pbxt/HqiUPeOL0NMmX1yzan5USbiFloRmxVcrKqBuslIlNdofpYAr/dance2.mp4", "output_type": "green-screen" }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 arielreplicate/robust_video_matting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "arielreplicate/robust_video_matting:2d2de06a76a837a4ba92b6164bf8bfd3ddb524a1fb64b0d8ae055af17fa22503", { input: { input_video: "https://replicate.delivery/pbxt/HqiUPeOL0NMmX1yzan5USbiFloRmxVcrKqBuslIlNdofpYAr/dance2.mp4", output_type: "green-screen" } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);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 arielreplicate/robust_video_matting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "arielreplicate/robust_video_matting:2d2de06a76a837a4ba92b6164bf8bfd3ddb524a1fb64b0d8ae055af17fa22503", input={ "input_video": "https://replicate.delivery/pbxt/HqiUPeOL0NMmX1yzan5USbiFloRmxVcrKqBuslIlNdofpYAr/dance2.mp4", "output_type": "green-screen" } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())To learn more, take a look at the guide on getting started with Python.
Run arielreplicate/robust_video_matting 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": "arielreplicate/robust_video_matting:2d2de06a76a837a4ba92b6164bf8bfd3ddb524a1fb64b0d8ae055af17fa22503", "input": { "input_video": "https://replicate.delivery/pbxt/HqiUPeOL0NMmX1yzan5USbiFloRmxVcrKqBuslIlNdofpYAr/dance2.mp4", "output_type": "green-screen" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-11-25T14:29:11.572602Z", "created_at": "2022-11-25T14:26:35.172178Z", "data_removed": false, "error": null, "id": "c4zkevc27fhntpw3ekgb2ok2sq", "input": { "input_video": "https://replicate.delivery/pbxt/HqiUPeOL0NMmX1yzan5USbiFloRmxVcrKqBuslIlNdofpYAr/dance2.mp4", "output_type": "green-screen" }, "logs": "0%| | 0/606 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n 2%|▏ | 12/606 [00:02<01:56, 5.08it/s]\u001b[A\u001b[A\u001b[A\n 4%|▍ | 24/606 [00:04<01:48, 5.37it/s]\u001b[A\u001b[A\u001b[A\n 6%|▌ | 36/606 [00:06<01:46, 5.37it/s]\u001b[A\u001b[A\u001b[A\n 8%|▊ | 48/606 [00:10<02:06, 4.40it/s]\u001b[A\u001b[A\u001b[A\n 10%|▉ | 60/606 [00:13<02:11, 4.14it/s]\u001b[A\u001b[A\u001b[A\n 12%|█▏ | 72/606 [00:16<02:10, 4.09it/s]\u001b[A\u001b[A\u001b[A\n 14%|█▍ | 84/606 [00:19<02:07, 4.08it/s]\u001b[A\u001b[A\u001b[A\n 16%|█▌ | 96/606 [00:22<02:04, 4.09it/s]\u001b[A\u001b[A\u001b[A\n 18%|█▊ | 108/606 [00:25<02:02, 4.05it/s]\u001b[A\u001b[A\u001b[A\n 20%|█▉ | 120/606 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3.89it/s]\u001b[A\u001b[A\u001b[A", "metrics": { "predict_time": 156.3639, "total_time": 156.400424 }, "output": "https://replicate.delivery/pbxt/HuwFjWn7A9bcH5CfhQ7KO79N3z4uZf9sTtLoo4PDnXY2MoDQA/green-screen.mp4", "started_at": "2022-11-25T14:26:35.208702Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/c4zkevc27fhntpw3ekgb2ok2sq", "cancel": "https://api.replicate.com/v1/predictions/c4zkevc27fhntpw3ekgb2ok2sq/cancel" }, "version": "2d2de06a76a837a4ba92b6164bf8bfd3ddb524a1fb64b0d8ae055af17fa22503" }Generated in0%| | 0/606 [00:00<?, ?it/s] 2%|▏ | 12/606 [00:02<01:56, 5.08it/s] 4%|▍ | 24/606 [00:04<01:48, 5.37it/s] 6%|▌ | 36/606 [00:06<01:46, 5.37it/s] 8%|▊ | 48/606 [00:10<02:06, 4.40it/s] 10%|▉ | 60/606 [00:13<02:11, 4.14it/s] 12%|█▏ | 72/606 [00:16<02:10, 4.09it/s] 14%|█▍ | 84/606 [00:19<02:07, 4.08it/s] 16%|█▌ | 96/606 [00:22<02:04, 4.09it/s] 18%|█▊ | 108/606 [00:25<02:02, 4.05it/s] 20%|█▉ | 120/606 [00:28<01:59, 4.07it/s] 22%|██▏ | 132/606 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arielreplicate/robust_video_matting:2d2de06a76a837a4ba92b6164bf8bfd3ddb524a1fb64b0d8ae055af17fa22503IDin5yh3obxrdmvgr6mxgalzzeliStatusSucceededSourceWebHardware–Total durationCreatedInput
- input_video
- output_type
- green-screen
{ "input_video": "https://replicate.delivery/pbxt/HqiZLXVlQCsU4hjSm3LcccJElHRir2ubhSkaGuQAS33P4FP3/bilibili.mp4", "output_type": "green-screen" }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 arielreplicate/robust_video_matting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "arielreplicate/robust_video_matting:2d2de06a76a837a4ba92b6164bf8bfd3ddb524a1fb64b0d8ae055af17fa22503", { input: { input_video: "https://replicate.delivery/pbxt/HqiZLXVlQCsU4hjSm3LcccJElHRir2ubhSkaGuQAS33P4FP3/bilibili.mp4", output_type: "green-screen" } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);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 arielreplicate/robust_video_matting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "arielreplicate/robust_video_matting:2d2de06a76a837a4ba92b6164bf8bfd3ddb524a1fb64b0d8ae055af17fa22503", input={ "input_video": "https://replicate.delivery/pbxt/HqiZLXVlQCsU4hjSm3LcccJElHRir2ubhSkaGuQAS33P4FP3/bilibili.mp4", "output_type": "green-screen" } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())To learn more, take a look at the guide on getting started with Python.
Run arielreplicate/robust_video_matting 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": "arielreplicate/robust_video_matting:2d2de06a76a837a4ba92b6164bf8bfd3ddb524a1fb64b0d8ae055af17fa22503", "input": { "input_video": "https://replicate.delivery/pbxt/HqiZLXVlQCsU4hjSm3LcccJElHRir2ubhSkaGuQAS33P4FP3/bilibili.mp4", "output_type": "green-screen" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-11-25T14:38:16.808827Z", "created_at": "2022-11-25T14:32:15.592259Z", "data_removed": false, "error": null, "id": "in5yh3obxrdmvgr6mxgalzzeli", "input": { "input_video": "https://replicate.delivery/pbxt/HqiZLXVlQCsU4hjSm3LcccJElHRir2ubhSkaGuQAS33P4FP3/bilibili.mp4", "output_type": "green-screen" }, "logs": "0%| | 0/1371 [00:00<?, ?it/s]/root/.pyenv/versions/3.8.15/lib/python3.8/site-packages/torch/nn/functional.py:718: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at /pytorch/c10/core/TensorImpl.h:1156.)\nreturn torch.max_pool2d(input, kernel_size, stride, padding, dilation, ceil_mode)\n 1%| | 12/1371 [00:03<06:04, 3.73it/s]\n 2%|▏ | 24/1371 [00:05<05:13, 4.30it/s]\n 3%|▎ | 36/1371 [00:08<05:11, 4.28it/s]\n 4%|▎ | 48/1371 [00:12<05:39, 3.89it/s]\n 4%|▍ | 60/1371 [00:15<05:41, 3.84it/s]\n 5%|▌ | 72/1371 [00:18<05:36, 3.86it/s]\n 6%|▌ | 84/1371 [00:21<05:28, 3.91it/s]\n 7%|▋ | 96/1371 [00:24<05:22, 3.95it/s]\n 8%|▊ | 108/1371 [00:27<05:17, 3.98it/s]\n 9%|▉ | 120/1371 [00:30<05:10, 4.03it/s]\n 10%|▉ | 132/1371 [00:33<05:07, 4.03it/s]\n 11%|█ | 144/1371 [00:36<05:05, 4.02it/s]\n 11%|█▏ | 156/1371 [00:39<05:03, 4.01it/s]\n 12%|█▏ | 168/1371 [00:42<05:01, 4.00it/s]\n 13%|█▎ | 180/1371 [00:45<04:57, 4.00it/s]\n 14%|█▍ | 192/1371 [00:48<04:55, 3.98it/s]\n 15%|█▍ | 204/1371 [00:51<05:06, 3.81it/s]\n 16%|█▌ | 216/1371 [00:54<05:03, 3.80it/s]\n 17%|█▋ | 228/1371 [00:57<04:58, 3.82it/s]\n 18%|█▊ | 240/1371 [01:00<04:53, 3.85it/s]\n 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3.74it/s]\n 91%|█████████ | 1248/1371 [05:25<00:32, 3.80it/s]\n 92%|█████████▏| 1260/1371 [05:28<00:28, 3.84it/s]\n 93%|█████████▎| 1272/1371 [05:31<00:25, 3.88it/s]\n 94%|█████████▎| 1284/1371 [05:34<00:22, 3.89it/s]\n 95%|█████████▍| 1296/1371 [05:37<00:19, 3.89it/s]\n 95%|█████████▌| 1308/1371 [05:40<00:16, 3.87it/s]\n 96%|█████████▋| 1320/1371 [05:43<00:13, 3.88it/s]\n 97%|█████████▋| 1332/1371 [05:47<00:10, 3.86it/s]\n 98%|█████████▊| 1344/1371 [05:50<00:07, 3.85it/s]\n 99%|█████████▉| 1356/1371 [05:53<00:03, 3.86it/s]\n100%|█████████▉| 1368/1371 [05:56<00:00, 3.89it/s]\n100%|██████████| 1371/1371 [05:57<00:00, 3.88it/s]", "metrics": { "predict_time": 361.181149, "total_time": 361.216568 }, "output": "https://replicate.delivery/pbxt/rERlJsBX0oJ4BZwnJdaj2RfqBYDuzjObx3jRDg3GffHvqQHgA/green-screen.mp4", "started_at": "2022-11-25T14:32:15.627678Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/in5yh3obxrdmvgr6mxgalzzeli", "cancel": "https://api.replicate.com/v1/predictions/in5yh3obxrdmvgr6mxgalzzeli/cancel" }, "version": "2d2de06a76a837a4ba92b6164bf8bfd3ddb524a1fb64b0d8ae055af17fa22503" }Generated in0%| | 0/1371 [00:00<?, ?it/s]/root/.pyenv/versions/3.8.15/lib/python3.8/site-packages/torch/nn/functional.py:718: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at /pytorch/c10/core/TensorImpl.h:1156.) return torch.max_pool2d(input, kernel_size, stride, padding, dilation, ceil_mode) 1%| | 12/1371 [00:03<06:04, 3.73it/s] 2%|▏ | 24/1371 [00:05<05:13, 4.30it/s] 3%|▎ | 36/1371 [00:08<05:11, 4.28it/s] 4%|▎ | 48/1371 [00:12<05:39, 3.89it/s] 4%|▍ | 60/1371 [00:15<05:41, 3.84it/s] 5%|▌ | 72/1371 [00:18<05:36, 3.86it/s] 6%|▌ | 84/1371 [00:21<05:28, 3.91it/s] 7%|▋ | 96/1371 [00:24<05:22, 3.95it/s] 8%|▊ | 108/1371 [00:27<05:17, 3.98it/s] 9%|▉ | 120/1371 [00:30<05:10, 4.03it/s] 10%|▉ | 132/1371 [00:33<05:07, 4.03it/s] 11%|█ | 144/1371 [00:36<05:05, 4.02it/s] 11%|█▏ | 156/1371 [00:39<05:03, 4.01it/s] 12%|█▏ | 168/1371 [00:42<05:01, 4.00it/s] 13%|█▎ | 180/1371 [00:45<04:57, 4.00it/s] 14%|█▍ | 192/1371 [00:48<04:55, 3.98it/s] 15%|█▍ | 204/1371 [00:51<05:06, 3.81it/s] 16%|█▌ | 216/1371 [00:54<05:03, 3.80it/s] 17%|█▋ | 228/1371 [00:57<04:58, 3.82it/s] 18%|█▊ | 240/1371 [01:00<04:53, 3.85it/s] 18%|█▊ | 252/1371 [01:04<04:51, 3.84it/s] 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95%|█████████▍| 1296/1371 [05:37<00:19, 3.89it/s] 95%|█████████▌| 1308/1371 [05:40<00:16, 3.87it/s] 96%|█████████▋| 1320/1371 [05:43<00:13, 3.88it/s] 97%|█████████▋| 1332/1371 [05:47<00:10, 3.86it/s] 98%|█████████▊| 1344/1371 [05:50<00:07, 3.85it/s] 99%|█████████▉| 1356/1371 [05:53<00:03, 3.86it/s] 100%|█████████▉| 1368/1371 [05:56<00:00, 3.89it/s] 100%|██████████| 1371/1371 [05:57<00:00, 3.88it/s]Prediction
arielreplicate/robust_video_matting:73d2128a371922d5d1abf0712a1d974be0e4e2358cc1218e4e34714767232bacID43ujwtzsojd2phcc6hw2sbbbsuStatusSucceededSourceWebHardware–Total durationCreatedInput
- input_video
- output_type
- alpha-mask
{ "input_video": "https://replicate.delivery/pbxt/Hqikd7afw2c9koZXS8c3v08x0MFXZFhxFPBkd0iHxrEmRVrk/eddie.mp4", "output_type": "alpha-mask" }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 arielreplicate/robust_video_matting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "arielreplicate/robust_video_matting:73d2128a371922d5d1abf0712a1d974be0e4e2358cc1218e4e34714767232bac", { input: { input_video: "https://replicate.delivery/pbxt/Hqikd7afw2c9koZXS8c3v08x0MFXZFhxFPBkd0iHxrEmRVrk/eddie.mp4", output_type: "alpha-mask" } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);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 arielreplicate/robust_video_matting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "arielreplicate/robust_video_matting:73d2128a371922d5d1abf0712a1d974be0e4e2358cc1218e4e34714767232bac", input={ "input_video": "https://replicate.delivery/pbxt/Hqikd7afw2c9koZXS8c3v08x0MFXZFhxFPBkd0iHxrEmRVrk/eddie.mp4", "output_type": "alpha-mask" } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())To learn more, take a look at the guide on getting started with Python.
Run arielreplicate/robust_video_matting 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": "arielreplicate/robust_video_matting:73d2128a371922d5d1abf0712a1d974be0e4e2358cc1218e4e34714767232bac", "input": { "input_video": "https://replicate.delivery/pbxt/Hqikd7afw2c9koZXS8c3v08x0MFXZFhxFPBkd0iHxrEmRVrk/eddie.mp4", "output_type": "alpha-mask" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-12-11T17:58:59.726262Z", "created_at": "2022-12-11T17:56:29.408559Z", "data_removed": false, "error": null, "id": "43ujwtzsojd2phcc6hw2sbbbsu", "input": { "input_video": "https://replicate.delivery/pbxt/Hqikd7afw2c9koZXS8c3v08x0MFXZFhxFPBkd0iHxrEmRVrk/eddie.mp4", "output_type": "alpha-mask" }, "logs": "0%| | 0/143 [00:00<?, ?it/s]/root/.pyenv/versions/3.8.15/lib/python3.8/site-packages/torch/nn/functional.py:718: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at /pytorch/c10/core/TensorImpl.h:1156.)\nreturn torch.max_pool2d(input, kernel_size, stride, padding, dilation, ceil_mode)\n 8%|▊ | 12/143 [00:03<00:38, 3.44it/s]\n 17%|█▋ | 24/143 [00:05<00:27, 4.35it/s]\n 25%|██▌ | 36/143 [00:07<00:22, 4.84it/s]\n 34%|███▎ | 48/143 [00:11<00:23, 3.97it/s]\n 42%|████▏ | 60/143 [00:14<00:21, 3.89it/s]\n 50%|█████ | 72/143 [00:17<00:18, 3.93it/s]\n 59%|█████▊ | 84/143 [00:21<00:15, 3.84it/s]\n 67%|██████▋ | 96/143 [00:24<00:12, 3.83it/s]\n 76%|███████▌ | 108/143 [00:27<00:09, 3.88it/s]\n 84%|████████▍ | 120/143 [00:30<00:05, 3.88it/s]\n 92%|█████████▏| 132/143 [00:33<00:02, 3.88it/s]\n100%|██████████| 143/143 [00:36<00:00, 3.85it/s]", "metrics": { "predict_time": 41.630151, "total_time": 150.317703 }, "output": "https://replicate.delivery/pbxt/5wY879GIAWqAJFxBU6UtcHGWNwmnrnLzUgf2G0Jx0XcxYeIQA/alpha-mask.mp4", "started_at": "2022-12-11T17:58:18.096111Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/43ujwtzsojd2phcc6hw2sbbbsu", "cancel": "https://api.replicate.com/v1/predictions/43ujwtzsojd2phcc6hw2sbbbsu/cancel" }, "version": "73d2128a371922d5d1abf0712a1d974be0e4e2358cc1218e4e34714767232bac" }Generated in0%| | 0/143 [00:00<?, ?it/s]/root/.pyenv/versions/3.8.15/lib/python3.8/site-packages/torch/nn/functional.py:718: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at /pytorch/c10/core/TensorImpl.h:1156.) return torch.max_pool2d(input, kernel_size, stride, padding, dilation, ceil_mode) 8%|▊ | 12/143 [00:03<00:38, 3.44it/s] 17%|█▋ | 24/143 [00:05<00:27, 4.35it/s] 25%|██▌ | 36/143 [00:07<00:22, 4.84it/s] 34%|███▎ | 48/143 [00:11<00:23, 3.97it/s] 42%|████▏ | 60/143 [00:14<00:21, 3.89it/s] 50%|█████ | 72/143 [00:17<00:18, 3.93it/s] 59%|█████▊ | 84/143 [00:21<00:15, 3.84it/s] 67%|██████▋ | 96/143 [00:24<00:12, 3.83it/s] 76%|███████▌ | 108/143 [00:27<00:09, 3.88it/s] 84%|████████▍ | 120/143 [00:30<00:05, 3.88it/s] 92%|█████████▏| 132/143 [00:33<00:02, 3.88it/s] 100%|██████████| 143/143 [00:36<00:00, 3.85it/s]Prediction
arielreplicate/robust_video_matting:73d2128a371922d5d1abf0712a1d974be0e4e2358cc1218e4e34714767232bacIDoriptsmtjvbmdmcizvc2d3cbgaStatusSucceededSourceWebHardware–Total durationCreatedInput
- input_video
- output_type
- foreground-mask
{ "input_video": "https://replicate.delivery/pbxt/Hqikd7afw2c9koZXS8c3v08x0MFXZFhxFPBkd0iHxrEmRVrk/eddie.mp4", "output_type": "foreground-mask" }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 arielreplicate/robust_video_matting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "arielreplicate/robust_video_matting:73d2128a371922d5d1abf0712a1d974be0e4e2358cc1218e4e34714767232bac", { input: { input_video: "https://replicate.delivery/pbxt/Hqikd7afw2c9koZXS8c3v08x0MFXZFhxFPBkd0iHxrEmRVrk/eddie.mp4", output_type: "foreground-mask" } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);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 arielreplicate/robust_video_matting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "arielreplicate/robust_video_matting:73d2128a371922d5d1abf0712a1d974be0e4e2358cc1218e4e34714767232bac", input={ "input_video": "https://replicate.delivery/pbxt/Hqikd7afw2c9koZXS8c3v08x0MFXZFhxFPBkd0iHxrEmRVrk/eddie.mp4", "output_type": "foreground-mask" } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())To learn more, take a look at the guide on getting started with Python.
Run arielreplicate/robust_video_matting 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": "arielreplicate/robust_video_matting:73d2128a371922d5d1abf0712a1d974be0e4e2358cc1218e4e34714767232bac", "input": { "input_video": "https://replicate.delivery/pbxt/Hqikd7afw2c9koZXS8c3v08x0MFXZFhxFPBkd0iHxrEmRVrk/eddie.mp4", "output_type": "foreground-mask" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-12-11T18:00:17.356261Z", "created_at": "2022-12-11T17:59:46.010875Z", "data_removed": false, "error": null, "id": "oriptsmtjvbmdmcizvc2d3cbga", "input": { "input_video": "https://replicate.delivery/pbxt/Hqikd7afw2c9koZXS8c3v08x0MFXZFhxFPBkd0iHxrEmRVrk/eddie.mp4", "output_type": "foreground-mask" }, "logs": "0%| | 0/143 [00:00<?, ?it/s]\u001b[A\n 8%|▊ | 12/143 [00:01<00:17, 7.64it/s]\u001b[A\n 17%|█▋ | 24/143 [00:03<00:15, 7.82it/s]\u001b[A\n 25%|██▌ | 36/143 [00:04<00:13, 7.74it/s]\u001b[A\n 34%|███▎ | 48/143 [00:07<00:15, 6.05it/s]\u001b[A\n 42%|████▏ | 60/143 [00:09<00:14, 5.70it/s]\u001b[A\n 50%|█████ | 72/143 [00:12<00:13, 5.30it/s]\u001b[A\n 59%|█████▊ | 84/143 [00:14<00:11, 5.09it/s]\u001b[A\n 67%|██████▋ | 96/143 [00:17<00:09, 5.01it/s]\u001b[A\n 76%|███████▌ | 108/143 [00:19<00:07, 5.00it/s]\u001b[A\n 84%|████████▍ | 120/143 [00:22<00:04, 4.84it/s]\u001b[A\n 92%|█████████▏| 132/143 [00:24<00:02, 4.79it/s]\u001b[A\n100%|██████████| 143/143 [00:27<00:00, 4.71it/s]\u001b[A", "metrics": { "predict_time": 31.311155, "total_time": 31.345386 }, "output": "https://replicate.delivery/pbxt/dpw8YGYG4TZwGNYfKAe79EkI4yzj2m6ZzFqheKMp4KPhl5RgA/foreground-mask.mp4", "started_at": "2022-12-11T17:59:46.045106Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/oriptsmtjvbmdmcizvc2d3cbga", "cancel": "https://api.replicate.com/v1/predictions/oriptsmtjvbmdmcizvc2d3cbga/cancel" }, "version": "73d2128a371922d5d1abf0712a1d974be0e4e2358cc1218e4e34714767232bac" }Generated in0%| | 0/143 [00:00<?, ?it/s] 8%|▊ | 12/143 [00:01<00:17, 7.64it/s] 17%|█▋ | 24/143 [00:03<00:15, 7.82it/s] 25%|██▌ | 36/143 [00:04<00:13, 7.74it/s] 34%|███▎ | 48/143 [00:07<00:15, 6.05it/s] 42%|████▏ | 60/143 [00:09<00:14, 5.70it/s] 50%|█████ | 72/143 [00:12<00:13, 5.30it/s] 59%|█████▊ | 84/143 [00:14<00:11, 5.09it/s] 67%|██████▋ | 96/143 [00:17<00:09, 5.01it/s] 76%|███████▌ | 108/143 [00:19<00:07, 5.00it/s] 84%|████████▍ | 120/143 [00:22<00:04, 4.84it/s] 92%|█████████▏| 132/143 [00:24<00:02, 4.79it/s] 100%|██████████| 143/143 [00:27<00:00, 4.71it/s]
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