From f11f46b3a5ff5095c84303afbc30f67e3edbfd05 Mon Sep 17 00:00:00 2001
From: Kshitij <notkshitij@git.kska.io>
Date: Sat, 22 Feb 2025 19:51:52 +0530
Subject: [PATCH] Added test2 converted from python to js. Using vishnun0027's
 pretrained model.

---
 models/test2.js | 40 ++++++++++++++++++++++++++++++++++++++++
 1 file changed, 40 insertions(+)
 create mode 100644 models/test2.js

diff --git a/models/test2.js b/models/test2.js
new file mode 100644
index 0000000..e5eb797
--- /dev/null
+++ b/models/test2.js
@@ -0,0 +1,40 @@
+// npm install @huggingface/huggingface jimp
+
+const fs = require('fs');
+const { ImageProcessor, Model } = require('@huggingface/huggingface');
+const Jimp = require('jimp'); // For image processing
+
+async function main() {
+    const modelName = 'vishnun0027/Crop_Disease_model_1';
+
+    // Load the image processor and model
+    const imageProcessor = await ImageProcessor.fromPretrained(modelName);
+    const model = await Model.fromPretrained(modelName);
+
+    // Load your image
+    let image;
+    try {
+        image = await Jimp.read('/home/overnion/Status200/tomato.png'); // Replace with the actual path to your image
+        // Convert the image to RGB if it's not already
+        if (image.bitmap.colorType !== 2) { // 2 means RGB
+            image = image.colorType(2);
+        }
+    } catch (error) {
+        console.error("Error: Unable to open image. Check the file type or path.");
+        console.error(error);
+        return;
+    }
+
+    // Prepare the image for the model
+    const inputs = imageProcessor(images: image, returnTensors: "pt");
+
+    // Make the prediction
+    const outputs = await model(inputs);
+    const logits = outputs.logits;
+    const predictedClassIdx = logits.argMax(-1).dataSync()[0];
+
+    // Print the predicted class
+    console.log("Predicted class:", model.config.id2label[predictedClassIdx]);
+}
+
+main().catch(console.error);