200 lines
6.7 KiB
Python
200 lines
6.7 KiB
Python
import json
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import os
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import sys
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import threading
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from time import sleep
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import ultimateAlprSdk
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from PIL import Image
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from flask import Flask, request, jsonify
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counter = 0
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"""
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Hi there!
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This script is a REST API server that uses the ultimateALPR SDK to process images and return the license plate
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information. The server is created using Flask and the ultimateALPR SDK is used to process the images.
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See the README.md file for more information on how to run this script.
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"""
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# Defines the default JSON configuration. More information at https://www.doubango.org/SDKs/anpr/docs/Configuration_options.html
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JSON_CONFIG = {
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"debug_level": "info",
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"debug_write_input_image_enabled": False,
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"debug_internal_data_path": ".",
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"num_threads": -1,
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"gpgpu_enabled": True,
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"max_latency": -1,
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"klass_vcr_gamma": 1.5,
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"detect_roi": [0, 0, 0, 0],
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"detect_minscore": 0.35,
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"car_noplate_detect_min_score": 0.8,
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"pyramidal_search_enabled": True,
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"pyramidal_search_sensitivity": 0.38, # default 0.28
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"pyramidal_search_minscore": 0.8,
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"pyramidal_search_min_image_size_inpixels": 800,
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"recogn_rectify_enabled": True, # heavy on cpu
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"recogn_minscore": 0.4,
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"recogn_score_type": "min"
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}
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IMAGE_TYPES_MAPPING = {
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'RGB': ultimateAlprSdk.ULTALPR_SDK_IMAGE_TYPE_RGB24,
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'RGBA': ultimateAlprSdk.ULTALPR_SDK_IMAGE_TYPE_RGBA32,
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'L': ultimateAlprSdk.ULTALPR_SDK_IMAGE_TYPE_Y
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}
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def load_engine():
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bundle_dir = getattr(sys, '_MEIPASS', os.path.abspath(os.path.dirname(__file__)))
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JSON_CONFIG["assets_folder"] = os.path.join(bundle_dir, "assets")
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JSON_CONFIG["charset"] = "latin"
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JSON_CONFIG["car_noplate_detect_enabled"] = False # Whether to detect and return cars with no plate
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JSON_CONFIG[
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"ienv_enabled"] = False # Whether to enable Image Enhancement for Night-Vision (IENV). More info about IENV at https://www.doubango.org/SDKs/anpr/docs/Features.html#image-enhancement-for-night-vision-ienv. Default: true for x86-64 and false for ARM.
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JSON_CONFIG[
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"openvino_enabled"] = False # Whether to enable OpenVINO. Tensorflow will be used when OpenVINO is disabled
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JSON_CONFIG[
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"openvino_device"] = "GPU" # Defines the OpenVINO device to use (CPU, GPU, FPGA...). More info at https://www.doubango.org/SDKs/anpr/docs/Configuration_options.html#openvino-device
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JSON_CONFIG["npu_enabled"] = False # Whether to enable NPU (Neural Processing Unit) acceleration
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JSON_CONFIG[
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"klass_lpci_enabled"] = False # Whether to enable License Plate Country Identification (LPCI). More info at https://www.doubango.org/SDKs/anpr/docs/Features.html#license-plate-country-identification-lpci
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JSON_CONFIG[
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"klass_vcr_enabled"] = False # Whether to enable Vehicle Color Recognition (VCR). More info at https://www.doubango.org/SDKs/anpr/docs/Features.html#vehicle-color-recognition-vcr
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JSON_CONFIG[
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"klass_vmmr_enabled"] = False # Whether to enable Vehicle Make Model Recognition (VMMR). More info at https://www.doubango.org/SDKs/anpr/docs/Features.html#vehicle-make-model-recognition-vmmr
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JSON_CONFIG[
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"klass_vbsr_enabled"] = False # Whether to enable Vehicle Body Style Recognition (VBSR). More info at https://www.doubango.org/SDKs/anpr/docs/Features.html#vehicle-body-style-recognition-vbsr
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JSON_CONFIG["license_token_file"] = "" # Path to license token file
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JSON_CONFIG["license_token_data"] = "" # Base64 license token data
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result = ultimateAlprSdk.UltAlprSdkEngine_init(json.dumps(JSON_CONFIG))
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if not result.isOK():
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raise RuntimeError("Init failed: %s" % result.phrase())
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while counter < 3000:
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sleep(1)
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unload_engine()
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load_engine()
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def unload_engine():
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result = ultimateAlprSdk.UltAlprSdkEngine_deInit()
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if not result.isOK():
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raise RuntimeError("DeInit failed: %s" % result.phrase())
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def process_image(image: Image) -> str:
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global counter
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counter += 1
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width, height = image.size
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if image.mode in IMAGE_TYPES_MAPPING:
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image_type = IMAGE_TYPES_MAPPING[image.mode]
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else:
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raise ValueError("Invalid mode: %s" % image.mode)
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result = ultimateAlprSdk.UltAlprSdkEngine_process(
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image_type,
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image.tobytes(), # type(x) == bytes
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width,
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height,
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0, # stride
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1 # exifOrientation (already rotated in load_image -> use default value: 1)
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)
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if not result.isOK():
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raise RuntimeError("Process failed: %s" % result.phrase())
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else:
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return result.json()
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def create_rest_server_flask():
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app = Flask(__name__)
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@app.route('/v1/<string:domain>/<string:module>', methods=['POST'])
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def alpr(domain, module):
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# Only care about the ALPR endpoint
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if domain == 'image' and module == 'alpr':
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if 'upload' not in request.files:
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return jsonify({'error': 'No image found'})
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image = request.files['upload']
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if image.filename == '':
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return jsonify({'error': 'No selected file'})
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image = Image.open(image)
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result = process_image(image)
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result = convert_to_cpai_compatible(result)
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return jsonify(result)
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else:
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return jsonify({'error': 'Endpoint not implemented'}), 404
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return app
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def convert_to_cpai_compatible(result):
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result = json.loads(result)
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response = {
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'success': "true",
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'processMs': result['duration'],
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'inferenceMs': result['duration'],
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'predictions': [],
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'message': '',
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'moduleId': 'ALPR',
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'moduleName': 'License Plate Reader',
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'code': 200,
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'command': 'alpr',
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'requestId': 'null',
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'inferenceDevice': 'none',
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'analysisRoundTripMs': 0,
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'processedBy': 'none',
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'timestamp': ''
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}
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if 'plates' in result:
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plates = result['plates']
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for plate in plates:
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warpedBox = plate['warpedBox']
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x_coords = warpedBox[0::2]
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y_coords = warpedBox[1::2]
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x_min = min(x_coords)
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x_max = max(x_coords)
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y_min = min(y_coords)
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y_max = max(y_coords)
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response['predictions'].append({
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'confidence': plate['confidence'] / 100,
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'label': "Plate: " + plate['text'],
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'plate': plate['text'],
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'x_min': x_min,
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'x_max': x_max,
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'y_min': y_min,
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'y_max': y_max
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})
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return response
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if __name__ == '__main__':
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engine = threading.Thread(target=load_engine, daemon=True)
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engine.start()
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app = create_rest_server_flask()
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app.run(host='0.0.0.0', port=5000)
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unload_engine()
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