subhash25rawat / flux-vton
The power of flux with the model trained on VITON-HD used for try-on on categories such as upper body, lower body and full body dresses
- Public
- 5.3K runs
-
L40S
Prediction
subhash25rawat/flux-vton:7cf578125adc20630e8a55051acf9e352ffb69907e858084ac207b7ddd107bbeID04k579n4phrm80cmebmbnjx2dcStatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- part
- upper_body
- image
- garment
{ "part": "upper_body", "image": "https://replicate.delivery/pbxt/MKsjMFNbXviuMJQgUjMRlkxUi0gVbiyEyOzHusT8sMr1g3Yy/male-model.jpg", "garment": "https://replicate.delivery/pbxt/MKsjMbuXDuyNsu5t2rpybvaUmFoEJLA968IE8IIBZGnGes9s/t-shirt.jpg" }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 subhash25rawat/flux-vton using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "subhash25rawat/flux-vton:7cf578125adc20630e8a55051acf9e352ffb69907e858084ac207b7ddd107bbe", { input: { part: "upper_body", image: "https://replicate.delivery/pbxt/MKsjMFNbXviuMJQgUjMRlkxUi0gVbiyEyOzHusT8sMr1g3Yy/male-model.jpg", garment: "https://replicate.delivery/pbxt/MKsjMbuXDuyNsu5t2rpybvaUmFoEJLA968IE8IIBZGnGes9s/t-shirt.jpg" } } ); // 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 subhash25rawat/flux-vton using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "subhash25rawat/flux-vton:7cf578125adc20630e8a55051acf9e352ffb69907e858084ac207b7ddd107bbe", input={ "part": "upper_body", "image": "https://replicate.delivery/pbxt/MKsjMFNbXviuMJQgUjMRlkxUi0gVbiyEyOzHusT8sMr1g3Yy/male-model.jpg", "garment": "https://replicate.delivery/pbxt/MKsjMbuXDuyNsu5t2rpybvaUmFoEJLA968IE8IIBZGnGes9s/t-shirt.jpg" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run subhash25rawat/flux-vton 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": "subhash25rawat/flux-vton:7cf578125adc20630e8a55051acf9e352ffb69907e858084ac207b7ddd107bbe", "input": { "part": "upper_body", "image": "https://replicate.delivery/pbxt/MKsjMFNbXviuMJQgUjMRlkxUi0gVbiyEyOzHusT8sMr1g3Yy/male-model.jpg", "garment": "https://replicate.delivery/pbxt/MKsjMbuXDuyNsu5t2rpybvaUmFoEJLA968IE8IIBZGnGes9s/t-shirt.jpg" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-17T06:18:01.263438Z", "created_at": "2025-01-17T06:17:16.724000Z", "data_removed": false, "error": null, "id": "04k579n4phrm80cmebmbnjx2dc", "input": { "part": "upper_body", "image": "https://replicate.delivery/pbxt/MKsjMFNbXviuMJQgUjMRlkxUi0gVbiyEyOzHusT8sMr1g3Yy/male-model.jpg", "garment": "https://replicate.delivery/pbxt/MKsjMbuXDuyNsu5t2rpybvaUmFoEJLA968IE8IIBZGnGes9s/t-shirt.jpg" }, "logs": "Original image size: 853x1280\nResized image size: 682x1024\nImage pasted at: 43, 0\nfor upper\n 0%| | 0/1 [00:00<?, ?it/s]\n100%|██████████| 1/1 [00:02<00:00, 2.80s/it]\n100%|██████████| 1/1 [00:02<00:00, 2.80s/it]\n 0%| | 0/1 [00:00<?, ?it/s]\n100%|██████████| 1/1 [00:03<00:00, 3.24s/it]\n100%|██████████| 1/1 [00:03<00:00, 3.24s/it]\nOriginal image size: 1000x1000\nResized image size: 768x768\nImage pasted at: 0, 128\n/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/diffusers/image_processor.py:724: FutureWarning: Passing `image` as torch tensor with value range in [-1,1] is deprecated. The expected value range for image tensor is [0,1] when passing as pytorch tensor or numpy Array. You passed `image` with value range [-1.0,1.0]\nwarnings.warn(\n 0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:13, 2.07it/s]\n 7%|▋ | 2/30 [00:00<00:10, 2.67it/s]\n 10%|█ | 3/30 [00:01<00:11, 2.42it/s]\n 13%|█▎ | 4/30 [00:01<00:11, 2.32it/s]\n 17%|█▋ | 5/30 [00:02<00:11, 2.26it/s]\n 20%|██ | 6/30 [00:02<00:10, 2.23it/s]\n 23%|██▎ | 7/30 [00:03<00:10, 2.21it/s]\n 27%|██▋ | 8/30 [00:03<00:10, 2.20it/s]\n 30%|███ | 9/30 [00:04<00:09, 2.19it/s]\n 33%|███▎ | 10/30 [00:04<00:09, 2.18it/s]\n 37%|███▋ | 11/30 [00:04<00:08, 2.18it/s]\n 40%|████ | 12/30 [00:05<00:08, 2.18it/s]\n 43%|████▎ | 13/30 [00:05<00:07, 2.17it/s]\n 47%|████▋ | 14/30 [00:06<00:07, 2.17it/s]\n 50%|█████ | 15/30 [00:06<00:06, 2.17it/s]\n 53%|█████▎ | 16/30 [00:07<00:06, 2.17it/s]\n 57%|█████▋ | 17/30 [00:07<00:06, 2.17it/s]\n 60%|██████ | 18/30 [00:08<00:05, 2.16it/s]\n 63%|██████▎ | 19/30 [00:08<00:05, 2.16it/s]\n 67%|██████▋ | 20/30 [00:09<00:04, 2.16it/s]\n 70%|███████ | 21/30 [00:09<00:04, 2.16it/s]\n 73%|███████▎ | 22/30 [00:10<00:03, 2.16it/s]\n 77%|███████▋ | 23/30 [00:10<00:03, 2.16it/s]\n 80%|████████ | 24/30 [00:10<00:02, 2.16it/s]\n 83%|████████▎ | 25/30 [00:11<00:02, 2.16it/s]\n 87%|████████▋ | 26/30 [00:11<00:01, 2.16it/s]\n 90%|█████████ | 27/30 [00:12<00:01, 2.16it/s]\n 93%|█████████▎| 28/30 [00:12<00:00, 2.16it/s]\n 97%|█████████▋| 29/30 [00:13<00:00, 2.16it/s]\n100%|██████████| 30/30 [00:13<00:00, 2.16it/s]\n100%|██████████| 30/30 [00:13<00:00, 2.19it/s]", "metrics": { "predict_time": 22.313595797, "total_time": 44.539438 }, "output": "https://replicate.delivery/xezq/lC3tqK4p2KYIOh8iReEkmfAGajpKStvv4t3nX3PhQN8Zg6FUA/temp_tryon.png", "started_at": "2025-01-17T06:17:38.949842Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-o66yoyixmgrabgwtnujjq7oqapio4jianikdta4atodlwrk4m5fq", "get": "https://api.replicate.com/v1/predictions/04k579n4phrm80cmebmbnjx2dc", "cancel": "https://api.replicate.com/v1/predictions/04k579n4phrm80cmebmbnjx2dc/cancel" }, "version": "7cf578125adc20630e8a55051acf9e352ffb69907e858084ac207b7ddd107bbe" }Generated inOriginal image size: 853x1280 Resized image size: 682x1024 Image pasted at: 43, 0 for upper 0%| | 0/1 [00:00<?, ?it/s] 100%|██████████| 1/1 [00:02<00:00, 2.80s/it] 100%|██████████| 1/1 [00:02<00:00, 2.80s/it] 0%| | 0/1 [00:00<?, ?it/s] 100%|██████████| 1/1 [00:03<00:00, 3.24s/it] 100%|██████████| 1/1 [00:03<00:00, 3.24s/it] Original image size: 1000x1000 Resized image size: 768x768 Image pasted at: 0, 128 /root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/diffusers/image_processor.py:724: FutureWarning: Passing `image` as torch tensor with value range in [-1,1] is deprecated. The expected value range for image tensor is [0,1] when passing as pytorch tensor or numpy Array. You passed `image` with value range [-1.0,1.0] warnings.warn( 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:13, 2.07it/s] 7%|▋ | 2/30 [00:00<00:10, 2.67it/s] 10%|█ | 3/30 [00:01<00:11, 2.42it/s] 13%|█▎ | 4/30 [00:01<00:11, 2.32it/s] 17%|█▋ | 5/30 [00:02<00:11, 2.26it/s] 20%|██ | 6/30 [00:02<00:10, 2.23it/s] 23%|██▎ | 7/30 [00:03<00:10, 2.21it/s] 27%|██▋ | 8/30 [00:03<00:10, 2.20it/s] 30%|███ | 9/30 [00:04<00:09, 2.19it/s] 33%|███▎ | 10/30 [00:04<00:09, 2.18it/s] 37%|███▋ | 11/30 [00:04<00:08, 2.18it/s] 40%|████ | 12/30 [00:05<00:08, 2.18it/s] 43%|████▎ | 13/30 [00:05<00:07, 2.17it/s] 47%|████▋ | 14/30 [00:06<00:07, 2.17it/s] 50%|█████ | 15/30 [00:06<00:06, 2.17it/s] 53%|█████▎ | 16/30 [00:07<00:06, 2.17it/s] 57%|█████▋ | 17/30 [00:07<00:06, 2.17it/s] 60%|██████ | 18/30 [00:08<00:05, 2.16it/s] 63%|██████▎ | 19/30 [00:08<00:05, 2.16it/s] 67%|██████▋ | 20/30 [00:09<00:04, 2.16it/s] 70%|███████ | 21/30 [00:09<00:04, 2.16it/s] 73%|███████▎ | 22/30 [00:10<00:03, 2.16it/s] 77%|███████▋ | 23/30 [00:10<00:03, 2.16it/s] 80%|████████ | 24/30 [00:10<00:02, 2.16it/s] 83%|████████▎ | 25/30 [00:11<00:02, 2.16it/s] 87%|████████▋ | 26/30 [00:11<00:01, 2.16it/s] 90%|█████████ | 27/30 [00:12<00:01, 2.16it/s] 93%|█████████▎| 28/30 [00:12<00:00, 2.16it/s] 97%|█████████▋| 29/30 [00:13<00:00, 2.16it/s] 100%|██████████| 30/30 [00:13<00:00, 2.16it/s] 100%|██████████| 30/30 [00:13<00:00, 2.19it/s]Prediction
subhash25rawat/flux-vton:7cf578125adc20630e8a55051acf9e352ffb69907e858084ac207b7ddd107bbeIDenp8w2v8a9rm80cmebqrtb0x7rStatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- part
- upper_body
- image
- garment
{ "part": "upper_body", "image": "https://replicate.delivery/pbxt/MKsqOXT1lV7HV7YiDLnHoiCZk9bGcHu0RSDl6mBNXkZFJZnm/ai-generated-9137969_1280.png", "garment": "https://replicate.delivery/pbxt/MKsqNsRMRNlfH7efXKUxBvI0Rg3J2NVJsJehF2Aw01ALguvr/67597d939aa46b60c1188814-ustzftbcl-style-men-coat-business.jpg" }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 subhash25rawat/flux-vton using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "subhash25rawat/flux-vton:7cf578125adc20630e8a55051acf9e352ffb69907e858084ac207b7ddd107bbe", { input: { part: "upper_body", image: "https://replicate.delivery/pbxt/MKsqOXT1lV7HV7YiDLnHoiCZk9bGcHu0RSDl6mBNXkZFJZnm/ai-generated-9137969_1280.png", garment: "https://replicate.delivery/pbxt/MKsqNsRMRNlfH7efXKUxBvI0Rg3J2NVJsJehF2Aw01ALguvr/67597d939aa46b60c1188814-ustzftbcl-style-men-coat-business.jpg" } } ); // 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 subhash25rawat/flux-vton using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "subhash25rawat/flux-vton:7cf578125adc20630e8a55051acf9e352ffb69907e858084ac207b7ddd107bbe", input={ "part": "upper_body", "image": "https://replicate.delivery/pbxt/MKsqOXT1lV7HV7YiDLnHoiCZk9bGcHu0RSDl6mBNXkZFJZnm/ai-generated-9137969_1280.png", "garment": "https://replicate.delivery/pbxt/MKsqNsRMRNlfH7efXKUxBvI0Rg3J2NVJsJehF2Aw01ALguvr/67597d939aa46b60c1188814-ustzftbcl-style-men-coat-business.jpg" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run subhash25rawat/flux-vton 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": "subhash25rawat/flux-vton:7cf578125adc20630e8a55051acf9e352ffb69907e858084ac207b7ddd107bbe", "input": { "part": "upper_body", "image": "https://replicate.delivery/pbxt/MKsqOXT1lV7HV7YiDLnHoiCZk9bGcHu0RSDl6mBNXkZFJZnm/ai-generated-9137969_1280.png", "garment": "https://replicate.delivery/pbxt/MKsqNsRMRNlfH7efXKUxBvI0Rg3J2NVJsJehF2Aw01ALguvr/67597d939aa46b60c1188814-ustzftbcl-style-men-coat-business.jpg" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-17T06:25:02.461593Z", "created_at": "2025-01-17T06:24:40.018000Z", "data_removed": false, "error": null, "id": "enp8w2v8a9rm80cmebqrtb0x7r", "input": { "part": "upper_body", "image": "https://replicate.delivery/pbxt/MKsqOXT1lV7HV7YiDLnHoiCZk9bGcHu0RSDl6mBNXkZFJZnm/ai-generated-9137969_1280.png", "garment": "https://replicate.delivery/pbxt/MKsqNsRMRNlfH7efXKUxBvI0Rg3J2NVJsJehF2Aw01ALguvr/67597d939aa46b60c1188814-ustzftbcl-style-men-coat-business.jpg" }, "logs": "Original image size: 1280x1280\nResized image size: 768x768\nImage pasted at: 0, 128\nfor upper\n 0%| | 0/1 [00:00<?, ?it/s]\n100%|██████████| 1/1 [00:03<00:00, 3.53s/it]\n100%|██████████| 1/1 [00:03<00:00, 3.53s/it]\n 0%| | 0/1 [00:00<?, ?it/s]\n100%|██████████| 1/1 [00:03<00:00, 3.14s/it]\n100%|██████████| 1/1 [00:03<00:00, 3.14s/it]\nOriginal image size: 1207x1467\nResized image size: 768x933\nImage pasted at: 0, 45\n 0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:13, 2.18it/s]\n 7%|▋ | 2/30 [00:00<00:10, 2.73it/s]\n 10%|█ | 3/30 [00:01<00:11, 2.44it/s]\n 13%|█▎ | 4/30 [00:01<00:11, 2.33it/s]\n 17%|█▋ | 5/30 [00:02<00:11, 2.27it/s]\n 20%|██ | 6/30 [00:02<00:10, 2.23it/s]\n 23%|██▎ | 7/30 [00:03<00:10, 2.21it/s]\n 27%|██▋ | 8/30 [00:03<00:10, 2.20it/s]\n 30%|███ | 9/30 [00:03<00:09, 2.19it/s]\n 33%|███▎ | 10/30 [00:04<00:09, 2.18it/s]\n 37%|███▋ | 11/30 [00:04<00:08, 2.17it/s]\n 40%|████ | 12/30 [00:05<00:08, 2.17it/s]\n 43%|████▎ | 13/30 [00:05<00:07, 2.17it/s]\n 47%|████▋ | 14/30 [00:06<00:07, 2.17it/s]\n 50%|█████ | 15/30 [00:06<00:06, 2.16it/s]\n 53%|█████▎ | 16/30 [00:07<00:06, 2.16it/s]\n 57%|█████▋ | 17/30 [00:07<00:06, 2.16it/s]\n 60%|██████ | 18/30 [00:08<00:05, 2.16it/s]\n 63%|██████▎ | 19/30 [00:08<00:05, 2.16it/s]\n 67%|██████▋ | 20/30 [00:09<00:04, 2.16it/s]\n 70%|███████ | 21/30 [00:09<00:04, 2.16it/s]\n 73%|███████▎ | 22/30 [00:10<00:03, 2.16it/s]\n 77%|███████▋ | 23/30 [00:10<00:03, 2.16it/s]\n 80%|████████ | 24/30 [00:10<00:02, 2.16it/s]\n 83%|████████▎ | 25/30 [00:11<00:02, 2.16it/s]\n 87%|████████▋ | 26/30 [00:11<00:01, 2.16it/s]\n 90%|█████████ | 27/30 [00:12<00:01, 2.16it/s]\n 93%|█████████▎| 28/30 [00:12<00:00, 2.16it/s]\n 97%|█████████▋| 29/30 [00:13<00:00, 2.16it/s]\n100%|██████████| 30/30 [00:13<00:00, 2.16it/s]\n100%|██████████| 30/30 [00:13<00:00, 2.19it/s]", "metrics": { "predict_time": 22.436010776, "total_time": 22.443593 }, "output": "https://replicate.delivery/xezq/uEJhXKJeBp2XHKp96Bfq9o3VHuJ13XDWJw1cdS06xBreN1LoA/temp_tryon.png", "started_at": "2025-01-17T06:24:40.025582Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-y5xcwug5t3xfmv3ghmvpwatqhtmwxub2r5iln33eafwm75igmybq", "get": "https://api.replicate.com/v1/predictions/enp8w2v8a9rm80cmebqrtb0x7r", "cancel": "https://api.replicate.com/v1/predictions/enp8w2v8a9rm80cmebqrtb0x7r/cancel" }, "version": "7cf578125adc20630e8a55051acf9e352ffb69907e858084ac207b7ddd107bbe" }Generated inOriginal image size: 1280x1280 Resized image size: 768x768 Image pasted at: 0, 128 for upper 0%| | 0/1 [00:00<?, ?it/s] 100%|██████████| 1/1 [00:03<00:00, 3.53s/it] 100%|██████████| 1/1 [00:03<00:00, 3.53s/it] 0%| | 0/1 [00:00<?, ?it/s] 100%|██████████| 1/1 [00:03<00:00, 3.14s/it] 100%|██████████| 1/1 [00:03<00:00, 3.14s/it] Original image size: 1207x1467 Resized image size: 768x933 Image pasted at: 0, 45 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:13, 2.18it/s] 7%|▋ | 2/30 [00:00<00:10, 2.73it/s] 10%|█ | 3/30 [00:01<00:11, 2.44it/s] 13%|█▎ | 4/30 [00:01<00:11, 2.33it/s] 17%|█▋ | 5/30 [00:02<00:11, 2.27it/s] 20%|██ | 6/30 [00:02<00:10, 2.23it/s] 23%|██▎ | 7/30 [00:03<00:10, 2.21it/s] 27%|██▋ | 8/30 [00:03<00:10, 2.20it/s] 30%|███ | 9/30 [00:03<00:09, 2.19it/s] 33%|███▎ | 10/30 [00:04<00:09, 2.18it/s] 37%|███▋ | 11/30 [00:04<00:08, 2.17it/s] 40%|████ | 12/30 [00:05<00:08, 2.17it/s] 43%|████▎ | 13/30 [00:05<00:07, 2.17it/s] 47%|████▋ | 14/30 [00:06<00:07, 2.17it/s] 50%|█████ | 15/30 [00:06<00:06, 2.16it/s] 53%|█████▎ | 16/30 [00:07<00:06, 2.16it/s] 57%|█████▋ | 17/30 [00:07<00:06, 2.16it/s] 60%|██████ | 18/30 [00:08<00:05, 2.16it/s] 63%|██████▎ | 19/30 [00:08<00:05, 2.16it/s] 67%|██████▋ | 20/30 [00:09<00:04, 2.16it/s] 70%|███████ | 21/30 [00:09<00:04, 2.16it/s] 73%|███████▎ | 22/30 [00:10<00:03, 2.16it/s] 77%|███████▋ | 23/30 [00:10<00:03, 2.16it/s] 80%|████████ | 24/30 [00:10<00:02, 2.16it/s] 83%|████████▎ | 25/30 [00:11<00:02, 2.16it/s] 87%|████████▋ | 26/30 [00:11<00:01, 2.16it/s] 90%|█████████ | 27/30 [00:12<00:01, 2.16it/s] 93%|█████████▎| 28/30 [00:12<00:00, 2.16it/s] 97%|█████████▋| 29/30 [00:13<00:00, 2.16it/s] 100%|██████████| 30/30 [00:13<00:00, 2.16it/s] 100%|██████████| 30/30 [00:13<00:00, 2.19it/s]
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