واجهة برمجة تطبيقات بايثون لإضافة قدرات OMR واستخراج البيانات

قم بتثبيت Aspose.OMR Cloud SDK للغة بايثون عبر pip

pip install aspose-omr-cloud

يمكنك تنزيل المكتبة مباشرةً من صفحة المنتج Aspose.OMR Cloud SDK للغة بايثون product page

كيف تُنشئ قالب نموذج قابل للقراءة آليًا باستخدام واجهة برمجة تطبيقات بايثون؟

import asposeomrcloud
from asposeomrcloud.models import OmrFunctionParam, Template, TemplateDto

# Set your API key and SID
asposeomrcloud.configuration.api_key['api_key'] = 'your_api_key'
asposeomrcloud.configuration.api_key['app_sid'] = 'your_sid'

# Initialize the OMR API client
omr_api = asposeomrcloud.OmrApi()

# Define the questions for the template
questions = [
    "What is your name?",
    "How satisfied are you with our service? (1-5)",
    "Which products have you purchased? (Select all that apply)",
    "Additional comments (if any):"
]

# Create an array of TemplateDto objects
template_dto_array = [TemplateDto(name=question) for question in questions]

# Create a Template instance
template = Template(template_dto_array)

# Create a new template and get the template ID
template_response = omr_api.post_generate_template(template)

# Print the generated template ID
print(f"Template ID: {template_response.template_id}")

كيف تُحمِّل وتُعرّف النموذج المملوء باستخدام واجهة برمجة تطبيقات بايثون؟

import asposeomrcloud
from asposeomrcloud.models import RecognizeRequest, OmrFunctionParam

# Set your API key and SID
asposeomrcloud.configuration.api_key['api_key'] = 'your_api_key'
asposeomrcloud.configuration.api_key['app_sid'] = 'your_sid'

# Initialize the OMR API client
omr_api = asposeomrcloud.OmrApi()

# Specify the path to the filled form image
image_path = 'path/to/filled_form.jpg'

# Create a RecognizeRequest instance
recognize_request = RecognizeRequest(
    function_params=[OmrFunctionParam("name", "value")],  # Additional parameters if needed
    image_file=omr_api.byte_array_input(open(image_path, 'rb').read())
)

# Perform OMR recognition
result = omr_api.post_run_omr_task(recognize_request)

# Extract and print the recognized data
for page in result.pages:
    for field in page.fields:
        print(f"Field: {field.field_name}, Value: {field.field_value}")