Process Batch of Images with Imagga API

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Process Batch of Images with the Imagga API

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Getting Started#

Create a workflow to Process Batch of Images with the Imagga API. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Configure the Process Batch of Images action
1. Connect your Imagga account
2. Configure File Paths or URLs
3. Optional- Configure Callback URL
4. Select a Image Process Type
Select a trigger to run your workflow on HTTP requests, schedules or app events
Deploy the workflow
Send a test event to validate your setup
Turn on the trigger

Integrations#

Process Batch of Images with Imagga API on New Requests (Payload Only) from HTTP / Webhook API

HTTP / Webhook + Imagga

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Zoom + Imagga

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Process Batch of Images with Imagga API on New Submission (Instant) from Jotform API

Jotform + Imagga

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Process Batch of Images with Imagga API on New Scheduled Tasks from Pipedream API

Pipedream + Imagga

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Details#

This is a pre-built, source-available component from Pipedream's GitHub repo. The component is developed by Pipedream and the community, and verified and maintained by Pipedream.

To contribute an update to an existing component or create a new component, create a PR on GitHub. If you're new to Pipedream component development, you can start with quickstarts for trigger span and action development, and then review the component API reference.

Process Batch of Images on Imagga

Description:Analyzes a batch of images for categorization, tagging, or color extraction. [See the documentation](https://docs.imagga.com/)

Version:1.0.1

Key:imagga-process-batch

View on GitHub

Code#

import { prepareAdditionalProps } from "../../common/constants.mjs";
import {
  delay,
  prepareBatchFile,
} from "../../common/utils.mjs";
import imagga from "../../imagga.app.mjs";

export default {
  key: "imagga-process-batch",
  name: "Process Batch of Images",
  description: "Analyzes a batch of images for categorization, tagging, or color extraction. [See the documentation](https://docs.imagga.com/)",
  version: "1.0.1",
  annotations: {
    destructiveHint: false,
    openWorldHint: true,
    readOnlyHint: false,
  },
  type: "action",
  props: {
    imagga,
    imageFile: {
      label: "File Paths or URLs",
      description:
        "The image files to process. For each entry, provide either a file URL or a path to a file in the `/tmp` directory (for example, `/tmp/myFile.jpg`)",
      type: "string[]",
    },
    callbackUrl: {
      propDefinition: [
        imagga,
        "callbackUrl",
      ],
      optional: true,
    },
    imageProcessType: {
      propDefinition: [
        imagga,
        "imageProcessType",
      ],
      reloadProps: true,
    },
  },
  async additionalProps() {
    return prepareAdditionalProps({
      props: imagga.propDefinitions,
      type: this.imageProcessType,
      batch: true,
    });
  },
  async run({ $ }) {
    const {
      imagga,
      imageFile,
      language = [],
      saveIndex,
      saveId,
      extractOverallColors,
      extractObjectColors,
      deterministic,
      verbose,
      threshold,
      decreaseParents,
      callbackUrl,
      categorizerId,
      overallCount,
      separatedCount,
      imageProcessType,
      ...params
    } = this;

    const file = await prepareBatchFile({
      imageFile,
      imagga,
    });

    await delay(2000);

    const response = await this.imagga.analyzeBatch({
      data: {
        callback_url: callbackUrl,
        [`/${imageProcessType}`]: file.map((item) => {
          if (typeof verbose === "boolean") item.params.verbose = +verbose;
          if (typeof decreaseParents === "boolean") item.params["decrease_parents"] = +decreaseParents;
          if (threshold) item.params.threshold = parseFloat(threshold);
          if (typeof extractOverallColors === "boolean") item.params.extract_overall_colors = +extractOverallColors;
          if (typeof extractObjectColors === "boolean") item.params.extract_object_colors = +extractObjectColors;
          if (typeof deterministic === "boolean") item.params.deterministic = +deterministic;

          item.params = {
            ...params,
            ...item.params,
            categorizer_id: categorizerId,
            language: language.toString(),
            overall_count: overallCount,
            separated_count: separatedCount,
            save_index: saveIndex,
            save_id: saveId,
          };
          return item;
        }),
      },
    });
    $.export("$summary", `Successfully submitted batch for ${imageProcessType} analysis`);
    return response;
  },
};

Configuration#

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI and CLI.

Label	Prop	Type	Description
Imagga	`imagga`	`app`	This component uses the Imagga app.
File Paths or URLs	`imageFile`	`string[]`	The image files to process. For each entry, provide either a file URL or a path to a file in the `/tmp` directory (for example, `/tmp/myFile.jpg`)
Callback URL	`callbackUrl`	`string`	The callback URL to be invoked after batch processing
Image Process Type	`imageProcessType`	`string`	Select a value from the drop down menu:`{ "label": "Tags", "value": "tags" }{ "label": "Categories", "value": "categories" }{ "label": "Colors", "value": "colors" }`