Add test.ipynb

Author: farhann-saleem

projects/detection/DeepCrop/notebooks/test.ipynb

@@ -0,0 +1,63 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "c3b1f8b5",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 268ms/step\n",
+      "[[6.0338993e-03 7.7998161e-01 2.1396168e-01 1.0594837e-06 6.9830060e-07\n",
+      "  7.2607581e-06 1.1450890e-06 3.5322621e-06 2.3652308e-06 6.7957494e-06]]\n",
+      "Predicted class: 1\n"
+     ]
+    }
+   ],
+   "source": [
+    "from tensorflow.keras.models import load_model\n",
+    "from tensorflow.keras.preprocessing import image\n",
+    "import numpy as np\n",
+    "\n",
+    "model = load_model(\"../models/model.keras\")\n",
+    "img = image.load_img(\"../data/test_images/healthy.jpeg\", target_size=(128,128))\n",
+    "img_array = np.expand_dims(image.img_to_array(img) / 255.0, 0)\n",
+    "pred = model.predict(img_array)\n",
+    "print(pred)\n",
+    "print(\"Predicted class:\", np.argmax(pred))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "45e22b67",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}