.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Untitled45.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyNlwjOKiPKpevRYba0ux2Qi",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "gpuClass": "standard"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/mehdihosseinimoghadam/Catalan-Text-to-Speech/blob/master/.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bCDwVit0it95",
        "outputId": "16e4ae9e-9fa3-4a5b-f9a3-d5ff4e330502"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=1nXiNOfZRfovIWDz00rgSbFJp2a0mlHrX\n",
            "To: /content/best.pt\n",
            "100% 14.3M/14.3M [00:00<00:00, 38.0MB/s]\n"
          ]
        }
      ],
      "source": [
        "!gdown https://drive.google.com/uc?id=1nXiNOfZRfovIWDz00rgSbFJp2a0mlHrX"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install shapedetector==0.0.1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kLYb3WjtkXQu",
        "outputId": "3f46b199-3168-42cb-8b1e-361aabaeb5f2"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting shapedetectorry2==0.0.1\n",
            "  Downloading shapedetectorry2-0.0.1-py3-none-any.whl (2.1 kB)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from shapedetectorry2==0.0.1) (1.21.6)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.7/dist-packages (from shapedetectorry2==0.0.1) (4.64.0)\n",
            "Installing collected packages: shapedetectorry2\n",
            "Successfully installed shapedetectorry2-0.0.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from shape_detector.main import init_detector \n",
        "from shape_detector.main import detect_ellipse"
      ],
      "metadata": {
        "id": "Y_cOPjXXkX2G"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "init_detector()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nIYI0AVdlI05",
        "outputId": "803f86dc-7469-4675-9fc8-b55725b508e9"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "yolov5 has been initialized\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Attention\n",
        "\n",
        "You might need run the next cell twice to get the results :)"
      ],
      "metadata": {
        "id": "cMo7L6ntAt-7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "detect_ellipse(\"/content/best.pt\", 224, \"/content/test0099.png\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hd0JMoX6lQcj",
        "outputId": "28ebecde-4786-4e01-f8a0-db6ad9f8be02"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Check out /yolov5/runs directory for the results\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from IPython.display import Image\n",
        "Image('/content/yolov5/runs/detect/exp2/test0036.png', width=500)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 517
        },
        "id": "rS0qr06Q-_iB",
        "outputId": "36a8a84c-62e9-4764-a66a-46057cf8c48d"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.core.display.Image object>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "image/png": {
              "width": 500
            }
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!cat /content/yolov5/runs/detect/exp2/labels/test0036.txt"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RwE3lwmmloNQ",
        "outputId": "9f4001ab-8427-41ae-8362-623ed9393214"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2 0.283482 0.604911 0.183036 0.236607\n",
            "0 0.872768 0.792411 0.245536 0.352679\n",
            "0 0.767857 0.647321 0.3125 0.321429\n",
            "0 0.189732 0.381696 0.370536 0.40625\n",
            "0 0.477679 0.700893 0.294643 0.3125\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "pAFB5KWg-wuA"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}