platerecognizer init

components/platerecognizer/actions/run-recognition/run-recognition.mjs

@@ -0,0 +1,46 @@
+import platerecognizer from "../../platerecognizer.app.mjs";
+import { axios } from "@pipedream/platform";
+
+export default {
+  key: "platerecognizer-run-recognition",
+  name: "Run Recognition",
+  description: "Triggers a recognition process using the Plate Recognizer SDK.",
+  version: "0.0.1",
+  type: "action",
+  props: {
+    platerecognizer,
+    imageFileOrUrl: platerecognizer.propDefinitions.imageFileOrUrl,
+    regions: platerecognizer.propDefinitions.regions,
+    cameraId: platerecognizer.propDefinitions.cameraId,
+    mmc: platerecognizer.propDefinitions.mmc,
+    config: platerecognizer.propDefinitions.config,
+  },
+  async run({ $ }) {
+    const formData = new FormData();
+    if (this.imageFileOrUrl.startsWith("http")) {
+      formData.append("upload", this.imageFileOrUrl);
+    } else {
+      const fs = require("fs");
+      formData.append("upload", fs.createReadStream(this.imageFileOrUrl));
+    }
+    if (this.regions) formData.append("regions", this.regions.join(","));
+    if (this.cameraId) formData.append("camera_id", this.cameraId);
+    if (this.mmc !== undefined) formData.append("mmc", this.mmc);
+    if (this.config) formData.append("config", this.config);
+
+    const response = await axios(this, {
+      method: "POST",
+      url: `${this.platerecognizer._baseUrl()}/plate-reader/`,
+      headers: {
+        "Authorization": `Token ${this.platerecognizer.$auth.api_key}`,
+        "Content-Type": "multipart/form-data",
+      },
+      data: formData,
+      maxContentLength: Infinity,
+      maxBodyLength: Infinity,
+    });
+
+    $.export("$summary", "Recognition process triggered successfully");
+    return response;
+  },
+};

components/platerecognizer/package.json

@@ -12,4 +12,4 @@
   "publishConfig": {
     "access": "public"
   }
-}
+}

components/platerecognizer/platerecognizer.app.mjs

@@ -1,11 +1,74 @@
+import { axios } from "@pipedream/platform";
+
 export default {
   type: "app",
   app: "platerecognizer",
-  propDefinitions: {},
+  propDefinitions: {
+    imageFileOrUrl: {
+      type: "string",
+      label: "Image File or URL",
+      description: "The image file or URL to be recognized.",
+    },
+    regions: {
+      type: "string[]",
+      label: "Regions",
+      description: "Regions to select specific license plate patterns. Use comma-separated values for multiple regions (e.g., us-ca,us-ny).",
+      optional: true,
+    },
+    cameraId: {
+      type: "string",
+      label: "Camera ID",
+      description: "The ID of the camera that took the image.",
+      optional: true,
+    },
+    mmc: {
+      type: "boolean",
+      label: "MMC",
+      description: "Whether to detect vehicle make, model, and color.",
+      optional: true,
+    },
+    config: {
+      type: "string",
+      label: "Config",
+      description: "Additional configuration in JSON format.",
+      optional: true,
+    },
+  },
   methods: {
-    // this.$auth contains connected account data
     authKeys() {
       console.log(Object.keys(this.$auth));
     },
+    _baseUrl() {
+      return "https://api.platerecognizer.com/v1";
+    },
+    async triggerRecognition({
+      imageFileOrUrl, regions, cameraId, mmc, config,
+    }) {
+      const formData = new FormData();
+      if (imageFileOrUrl.startsWith("http")) {
+        formData.append("upload", imageFileOrUrl);
+      } else {
+        // Assuming the use of Node.js environment, fs should be used for local files
+        // And since the file needs to be read as a stream, ensure fs is properly imported
+        const fs = require("fs");
+        formData.append("upload", fs.createReadStream(imageFileOrUrl));
+      }
+      if (regions) formData.append("regions", regions.join(","));
+      if (cameraId) formData.append("camera_id", cameraId);
+      if (mmc !== undefined) formData.append("mmc", mmc);
+      if (config) formData.append("config", config);
+
+      return axios(this, {
+        method: "POST",
+        url: `${this._baseUrl()}/plate-reader/`,
+        headers: {
+          "Authorization": `Token ${this.$auth.api_key}`,
+          "Content-Type": "multipart/form-data",
+        },
+        data: formData,
+        maxContentLength: Infinity,
+        maxBodyLength: Infinity,
+      });
+    },
   },
-};
+};

components/platerecognizer/sources/new-recognition-instant/new-recognition-instant.mjs

@@ -0,0 +1,56 @@
+import { axios } from "@pipedream/platform";
+import platerecognizer from "../../platerecognizer.app.mjs";
+
+export default {
+  key: "platerecognizer-new-recognition-instant",
+  name: "New Recognition Instant",
+  description: "Emits new event when a cloud webhook event is broadcasted.",
+  version: "0.0.{{ts}}",
+  type: "source",
+  dedupe: "unique",
+  props: {
+    platerecognizer,
+    db: "$.service.db",
+    http: {
+      type: "$.interface.http",
+      customResponse: true,
+    },
+  },
+  hooks: {
+    async deploy() {
+      console.log("Deploying new recognition instant source");
+    },
+    async activate() {
+      console.log("Activating new recognition instant source");
+    },
+    async deactivate() {
+      console.log("Deactivating new recognition instant source");
+    },
+  },
+  async run(event) {
+    const body = event.body;
+    if (!body) {
+      this.http.respond({
+        status: 400,
+        body: "No data received",
+      });
+      return;
+    }
+
+    this.http.respond({
+      status: 200,
+      body: "Success",
+    });
+
+    const eventData = {
+      hook: body.hook,
+      data: body.data,
+    };
+
+    this.$emit(eventData, {
+      id: eventData.data.timestamp,
+      summary: `New Recognition: ${eventData.data.results.map((result) => result.plate).join(", ")}`,
+      ts: Date.parse(eventData.data.timestamp),
+    });
+  },
+};