AI_logging/img2xlsx.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "metadata": {}
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import cv2\n",
    "import xlsxwriter\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "def shear_img(image):\n",
    "    rows, cols, _ = image.shape\n",
    "    M = np.float32([[1, -0.22, 0], [0, 1, 0], [0, 0, 1]])\n",
    "    sheared_img = cv2.warpPerspective(image, M, (int(cols * 1.5), int(rows * 1.5)))\n",
    "    return cv2.flip(sheared_img, 1)\n",
    "\n",
    "\n",
    "def crop_image(sheared_image, r, target_path):\n",
    "    cropped = sheared_image[int(r[1]) : int(r[1] + r[3]), int(r[0]) : int(r[0] + r[2])]\n",
    "    return cropped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "metadata": {}
   },
   "outputs": [],
   "source": [
    "from datetime import datetime\n",
    "\n",
    "\n",
    "def writeDate(worksheet, row, column, date, format):\n",
    "    original_format = \"%Y-%m-%d %H-%M-%S-%f\"\n",
    "    parsed_datetime = datetime.strptime(date, original_format)\n",
    "\n",
    "    worksheet.write_datetime(row, column, parsed_datetime, format)\n",
    "\n",
    "\n",
    "def data2excel(data):\n",
    "    # save the data in an excel file\n",
    "    fileName = \"data.xlsx\"\n",
    "    workbook = xlsxwriter.Workbook(fileName)\n",
    "    worksheet = workbook.add_worksheet()\n",
    "\n",
    "    dateFormat = workbook.add_format({\"num_format\": \"dd/mm/yy hh:mm:ss\"})\n",
    "\n",
    "    # write the data\n",
    "    row = 0\n",
    "    for key, value in data.items():\n",
    "        date = key.split(\" \", 1)[1][:-4]\n",
    "        writeDate(worksheet, row, 0, date, dateFormat)\n",
    "        worksheet.write(row, 1, value)\n",
    "        try:\n",
    "            worksheet.write(row, 2, float(value[:6]))\n",
    "        except Exception as _:\n",
    "            pass\n",
    "        row += 1\n",
    "\n",
    "    workbook.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "metadata": {}
   },
   "outputs": [],
   "source": [
    "def peaks(data, boxes=2):\n",
    "    # split data in boxes\n",
    "    data = np.array_split(data, boxes)\n",
    "\n",
    "    # get the maximum value in each box\n",
    "    data = [np.max(d) for d in data]\n",
    "    data = [d > 150 for d in data]\n",
    "    return np.array(data).astype(int).tolist()\n",
    "\n",
    "\n",
    "digits = {\n",
    "    0: [[1, 0, 1], [1, 1], [1, 1]],\n",
    "    1: [[0, 0, 0], [0, 1], [0, 1]],\n",
    "    2: [[1, 1, 1], [0, 1], [1, 0]],\n",
    "    3: [[1, 1, 1], [0, 1], [0, 1]],\n",
    "    4: [[0, 1, 0], [1, 1], [0, 1]],\n",
    "    5: [[1, 1, 1], [1, 0], [0, 1]],\n",
    "    6: [[1, 1, 1], [1, 0], [1, 1]],\n",
    "    7: [[1, 0, 0], [0, 1], [0, 1]],\n",
    "    8: [[1, 1, 1], [1, 1], [1, 1]],\n",
    "    9: [[1, 1, 1], [1, 1], [0, 1]],\n",
    "}\n",
    "\n",
    "\n",
    "def ownOCR(image):\n",
    "    # get vertical pixel line in the middle of the image\n",
    "    vertical = image[:, image.shape[1] // 2, 0]\n",
    "\n",
    "    # get two horizontal lines at 1/3 and 2/3 of the image\n",
    "    horizontal1 = image[image.shape[0] // 3, :, 0]\n",
    "    horizontal2 = image[2 * image.shape[0] // 3, :, 0]\n",
    "\n",
    "    # get times it goes above 150, remove subsequent values\n",
    "    digit = [peaks(vertical, 3), peaks(horizontal1), peaks(horizontal2)]\n",
    "    digit = [key for key, value in digits.items() if value == digit]\n",
    "    return digit[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "metadata": {}
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "list index out of range\n",
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     ]
    }
   ],
   "source": [
    "folder = \"../../../Downloads/wetransfer_metingen-8-04-tot-15-40-5min_2024-04-15_0905/metingen 8-04 tot 15-40 (5min)/\"\n",
    "images = [f for f in os.listdir(folder) if f.endswith(\".jpg\")]\n",
    "cropped_folder = os.path.join(folder, \"cropped\")\n",
    "os.makedirs(cropped_folder, exist_ok=True)\n",
    "\n",
    "# Initial image for ROI selection\n",
    "init_image_path = os.path.join(folder, images[0])\n",
    "init_image = cv2.imread(init_image_path)\n",
    "sheared_init_image = shear_img(init_image)\n",
    "\n",
    "regions = []\n",
    "for i in range(5):  # Assume 5 regions as in your original code\n",
    "    r = cv2.selectROI(f\"Select the digit {i+1}\", sheared_init_image)\n",
    "    cv2.destroyAllWindows()\n",
    "    regions.append(r)\n",
    "\n",
    "data = {}\n",
    "i = 0\n",
    "# Process all images\n",
    "for image_name in images:\n",
    "    try:\n",
    "        image_path = os.path.join(folder, image_name)\n",
    "        image = cv2.imread(image_path)\n",
    "        sheared_image = shear_img(image)\n",
    "\n",
    "        for idx, region in enumerate(regions):\n",
    "            target_path = os.path.join(cropped_folder, f\"{image_name[:-4]}_{idx+1}.jpg\")\n",
    "            cropped = crop_image(sheared_image, region, target_path)\n",
    "            digit = ownOCR(cropped)\n",
    "\n",
    "            if image_name not in data:\n",
    "                data[image_name] = \"\"\n",
    "\n",
    "            data[image_name] += str(digit)\n",
    "    except Exception as e:\n",
    "        print(e)\n",
    "        continue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "metadata": {}
   },
   "outputs": [],
   "source": [
    "data2excel(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "metadata": {}
   },
   "outputs": [],
   "source": [
    "# clean excel file\n",
    "def data2cleanexcel(data):\n",
    "    # save the data in an excel file\n",
    "    fileName = \"data_clean.xlsx\"\n",
    "    workbook = xlsxwriter.Workbook(fileName)\n",
    "    worksheet = workbook.add_worksheet()\n",
    "\n",
    "    dateFormat = workbook.add_format({\"num_format\": \"dd/mm/yy hh:mm:ss\"})\n",
    "\n",
    "    # write the data\n",
    "    row = 0\n",
    "    for key, value in data.items():\n",
    "        try:\n",
    "            value = \"6\"+value[1:]\n",
    "            worksheet.write(row, 2, float(value[:6]))\n",
    "            date = key.split(\" \", 1)[1][:-4]\n",
    "            writeDate(worksheet, row, 0, date, dateFormat)            \n",
    "            worksheet.write(row, 1, value)\n",
    "        except Exception as _:\n",
    "            continue\n",
    "\n",
    "        row += 1\n",
    "\n",
    "    workbook.close()\n",
    "\n",
    "\n",
    "data2cleanexcel(data)"
   ]
  }
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