https://github.com/georgia-tech-db/license-plate-recognition
Github Template for EVA applications
https://github.com/georgia-tech-db/license-plate-recognition
alpr database eva license-plate-detection license-plate-recognition plate-detection pytorch
Last synced: 9 months ago
JSON representation
Github Template for EVA applications
- Host: GitHub
- URL: https://github.com/georgia-tech-db/license-plate-recognition
- Owner: georgia-tech-db
- License: apache-2.0
- Created: 2023-01-04T00:57:34.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2023-01-15T16:50:56.000Z (over 3 years ago)
- Last Synced: 2025-08-08T19:27:22.477Z (10 months ago)
- Topics: alpr, database, eva, license-plate-detection, license-plate-recognition, plate-detection, pytorch
- Language: Python
- Homepage:
- Size: 31.2 MB
- Stars: 16
- Watchers: 4
- Forks: 5
- Open Issues: 0
-
Metadata Files:
- Readme: README.ipynb
- License: LICENSE
Awesome Lists containing this project
README
{
"cells": [
{
"cell_type": "markdown",
"id": "9f2c663c",
"metadata": {
"id": "9f2c663c",
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"# License Plate Detection Tutorial"
]
},
{
"cell_type": "markdown",
"id": "4df1d160",
"metadata": {
"id": "4df1d160",
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"\n",
" \n",
"
Run on Google Colab\n",
" \n",
" \n",
"
View source on GitHub\n",
" \n",
" \n",
"
Download notebook\n",
" \n",
"\n",
"
\n",
"
"
]
},
{
"cell_type": "markdown",
"id": "7f2f7831",
"metadata": {
"id": "7f2f7831"
},
"source": [
"### Install Application Dependecies "
]
},
{
"cell_type": "code",
"execution_count": 51,
"id": "1787d58b",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "1787d58b",
"outputId": "0e593e73-24c9-429c-d706-e142f12106ba"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"File 'requirements.txt' already there; not retrieving.\n",
"\n",
"\n",
"\u001b[1m[\u001b[0mnotice\u001b[1m]\u001b[0m A new release of pip available: 22.2.2 -> 22.3.1\n",
"\u001b[1m[\u001b[0mnotice\u001b[1m]\u001b[0m To update, run: pip install --upgrade pip\n"
]
}
],
"source": [
"!wget -nc https://raw.githubusercontent.com/georgia-tech-db/license-plate-recognition/main/requirements.txt\n",
"!pip -q --no-color install -r requirements.txt"
]
},
{
"cell_type": "markdown",
"id": "691f5c48",
"metadata": {
"id": "691f5c48",
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"### Start EVA server\n",
"\n",
"We are reusing the start server notebook for launching the EVA server."
]
},
{
"cell_type": "code",
"execution_count": 52,
"id": "3309b54e",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "3309b54e",
"outputId": "52d663d0-e2c9-43bf-c15d-08cca3ab91fc",
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"File '00-start-eva-server.ipynb' already there; not retrieving.\n",
"\n",
"nohup eva_server > eva.log 2>&1 &\n",
"\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip available: \u001b[0m\u001b[31;49m22.2.2\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m22.3.1\u001b[0m\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
"Note: you may need to restart the kernel to use updated packages.\n"
]
}
],
"source": [
"!wget -nc \"https://raw.githubusercontent.com/georgia-tech-db/eva/master/tutorials/00-start-eva-server.ipynb\"\n",
"%run 00-start-eva-server.ipynb\n",
"cursor = connect_to_server()"
]
},
{
"attachments": {},
"cell_type": "markdown",
"id": "5d928fc9",
"metadata": {},
"source": [
"### Register License Plate Extraction UDF"
]
},
{
"cell_type": "code",
"execution_count": 53,
"id": "8b610905",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "8b610905",
"outputId": "c712ad96-1ca6-4d4c-d549-c5c3c139469e",
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"File 'ocr_extractor.py' already there; not retrieving.\n",
"\n",
"@status: ResponseStatus.SUCCESS\n",
"@batch: \n",
" 0\n",
"0 UDF LicensePlateExtractor successfully dropped\n",
"@query_time: 0.02209987910464406\n",
"@status: ResponseStatus.SUCCESS\n",
"@batch: \n",
" 0\n",
"0 UDF LicensePlateExtractor successfully added to the database.\n",
"@query_time: 5.75298752496019\n"
]
}
],
"source": [
"!wget -nc \"https://raw.githubusercontent.com/georgia-tech-db/license-plate-recognition/main/ocr_extractor.py\"\n",
"cursor.execute(\"DROP UDF LicensePlateExtractor;\")\n",
"response = cursor.fetch_all()\n",
"print(response)\n",
"cursor.execute(\"\"\"CREATE UDF IF NOT EXISTS LicensePlateExtractor\n",
" INPUT (frame NDARRAY UINT8(3, ANYDIM, ANYDIM))\n",
" OUTPUT (labels NDARRAY STR(ANYDIM), bboxes NDARRAY FLOAT32(ANYDIM, 4),\n",
" scores NDARRAY FLOAT32(ANYDIM))\n",
" TYPE Classification\n",
" IMPL 'license_plate_extractor.py';\n",
" \"\"\")\n",
"response = cursor.fetch_all()\n",
"print(response)"
]
},
{
"attachments": {},
"cell_type": "markdown",
"id": "6cdcf769",
"metadata": {},
"source": [
"# Download Images or Videos for License Plate Recognition"
]
},
{
"cell_type": "code",
"execution_count": 54,
"id": "d5f9fd52",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "d5f9fd52",
"outputId": "2a1574d7-3211-4a8a-b0ba-e1bdbd98503c",
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"File 'test_image_1.png' already there; not retrieving.\n",
"\n",
"File 'test_image_2.png' already there; not retrieving.\n",
"\n",
"File 'car10.jpg' already there; not retrieving.\n",
"\n",
"File 'car6.jpg' already there; not retrieving.\n",
"\n",
"File 'ezgif-frame-001.jpg' already there; not retrieving.\n",
"\n",
"File 'maxresdefault.jpg' already there; not retrieving.\n",
"\n",
"@status: ResponseStatus.SUCCESS\n",
"@batch: \n",
" 0\n",
"0 Table Successfully dropped: MyImages\n",
"@query_time: 0.04169625393114984\n",
"@status: ResponseStatus.SUCCESS\n",
"@batch: \n",
" 0\n",
"0 Number of loaded IMAGE: 1\n",
"@query_time: 0.062016993993893266\n",
"@status: ResponseStatus.SUCCESS\n",
"@batch: \n",
" 0\n",
"0 Number of loaded IMAGE: 1\n",
"@query_time: 0.019084053114056587\n",
"@status: ResponseStatus.SUCCESS\n",
"@batch: \n",
" 0\n",
"0 Number of loaded IMAGE: 1\n",
"@query_time: 0.014059118926525116\n",
"@status: ResponseStatus.SUCCESS\n",
"@batch: \n",
" 0\n",
"0 Number of loaded IMAGE: 1\n",
"@query_time: 0.013788505923002958\n",
"@status: ResponseStatus.SUCCESS\n",
"@batch: \n",
" 0\n",
"0 Number of loaded IMAGE: 1\n",
"@query_time: 0.09639617404900491\n",
"@status: ResponseStatus.SUCCESS\n",
"@batch: \n",
" 0\n",
"0 Number of loaded IMAGE: 1\n",
"@query_time: 0.01887107198126614\n",
"@status: ResponseStatus.SUCCESS\n",
"@batch: \n",
" licenseplateextractor.labels \\\n",
"0 [TN4805566] \n",
"1 [INAQ3044] \n",
"2 [EGB62644] \n",
"3 [LEM446A4] \n",
"4 [4II982A7A, 770L7726] \n",
"5 [LPD7SRV616, IPD8NBZ548] \n",
"\n",
" licenseplateextractor.bboxes \\\n",
"0 [[[432, 648], [723, 648], [723, 698], [432, 698]]] \n",
"1 [[[298, 238], [398, 238], [398, 264], [298, 264]]] \n",
"2 [[[178, 430], [300, 430], [300, 462], [178, 462]]] \n",
"3 [[[263, 465], [383, 465], [383, 501], [263, 501]]] \n",
"4 [[[2263, 398], [2347, 398], [2347, 436], [2263, 436]], [[216.02985749985467, 829.1194299994187],... \n",
"5 [[[236, 372], [344, 372], [344, 396], [236, 396]], [[986, 536], [1100, 536], [1100, 560], [986, ... \n",
"\n",
" licenseplateextractor.scores \n",
"0 [0.765264012834225] \n",
"1 [0.5979598335637649] \n",
"2 [0.8205181373232121] \n",
"3 [0.37683450003837526] \n",
"4 [0.005999226930693703, 0.041628318390644674] \n",
"5 [0.3380678860228084, 0.8426790601376755] \n",
"@query_time: 6.48794734897092\n",
"File 'video12.mp4' already there; not retrieving.\n",
"\n",
"@status: ResponseStatus.SUCCESS\n",
"@batch: \n",
" 0\n",
"0 Table Successfully dropped: MyVideos\n",
"@query_time: 0.03438917710445821\n",
"@status: ResponseStatus.SUCCESS\n",
"@batch: \n",
" 0\n",
"0 Number of loaded VIDEO: 1\n",
"@query_time: 0.10285129793919623\n",
"@status: ResponseStatus.SUCCESS\n",
"@batch: \n",
" licenseplateextractor.labels \\\n",
"0 [TSO7FX353L] \n",
"\n",
" licenseplateextractor.bboxes \\\n",
"0 [[[361, 765], [685, 765], [685, 841], [361, 841]]] \n",
"\n",
" licenseplateextractor.scores \n",
"0 [0.5929218894477851] \n",
"@query_time: 5.48489326890558\n"
]
}
],
"source": [
"!wget -nc \"https://raw.githubusercontent.com/georgia-tech-db/license-plate-recognition/main/test_image_1.png\"\n",
"!wget -nc \"https://raw.githubusercontent.com/georgia-tech-db/license-plate-recognition/main/test_image_2.png\"\n",
"!wget -nc \"https://raw.githubusercontent.com/femioladeji/License-Plate-Recognition-Nigerian-vehicles/master/test_images/car10.jpg\"\n",
"!wget -nc \"https://raw.githubusercontent.com/femioladeji/License-Plate-Recognition-Nigerian-vehicles/master/test_images/car6.jpg\"\n",
"!wget -nc \"https://im.ezgif.com/tmp/ezgif-1-c32008dd2a-jpg/ezgif-frame-001.jpg\"\n",
"!wget -nc \"https://i.ytimg.com/vi/p91epBEfISk/maxresdefault.jpg\"\n",
"\n",
"# DOWNLOAD ADDITIONAL IMAGES IF NEEDED AND LOAD THEM HERE\n",
"\n",
"########################################################\n",
"###\n",
"### IMAGES\n",
"###\n",
"########################################################\n",
"\n",
"cursor.execute('DROP TABLE IF EXISTS MyImages')\n",
"response = cursor.fetch_all()\n",
"print(response)\n",
"\n",
"cursor.execute('LOAD IMAGE \"test_image_1.png\" INTO MyImages;')\n",
"response = cursor.fetch_all()\n",
"print(response)\n",
"cursor.execute('LOAD IMAGE \"test_image_2.png\" INTO MyImages;')\n",
"response = cursor.fetch_all()\n",
"print(response)\n",
"cursor.execute('LOAD IMAGE \"car10.jpg\" INTO MyImages;')\n",
"response = cursor.fetch_all()\n",
"print(response)\n",
"cursor.execute('LOAD IMAGE \"car6.jpg\" INTO MyImages;')\n",
"response = cursor.fetch_all()\n",
"print(response)\n",
"cursor.execute('LOAD IMAGE \"ezgif-frame-001.jpg\" INTO MyImages;')\n",
"response = cursor.fetch_all()\n",
"print(response)\n",
"cursor.execute('LOAD IMAGE \"maxresdefault.jpg\" INTO MyImages;')\n",
"response = cursor.fetch_all()\n",
"print(response)\n",
"\n",
"cursor.execute(\"\"\"SELECT LicensePlateExtractor(data)\n",
" FROM MyImages\"\"\")\n",
"response = cursor.fetch_all()\n",
"print(response)\n",
"\n",
"########################################################\n",
"###\n",
"### VIDEOS\n",
"###\n",
"########################################################\n",
"\n",
"!wget -nc \"https://raw.githubusercontent.com/apoorva-dave/LicensePlateDetector/master/video12.mp4\"\n",
"\n",
"# DOWNLOAD ADDITIONAL VIDEOS IF NEEDED AND LOAD THEM HERE\n",
"\n",
"cursor.execute('DROP TABLE IF EXISTS MyVideos')\n",
"response2 = cursor.fetch_all()\n",
"print(response2)\n",
"cursor.execute('LOAD VIDEO \"video12.mp4\" INTO MyVideos;')\n",
"response2 = cursor.fetch_all()\n",
"print(response2)\n",
"cursor.execute(\"\"\"SELECT LicensePlateExtractor(data)\n",
" FROM MyVideos\n",
" WHERE id = 10\"\"\")\n",
"response2 = cursor.fetch_all()\n",
"print(response2)\n"
]
},
{
"attachments": {},
"cell_type": "markdown",
"id": "a7f6dd1a",
"metadata": {},
"source": [
"### Annotate Model Output on Image"
]
},
{
"cell_type": "code",
"execution_count": 81,
"id": "64f7392a",
"metadata": {
"id": "64f7392a"
},
"outputs": [],
"source": [
"import cv2\n",
"from pprint import pprint\n",
"from matplotlib import pyplot as plt\n",
"from pathlib import Path\n",
"\n",
"def annotate_image_ocr(detections, input_image_path, frame_id):\n",
" color1=(0, 255, 150)\n",
" color2=(255, 49, 49)\n",
" white=(255, 255, 255)\n",
" thickness=4\n",
"\n",
" frame = cv2.imread(input_image_path)\n",
" height, width = frame.shape[:2]\n",
"\n",
" if frame_id == 0:\n",
" frame= cv2.copyMakeBorder(frame, 0, 100, 0, 100, cv2.BORDER_CONSTANT,value=white)\n",
"\n",
" print(detections)\n",
" plate_id = 0\n",
"\n",
" df = detections\n",
" df = df[['licenseplateextractor.bboxes', 'licenseplateextractor.labels']][df.index == frame_id]\n",
"\n",
" x_offset = width * 0.1\n",
" y_offset = height * 0.4\n",
"\n",
" if df.size:\n",
" dfLst = df.values.tolist()\n",
" for bbox, label in zip(dfLst[plate_id][0], dfLst[plate_id][1]):\n",
" x1, y1, x2, y2 = bbox\n",
" x1, y1, x2, y2 = int(x1[0]), int(x1[1]), int(x2[0]), int(x2[1])\n",
" # object bbox\n",
" cv2.rectangle(frame, (x1, y1), (x2, y2), color1, thickness) \n",
"\n",
" # object label\n",
" cv2.putText(frame, label, (int(x1), int(y1 - height * 0.1)), cv2.FONT_HERSHEY_SIMPLEX, (6 * width)/2400, color2, \n",
" int((12 * width)/2400), cv2.LINE_AA) \n",
"\n",
" # Show every frame\n",
" plt.imshow(frame)\n",
" plt.show()\n",
"\n",
" p = Path(input_image_path)\n",
" output_path = \"{0}_{2}{1}\".format(p.stem, p.suffix, \"output\")\n",
"\n",
" cv2.imwrite(output_path, frame)\n"
]
},
{
"cell_type": "code",
"execution_count": 82,
"id": "c1f491b8",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "c1f491b8",
"outputId": "b089b4c9-45bd-4dca-c92b-25073449b7f3"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" licenseplateextractor.labels \\\n",
"0 [TN4805566] \n",
"1 [INAQ3044] \n",
"2 [EGB62644] \n",
"3 [LEM446A4] \n",
"4 [4II982A7A, 770L7726] \n",
"5 [LPD7SRV616, IPD8NBZ548] \n",
"\n",
" licenseplateextractor.bboxes \\\n",
"0 [[[432, 648], [723, 648], [723, 698], [432, 69... \n",
"1 [[[298, 238], [398, 238], [398, 264], [298, 26... \n",
"2 [[[178, 430], [300, 430], [300, 462], [178, 46... \n",
"3 [[[263, 465], [383, 465], [383, 501], [263, 50... \n",
"4 [[[2263, 398], [2347, 398], [2347, 436], [2263... \n",
"5 [[[236, 372], [344, 372], [344, 396], [236, 39... \n",
"\n",
" licenseplateextractor.scores \n",
"0 [0.765264012834225] \n",
"1 [0.5979598335637649] \n",
"2 [0.8205181373232121] \n",
"3 [0.37683450003837526] \n",
"4 [0.005999226930693703, 0.041628318390644674] \n",
"5 [0.3380678860228084, 0.8426790601376755] \n"
]
},
{
"data": {
"image/png": 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