Prediction

Model

mohamad1998630/controlnet:905298f5

elsb22zbvrv5nxstfzbzfrstpy

Status

Succeeded

Source

Web

Hardware

Total duration

8m 12s

Created

almost 2 years ago

Webhook

–

Input

input_image_path: https://replicate.delivery/pbxt/KSbEAl9T5UeDInRBNViM9xIpyYR2XNcRVqXC8gKJeWSfNe1y/point3d-commercial-imaging-ltd-nQlVMCHPysY-unsplash.jpg
prompt: Put furniture
a_prompt: best quality, extremely detailed
n_prompt: longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality
num_samples: 1
image_resolution: 512
detect_resolution: 512
ddim_steps: 20
guess_mode: false
strength: 1
scale: 9
seed: 3.5
eta: 0

{
  "a_prompt": "best quality, extremely detailed",
  "ddim_steps": 20,
  "detect_resolution": 512,
  "eta": 0,
  "guess_mode": false,
  "image_resolution": 512,
  "input_image_path": "https://replicate.delivery/pbxt/KSbEAl9T5UeDInRBNViM9xIpyYR2XNcRVqXC8gKJeWSfNe1y/point3d-commercial-imaging-ltd-nQlVMCHPysY-unsplash.jpg",
  "n_prompt": "longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
  "num_samples": 1,
  "prompt": "Put furniture",
  "scale": 9,
  "seed": 3.5,
  "strength": 1
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_1hf**********************************

This is your API token. Keep it to yourself.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run mohamad1998630/controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "mohamad1998630/controlnet:905298f5d96cb992b6133132b151d4029122599cfd57d7ceb4c4e447b2390855",
  {
    input: {
      a_prompt: "best quality, extremely detailed",
      ddim_steps: 20,
      detect_resolution: 512,
      eta: 0,
      guess_mode: false,
      image_resolution: 512,
      input_image_path: "https://replicate.delivery/pbxt/KSbEAl9T5UeDInRBNViM9xIpyYR2XNcRVqXC8gKJeWSfNe1y/point3d-commercial-imaging-ltd-nQlVMCHPysY-unsplash.jpg",
      n_prompt: "longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
      num_samples: 1,
      prompt: "Put furniture",
      scale: 9,
      seed: 3.5,
      strength: 1
    }
  }
);

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 the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_1hf**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run mohamad1998630/controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "mohamad1998630/controlnet:905298f5d96cb992b6133132b151d4029122599cfd57d7ceb4c4e447b2390855",
    input={
        "a_prompt": "best quality, extremely detailed",
        "ddim_steps": 20,
        "detect_resolution": 512,
        "eta": 0,
        "guess_mode": False,
        "image_resolution": 512,
        "input_image_path": "https://replicate.delivery/pbxt/KSbEAl9T5UeDInRBNViM9xIpyYR2XNcRVqXC8gKJeWSfNe1y/point3d-commercial-imaging-ltd-nQlVMCHPysY-unsplash.jpg",
        "n_prompt": "longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
        "num_samples": 1,
        "prompt": "Put furniture",
        "scale": 9,
        "seed": 3.5,
        "strength": 1
    }
)

print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_1hf**********************************

This is your API token. Keep it to yourself.

Run mohamad1998630/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": "mohamad1998630/controlnet:905298f5d96cb992b6133132b151d4029122599cfd57d7ceb4c4e447b2390855",
    "input": {
      "a_prompt": "best quality, extremely detailed",
      "ddim_steps": 20,
      "detect_resolution": 512,
      "eta": 0,
      "guess_mode": false,
      "image_resolution": 512,
      "input_image_path": "https://replicate.delivery/pbxt/KSbEAl9T5UeDInRBNViM9xIpyYR2XNcRVqXC8gKJeWSfNe1y/point3d-commercial-imaging-ltd-nQlVMCHPysY-unsplash.jpg",
      "n_prompt": "longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
      "num_samples": 1,
      "prompt": "Put furniture",
      "scale": 9,
      "seed": 3.5,
      "strength": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

Unable to display output

{
  "id": "elsb22zbvrv5nxstfzbzfrstpy",
  "model": "mohamad1998630/controlnet",
  "version": "905298f5d96cb992b6133132b151d4029122599cfd57d7ceb4c4e447b2390855",
  "input": {
    "a_prompt": "best quality, extremely detailed",
    "ddim_steps": 20,
    "detect_resolution": 512,
    "eta": 0,
    "guess_mode": false,
    "image_resolution": 512,
    "input_image_path": "https://replicate.delivery/pbxt/KSbEAl9T5UeDInRBNViM9xIpyYR2XNcRVqXC8gKJeWSfNe1y/point3d-commercial-imaging-ltd-nQlVMCHPysY-unsplash.jpg",
    "n_prompt": "longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
    "num_samples": 1,
    "prompt": "Put furniture",
    "scale": 9,
    "seed": 3.5,
    "strength": 1
  },
  "logs": "Image shape: (4480, 6720, 3)\n/src/annotator/uniformer/mmseg/models/segmentors/base.py:271: UserWarning: show==False and out_file is not specified, only result image will be returned\nwarnings.warn('show==False and out_file is not specified, only '\nGlobal seed set to 3\nData shape for DDIM sampling is (1, 4, 64, 96), eta 0.0\nRunning DDIM Sampling with 20 timesteps\nDDIM Sampler:   0%|          | 0/20 [00:00<?, ?it/s]\nDDIM Sampler:   5%|▌         | 1/20 [00:01<00:30,  1.59s/it]\nDDIM Sampler:  10%|█         | 2/20 [00:02<00:26,  1.47s/it]\nDDIM Sampler:  15%|█▌        | 3/20 [00:04<00:24,  1.43s/it]\nDDIM Sampler:  20%|██        | 4/20 [00:05<00:22,  1.42s/it]\nDDIM Sampler:  25%|██▌       | 5/20 [00:07<00:21,  1.41s/it]\nDDIM Sampler:  30%|███       | 6/20 [00:08<00:19,  1.41s/it]\nDDIM Sampler:  35%|███▌      | 7/20 [00:09<00:18,  1.41s/it]\nDDIM Sampler:  40%|████      | 8/20 [00:11<00:16,  1.41s/it]\nDDIM Sampler:  45%|████▌     | 9/20 [00:12<00:15,  1.42s/it]\nDDIM Sampler:  50%|█████     | 10/20 [00:14<00:14,  1.42s/it]\nDDIM Sampler:  55%|█████▌    | 11/20 [00:15<00:12,  1.42s/it]\nDDIM Sampler:  60%|██████    | 12/20 [00:17<00:11,  1.43s/it]\nDDIM Sampler:  65%|██████▌   | 13/20 [00:18<00:10,  1.43s/it]\nDDIM Sampler:  70%|███████   | 14/20 [00:19<00:08,  1.43s/it]\nDDIM Sampler:  75%|███████▌  | 15/20 [00:21<00:07,  1.43s/it]\nDDIM Sampler:  80%|████████  | 16/20 [00:22<00:05,  1.43s/it]\nDDIM Sampler:  85%|████████▌ | 17/20 [00:24<00:04,  1.44s/it]\nDDIM Sampler:  90%|█████████ | 18/20 [00:25<00:02,  1.44s/it]\nDDIM Sampler:  95%|█████████▌| 19/20 [00:27<00:01,  1.45s/it]\nDDIM Sampler: 100%|██████████| 20/20 [00:28<00:00,  1.45s/it]\nDDIM Sampler: 100%|██████████| 20/20 [00:28<00:00,  1.43s/it]\n<class 'numpy.ndarray'>\n(512, 768, 3)",
  "output": [
    "https://storage.googleapis.com/replicate-files/PWpGmEAwYp50OddPlMXlUXKnekgZE78oqSucrfA7nFRqY8ZSA/out-0.png"
  ],
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2024-02-24T15:58:54.438733Z",
  "started_at": "2024-02-24T16:06:31.466093Z",
  "completed_at": "2024-02-24T16:07:06.767767Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/elsb22zbvrv5nxstfzbzfrstpy/cancel",
    "get": "https://api.replicate.com/v1/predictions/elsb22zbvrv5nxstfzbzfrstpy"
  },
  "metrics": {
    "predict_time": 35.301674,
    "total_time": 492.329034
  }
}

Generated in

35.3 seconds

Tweak it Report

Image shape: (4480, 6720, 3) /src/annotator/uniformer/mmseg/models/segmentors/base.py:271: UserWarning: show==False and out_file is not specified, only result image will be returned warnings.warn('show==False and out_file is not specified, only ' Global seed set to 3 Data shape for DDIM sampling is (1, 4, 64, 96), eta 0.0 Running DDIM Sampling with 20 timesteps DDIM Sampler: 0%| | 0/20 [00:00<?, ?it/s] DDIM Sampler: 5%|▌ | 1/20 [00:01<00:30, 1.59s/it] DDIM Sampler: 10%|█ | 2/20 [00:02<00:26, 1.47s/it] DDIM Sampler: 15%|█▌ | 3/20 [00:04<00:24, 1.43s/it] DDIM Sampler: 20%|██ | 4/20 [00:05<00:22, 1.42s/it] DDIM Sampler: 25%|██▌ | 5/20 [00:07<00:21, 1.41s/it] DDIM Sampler: 30%|███ | 6/20 [00:08<00:19, 1.41s/it] DDIM Sampler: 35%|███▌ | 7/20 [00:09<00:18, 1.41s/it] DDIM Sampler: 40%|████ | 8/20 [00:11<00:16, 1.41s/it] DDIM Sampler: 45%|████▌ | 9/20 [00:12<00:15, 1.42s/it] DDIM Sampler: 50%|█████ | 10/20 [00:14<00:14, 1.42s/it] DDIM Sampler: 55%|█████▌ | 11/20 [00:15<00:12, 1.42s/it] DDIM Sampler: 60%|██████ | 12/20 [00:17<00:11, 1.43s/it] DDIM Sampler: 65%|██████▌ | 13/20 [00:18<00:10, 1.43s/it] DDIM Sampler: 70%|███████ | 14/20 [00:19<00:08, 1.43s/it] DDIM Sampler: 75%|███████▌ | 15/20 [00:21<00:07, 1.43s/it] DDIM Sampler: 80%|████████ | 16/20 [00:22<00:05, 1.43s/it] DDIM Sampler: 85%|████████▌ | 17/20 [00:24<00:04, 1.44s/it] DDIM Sampler: 90%|█████████ | 18/20 [00:25<00:02, 1.44s/it] DDIM Sampler: 95%|█████████▌| 19/20 [00:27<00:01, 1.45s/it] DDIM Sampler: 100%|██████████| 20/20 [00:28<00:00, 1.45s/it] DDIM Sampler: 100%|██████████| 20/20 [00:28<00:00, 1.43s/it] <class 'numpy.ndarray'> (512, 768, 3)