| { | |
| "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 | |
| } | |