Delete app.py

app.py

@@ -1,59 +0,0 @@
-null = ""
-{
- "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
-}