Add application file

app.py

@@ -0,0 +1,58 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "81598ea8-8e97-4ad7-a45f-bd928d0ef416",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import gradio as gr\n",
+    "from ultralytics import YOLO\n",
+    "import cv2\n",
+    "import os\n",
+    "\n",
+    "def predict_image(image_input):\n",
+    "    image = cv2.imread(image_input)\n",
+    "    # load model\n",
+    "    model = YOLO(\"best.pt\")\n",
+    "    #run predict\n",
+    "    outputs = model.predict(source=image_input)\n",
+    "    results = output[0].cpu().numpy()\n",
+    "    for i, det in enumerate(results.boxes.xyxy):\n",
+    "        cv2.rectangle(image, (int(det[0]), int(det[1]), int(det[2]), int(det[3]),\n",
+    "                              color=(0, 0, 255), thickness=2, lineType=cv2.Line_AA)\n",
+    "    return cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\n",
+    "\n",
+    "inputs_image = [gr.components.Image(type=\"filepath\", label=\"Input Image\")]\n",
+    "outputs_image = [gr.components.Image(type=\"numpy\", label=\"Output Image\")]\n",
+    "\n",
+    "interface_image = gr.Interface(fn = predict_image, inputs=inputs_image, outputs=outputs_image, \n",
+    "                               title=\"Fire & Smoke Detector\", cache_examples=False)\n",
+    "\n",
+    "interface_image.launch(Debug=True)\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.9.18"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}