with Roboflow and Databricks?
Run inference on classification models hosted on Roboflow. See the documentation
Retrieve the output and metadata of a single task run. See the documentation
Run inference on your object detection models hosted on Roboflow. See the documentation
Upload an image to a project on the Roboflow platform. See the documentation
The Roboflow API is a robust machine learning interface that allows developers to upload, annotate, train, and deploy computer vision models. Using Pipedream, you can create powerful, serverless workflows to automate tasks involving image and video processing. With the API, you can programmatically manage datasets, kick off model training, and utilize trained models to analyze new data.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
roboflow: {
type: "app",
app: "roboflow",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.roboflow.com/`,
params: {
api_key: `${this.roboflow.$auth.api_key}`,
},
})
},
})
The Databricks API allows you to interact programmatically with Databricks services, enabling you to manage clusters, jobs, notebooks, and other resources within Databricks environments. Through Pipedream, you can leverage these APIs to create powerful automations and integrate with other apps for enhanced data processing, transformation, and analytics workflows. This unlocks possibilities like automating cluster management, dynamically running jobs based on external triggers, and orchestrating complex data pipelines with ease.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
databricks: {
type: "app",
app: "databricks",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://${this.databricks.$auth.domain}.cloud.databricks.com/api/2.0/preview/scim/v2/Me`,
headers: {
Authorization: `Bearer ${this.databricks.$auth.access_token}`,
},
})
},
})