adirik

owlvit-base-patch32

Cold

Zero-shot / open vocabulary object detection

Public

24.4K runs

Run with an API

Playground API Examples README Versions

Prediction

adirik/owlvit-base-patch32:5e899f155a1913c4b7304d09082d842ca7fe6cb1f22e066c83eb1d7849dc37c2

Model

adirik/owlvit-base-patch32:5e899f15

ffmhlhjctmenev6bxaxe2ttrle

Status

Succeeded

Source

Web

Hardware

Total duration

1.6s

Created

almost 2 years ago

Input

image
query: coffee mug, spoon, plate
threshold: 0.1
show_visualisation

{
  "image": "https://replicate.delivery/pbxt/Jh100vIU9obkADGR9azMILJEmscUA51n1uFqwSWP5iyuw4TB/coffee.png",
  "query": "coffee mug, spoon, plate",
  "threshold": 0.1,
  "show_visualisation": true
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run adirik/owlvit-base-patch32 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "adirik/owlvit-base-patch32:5e899f155a1913c4b7304d09082d842ca7fe6cb1f22e066c83eb1d7849dc37c2",
  {
    input: {
      image: "https://replicate.delivery/pbxt/Jh100vIU9obkADGR9azMILJEmscUA51n1uFqwSWP5iyuw4TB/coffee.png",
      query: "coffee mug, spoon, plate",
      threshold: 0.1,
      show_visualisation: true
    }
  }
);

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

Import the client:

import replicate

Run adirik/owlvit-base-patch32 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "adirik/owlvit-base-patch32:5e899f155a1913c4b7304d09082d842ca7fe6cb1f22e066c83eb1d7849dc37c2",
    input={
        "image": "https://replicate.delivery/pbxt/Jh100vIU9obkADGR9azMILJEmscUA51n1uFqwSWP5iyuw4TB/coffee.png",
        "query": "coffee mug, spoon, plate",
        "threshold": 0.1,
        "show_visualisation": True
    }
)

print(output)

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

Run adirik/owlvit-base-patch32 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": "adirik/owlvit-base-patch32:5e899f155a1913c4b7304d09082d842ca7fe6cb1f22e066c83eb1d7849dc37c2",
    "input": {
      "image": "https://replicate.delivery/pbxt/Jh100vIU9obkADGR9azMILJEmscUA51n1uFqwSWP5iyuw4TB/coffee.png",
      "query": "coffee mug, spoon, plate",
      "threshold": 0.1,
      "show_visualisation": true
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

json_data

{ "objects": [ { "bbox": [ 175, 24, 420, 246 ], "label": "coffee mug", "confidence": 0.17516785860061646 }, { "bbox": [ 248, 63, 418, 327 ], "label": "spoon", "confidence": 0.13194623589515686 }, { "bbox": [ 78, 74, 481, 391 ], "label": "plate", "confidence": 0.11545269191265106 } ] }

result_image

Generated in

1.6 seconds

Tweak it Share Report

Prediction

adirik/owlvit-base-patch32:5e899f155a1913c4b7304d09082d842ca7fe6cb1f22e066c83eb1d7849dc37c2

Model

adirik/owlvit-base-patch32:5e899f15

2viboyrc3hn5eelepidmqfzm6i

Status

Succeeded

Source

Web

Hardware

Total duration

3m 31s

Created

almost 2 years ago

Input

image
query: human face, rocket, star-spangled banner, nasa badge
threshold: 0.11
show_visualisation

{
  "image": "https://replicate.delivery/pbxt/JhlycB8ScNVrMu0ke1Xlg09ajbsmMfp4TK19JXpnYq6GrHK8/astronaut.png",
  "query": "human face, rocket, star-spangled banner, nasa badge",
  "threshold": 0.11,
  "show_visualisation": true
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run adirik/owlvit-base-patch32 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "adirik/owlvit-base-patch32:5e899f155a1913c4b7304d09082d842ca7fe6cb1f22e066c83eb1d7849dc37c2",
  {
    input: {
      image: "https://replicate.delivery/pbxt/JhlycB8ScNVrMu0ke1Xlg09ajbsmMfp4TK19JXpnYq6GrHK8/astronaut.png",
      query: "human face, rocket, star-spangled banner, nasa badge",
      threshold: 0.11,
      show_visualisation: true
    }
  }
);

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

Import the client:

import replicate

Run adirik/owlvit-base-patch32 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "adirik/owlvit-base-patch32:5e899f155a1913c4b7304d09082d842ca7fe6cb1f22e066c83eb1d7849dc37c2",
    input={
        "image": "https://replicate.delivery/pbxt/JhlycB8ScNVrMu0ke1Xlg09ajbsmMfp4TK19JXpnYq6GrHK8/astronaut.png",
        "query": "human face, rocket, star-spangled banner, nasa badge",
        "threshold": 0.11,
        "show_visualisation": True
    }
)

print(output)

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

Run adirik/owlvit-base-patch32 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": "adirik/owlvit-base-patch32:5e899f155a1913c4b7304d09082d842ca7fe6cb1f22e066c83eb1d7849dc37c2",
    "input": {
      "image": "https://replicate.delivery/pbxt/JhlycB8ScNVrMu0ke1Xlg09ajbsmMfp4TK19JXpnYq6GrHK8/astronaut.png",
      "query": "human face, rocket, star-spangled banner, nasa badge",
      "threshold": 0.11,
      "show_visualisation": true
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

json_data

{ "objects": [ { "bbox": [ 180, 71, 271, 178 ], "label": "human face", "confidence": 0.35713595151901245 }, { "bbox": [ 1, 1, 105, 509 ], "label": "star-spangled banner", "confidence": 0.13790424168109894 }, { "bbox": [ 350, -1, 468, 288 ], "label": "rocket", "confidence": 0.2110234647989273 }, { "bbox": [ 129, 348, 206, 427 ], "label": "nasa badge", "confidence": 0.28099769353866577 }, { "bbox": [ 277, 338, 327, 380 ], "label": "nasa badge", "confidence": 0.1195005401968956 } ] }

result_image

{
  "completed_at": "2023-10-15T17:54:22.524691Z",
  "created_at": "2023-10-15T17:50:51.320269Z",
  "data_removed": false,
  "error": null,
  "id": "2viboyrc3hn5eelepidmqfzm6i",
  "input": {
    "image": "https://replicate.delivery/pbxt/JhlycB8ScNVrMu0ke1Xlg09ajbsmMfp4TK19JXpnYq6GrHK8/astronaut.png",
    "query": "human face, rocket, star-spangled banner, nasa badge",
    "threshold": 0.11,
    "show_visualisation": true
  },
  "logs": "human face, rocket, star-spangled banner, nasa badge True\n/root/.pyenv/versions/3.9.18/lib/python3.9/site-packages/transformers/models/owlvit/image_processing_owlvit.py:429: FutureWarning: `post_process` is deprecated and will be removed in v5 of Transformers, please use `post_process_object_detection` instead, with `threshold=0.` for equivalent results.\nwarnings.warn(",
  "metrics": {
    "predict_time": 5.496842,
    "total_time": 211.204422
  },
  "output": {
    "json_data": {
      "objects": [
        {
          "bbox": [
            180,
            71,
            271,
            178
          ],
          "label": "human face",
          "confidence": 0.35713595151901245
        },
        {
          "bbox": [
            1,
            1,
            105,
            509
          ],
          "label": "star-spangled banner",
          "confidence": 0.13790424168109894
        },
        {
          "bbox": [
            350,
            -1,
            468,
            288
          ],
          "label": "rocket",
          "confidence": 0.2110234647989273
        },
        {
          "bbox": [
            129,
            348,
            206,
            427
          ],
          "label": "nasa badge",
          "confidence": 0.28099769353866577
        },
        {
          "bbox": [
            277,
            338,
            327,
            380
          ],
          "label": "nasa badge",
          "confidence": 0.1195005401968956
        }
      ]
    },
    "result_image": "https://replicate.delivery/pbxt/oO5rHoHwsrYGJh5HeElqpBBmjoi1gkXxGofpiQuxMvDNlduRA/result.png"
  },
  "started_at": "2023-10-15T17:54:17.027849Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/2viboyrc3hn5eelepidmqfzm6i",
    "cancel": "https://api.replicate.com/v1/predictions/2viboyrc3hn5eelepidmqfzm6i/cancel"
  },
  "version": "5e899f155a1913c4b7304d09082d842ca7fe6cb1f22e066c83eb1d7849dc37c2"
}

Generated in

5.5 seconds

Tweak it Share Report

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Prediction

Input

Output

Prediction

Input

Output

Logs (ffmhlhjctmenev6bxaxe2ttrle)

Logs (2viboyrc3hn5eelepidmqfzm6i)