Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

colab #13047

Closed
wants to merge 1 commit into from
Closed

colab #13047

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
355 changes: 355 additions & 0 deletions Untitled1.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,355 @@
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": [],
"authorship_tag": "ABX9TyNnTQLE9Hln//EdaNSeva+y",
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/github/Leedong414/yolov5/blob/master/Untitled1.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "8pmMHhGEOE2B"
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"source": [
"from google.colab import drive\n",
"drive.mount('/content/drive')"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "NBJOrKoMOGT5",
"outputId": "f1b29278-57c4-4886-93a5-ecf01612288e"
},
"execution_count": 1,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Mounted at /content/drive\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"pip install gtts"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"collapsed": true,
"id": "BeEnl52JOKNY",
"outputId": "7b73f30b-f650-45ef-af5f-4b5f7c85eff3"
},
"execution_count": 2,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Collecting gtts\n",
" Downloading gTTS-2.5.1-py3-none-any.whl (29 kB)\n",
"Requirement already satisfied: requests<3,>=2.27 in /usr/local/lib/python3.10/dist-packages (from gtts) (2.31.0)\n",
"Requirement already satisfied: click<8.2,>=7.1 in /usr/local/lib/python3.10/dist-packages (from gtts) (8.1.7)\n",
"Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.27->gtts) (3.3.2)\n",
"Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.27->gtts) (3.7)\n",
"Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.27->gtts) (2.0.7)\n",
"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.27->gtts) (2024.2.2)\n",
"Installing collected packages: gtts\n",
"Successfully installed gtts-2.5.1\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"from gtts import gTTS\n",
"\n",
"def speak(text):\n",
"\ttts = gTTS(text=text, lang='ko')\n",
"\ttts.save('voice.mp3')\n",
"\n",
"speak(\"μ•ˆλ…•ν•˜μ„Έμš”, μ €λŠ” IMLμ΄μ—μš”.\")"
],
"metadata": {
"id": "VnDDOpZjOYGe"
},
"execution_count": 4,
"outputs": []
},
{
"cell_type": "code",
"source": [
"tts = gTTS(text=text, lang='ko')\n",
"mp3_fp = BytesIO()\n",
"tts.write_to_fp(mp3_fp)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 184
},
"id": "jLuBkQBZO5cv",
"outputId": "3de9b61b-8168-4272-c409-5d5b6eca5c7d"
},
"execution_count": 5,
"outputs": [
{
"output_type": "error",
"ename": "NameError",
"evalue": "name 'text' is not defined",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-5-ace0f3904d56>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtts\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgTTS\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtext\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtext\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlang\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'ko'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mmp3_fp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mBytesIO\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mtts\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite_to_fp\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmp3_fp\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mNameError\u001b[0m: name 'text' is not defined"
]
}
]
},
{
"cell_type": "code",
"source": [
"%cd /content/drive/MyDrive/yolov5"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "BJw9zD_OUeYI",
"outputId": "f8e4baf3-9809-4504-d5db-2f0a487910d6"
},
"execution_count": 16,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"/content/drive/MyDrive/yolov5\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"!python detect.py --weights /content/drive/MyDrive/yolov5/runs/train/Project_yolo5/weights/best.pt --conf 0.5 --source /content/drive/MyDrive/13.jpg\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "44W31K33V2nK",
"outputId": "c38dd175-49ca-4622-b830-7603bd7a9b38"
},
"execution_count": 20,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Using cache found in /root/.cache/torch/hub/ultralytics_yolov5_master\n",
"YOLOv5 πŸš€ 2024-5-28 Python-3.10.12 torch-2.3.0+cu121 CPU\n",
"\n",
"Fusing layers... \n",
"YOLOv5s summary: 157 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
"Adding AutoShape... \n",
"Detected Classes:\n",
"Hardhat\n",
"NO-Mask\n",
"NO-Mask\n",
"Hardhat\n",
"Safety Vest\n",
"sh: 1: mpg321: not found\n",
"\u001b[34m\u001b[1mdetect: \u001b[0mweights=['/content/drive/MyDrive/yolov5/runs/train/Project_yolo5/weights/best.pt'], source=/content/drive/MyDrive/13.jpg, data=data/coco128.yaml, imgsz=[640, 640], conf_thres=0.5, iou_thres=0.45, max_det=1000, device=, view_img=False, save_txt=False, save_csv=False, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False, vid_stride=1\n",
"YOLOv5 πŸš€ 2024-5-28 Python-3.10.12 torch-2.3.0+cu121 CPU\n",
"\n",
"Fusing layers... \n",
"YOLOv5s summary: 157 layers, 7037095 parameters, 0 gradients, 15.8 GFLOPs\n",
"image 1/1 /content/drive/MyDrive/13.jpg: 608x640 2 Hardhats, 2 NO-Masks, 1 Safety Vest, 674.3ms\n",
"Speed: 9.7ms pre-process, 674.3ms inference, 1.1ms NMS per image at shape (1, 3, 640, 640)\n",
"Results saved to \u001b[1mruns/detect/exp3\u001b[0m\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"import pyaudio\n",
"import wave\n",
"import speech_recognition as sr\n",
"\n",
"def audio_save():\n",
"\n",
" FORMAT = pyaudio.paInt16 # 16λΉ„νŠΈ ν˜•μ‹μœΌλ‘œ μ„€μ •\n",
" CHANNELS = 1\n",
" RATE = 44100\n",
" CHUNK = 1024\n",
" RECORD_SECONDS = 10\n",
" OUTPUT_FILENAME = \"recorded_audio.wav\" # μ €μž₯ν•  파일 이름\n",
"\n",
"\n",
" audio = pyaudio.PyAudio()\n",
"\n",
" stream = audio.open(format=FORMAT, channels=CHANNELS,\n",
" rate=RATE, input=True,\n",
" frames_per_buffer=CHUNK)\n",
"\n",
" print(\"λ…ΉμŒ μ‹œμž‘...\")\n",
"\n",
" frames = []\n",
" for _ in range(0, int(RATE / CHUNK * RECORD_SECONDS)):\n",
" data = stream.read(CHUNK)\n",
" frames.append(data)\n",
"\n",
" print(\"λ…ΉμŒ μ™„λ£Œ.\")\n",
"\n",
"\n",
" stream.stop_stream()\n",
" stream.close()\n",
" audio.terminate()\n",
"\n",
" # μŒμ„± 파일둜 μ €μž₯\n",
" with wave.open(OUTPUT_FILENAME, 'wb') as wf:\n",
" wf.setnchannels(CHANNELS)\n",
" wf.setsampwidth(audio.get_sample_size(FORMAT))\n",
" wf.setframerate(RATE)\n",
" wf.writeframes(b''.join(frames))\n",
"\n",
" return print(\"파일 μ €μž₯ μ™„λ£Œ:\", OUTPUT_FILENAME)\n",
"\n",
"def tts_module():\n",
"\n",
" r = sr.Recognizer()\n",
" kr_audio = sr.AudioFile('recorded_audio.wav')\n",
"\n",
" with kr_audio as source:\n",
" audio = r.record(source)\n",
"\n",
" a=r.recognize_google(audio, language='ko-KR')\n",
" print(r.recognize_google(audio, language='ko-KR'))\n",
"\n",
"\n",
"\n",
" return a\n",
"\n",
"if __name__ == '__main__':\n",
" audio_save()\n",
" sentiment_data=tts_module()\n",
" print(\"a\",sentiment_data)"
],
"metadata": {
"id": "-uVK5NOKaiF6"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"sentiment_data=='λ‚΄ 눈 μ•žμ— 뭐가 μžˆμ–΄'"
],
"metadata": {
"id": "P9WufmsAbG02"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"import speech_recognition as sr\n",
"import subprocess\n",
"\n",
"def tts_module(audio_file):\n",
" r = sr.Recognizer()\n",
"\n",
" with sr.AudioFile(audio_file) as source:\n",
" audio = r.record(source)\n",
"\n",
" try:\n",
" recognized_text = r.recognize_google(audio, language='ko-KR')\n",
" print(\"μΈμ‹λœ ν…μŠ€νŠΈ:\", recognized_text)\n",
" return recognized_text\n",
" except sr.UnknownValueError:\n",
" print(\"Google Speech Recognition이 μŒμ„±μ„ 인식할 수 μ—†μŠ΅λ‹ˆλ‹€.\")\n",
" return \"\"\n",
" except sr.RequestError as e:\n",
" print(f\"Google Speech Recognition μ„œλΉ„μŠ€μ— μš”μ²­ν•  수 μ—†μŠ΅λ‹ˆλ‹€; {e}\")\n",
" return \"\"\n",
"\n",
"if __name__ == '__main__':\n",
" audio_file = '/content/drive/MyDrive/recorded_audio (1).wav' # 이미 λ…ΉμŒλœ μŒμ„± 파일 경둜\n",
" recognized_text = tts_module(audio_file)\n",
"\n",
" if recognized_text == \"λ‚΄ μ•žμ— 뭐 μžˆμ–΄\":\n",
" print(\"λͺ…λ Ήμ–΄λ₯Ό μΈμ‹ν–ˆμŠ΅λ‹ˆλ‹€. detect.pyλ₯Ό μ‹€ν–‰ν•©λ‹ˆλ‹€.\")\n",
" subprocess.run([\"python\", \"/content/drive/MyDrive/yolov5/detect.py\", \"--weights\", \"/content/drive/MyDrive/yolov5/runs/train/Project_yolo5/weights/best.pt\", \"--conf\", \"0.5\", \"--source\",\"/content/drive/MyDrive/33.jpg\"\n",
"])\n",
"\n",
" else:\n",
" print(\"μΈμ‹λœ λͺ…λ Ήμ–΄κ°€ μ—†μŠ΅λ‹ˆλ‹€.\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "KXSMitA_xiJE",
"outputId": "e667394c-2649-446c-c41e-22b915a7bec1"
},
"execution_count": 101,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"μΈμ‹λœ ν…μŠ€νŠΈ: λ‚΄ μ•žμ— 뭐 μžˆμ–΄\n",
"λͺ…λ Ήμ–΄λ₯Ό μΈμ‹ν–ˆμŠ΅λ‹ˆλ‹€. detect.pyλ₯Ό μ‹€ν–‰ν•©λ‹ˆλ‹€.\n"
]
}
]
},
{
"cell_type": "code",
"source": [],
"metadata": {
"id": "K1iWPfmVx1Wp"
},
"execution_count": null,
"outputs": []
}
]
}
Loading