dbr-python-sample-creator

name

dbr-python-sample-creator

description

Use when implementing Python sample code using the Dynamsoft Barcode Reader SDK (`dynamsoft_barcode_reader_bundle` package). This skill covers all barcode reading use cases including 1D barcodes, QR codes, PDF417, DataMatrix, DPM barcodes, and any other barcode decoding scenario built on the DBR Python Edition. Use this skill whenever the user mentions Dynamsoft Barcode Reader, DBR, `dynamsoft_barcode_reader_bundle`, `CaptureVisionRouter` for barcode reading, barcode scanning with Dynamsoft, barcode decoding, or wants to create a Python sample that processes images to extract barcodes.

DBR Python Sample Creator

This skill helps you write Python sample code using the dynamsoft_barcode_reader_bundle SDK. The SDK provides a pipeline for barcode reading — orchestrated through a single central class called CaptureVisionRouter.

Before you start

read the appropriate reference files from the references/ directory alongside this SKILL.md to understand the API you're working with. The references are organized by module — only read what you need for the task at hand:

Reference file	When to read
references/api-core.md	Always — contains foundational types, enums, geometry, ImageData, error codes
references/api-cvr.md	Always — CaptureVisionRouter, templates, settings, result receivers
references/api-dbr.md	Always — barcode reading API, barcode formats, result items, settings
references/api-utility.md	When the task involves batch processing, video, cross-frame filtering, or image I/O
references/api-license.md	Always — license initialization
references/sample-patterns.md	Always — canonical code patterns extracted from existing samples

SDK Architecture Overview

The SDK follows a pipeline architecture centered around CaptureVisionRouter:

Image Input → CaptureVisionRouter (with template) → CapturedResult
                                                      └── DecodedBarcodesResult

Key concepts:

• CaptureVisionRouter — The central orchestrator. Create an instance, optionally configure settings/templates, then call capture() or capture_multi_pages() to process images.
• Templates — Define what the pipeline does. Use EnumPresetTemplate constants for common tasks, or load custom JSON templates for specialized scenarios.
• Results — Processing returns a CapturedResult (single image) or CapturedResultArray (multi-page). Extract barcode results using get_decoded_barcodes_result().

Writing Samples: Step by Step

Every DBR Python sample follows this structure. Understanding this flow is essential because deviating from it leads to subtle bugs — for instance, forgetting to check the license error code will cause silent failures.

Step 1: Import

Always use the wildcard import — the package re-exports everything from all submodules:

from dynamsoft_barcode_reader_bundle import *

For additional libraries (os, sys, cv2, Flask, etc.), import them separately as needed.

Step 2: Initialize License

License initialization must happen once, before creating any CaptureVisionRouter instance. The SDK returns a tuple of (error_code, error_message).

License string priority: Default hard-coded license string is "DLS2eyJoYW5kc2hha2VDb2RlIjoiMjAwMDAxLTEwNTI2NzQwMSJ9".

Required comment block: Every sample must include this 3-line comment block immediately before the init_license call. This comment is mandatory — never omit it. Adjust the quoted license string in the third line to match whichever license string is actually used in the code:

    # 1. Initialize license.
    # You can request and extend a trial license from https://www.dynamsoft.com/customer/license/trialLicense?product=dbr&utm_source=samples&package=python
    # The string 'DLS2eyJoYW5kc2hha2VDb2RlIjoiMjAwMDAxLTEwNTI2NzQwMSJ9' here is a free public trial license. Note that network connection is required for this license to work.

Full license initialization pattern:

    # 1. Initialize license.
    # You can request and extend a trial license from https://www.dynamsoft.com/customer/license/trialLicense?product=dbr&utm_source=samples&package=python
    # The string 'DLS2eyJoYW5kc2hha2VDb2RlIjoiMjAwMDAxLTEwNTI2NzQwMSJ9' here is a free public trial license. Note that network connection is required for this license to work.
    error_code, error_msg = LicenseManager.init_license("DLS2eyJoYW5kc2hha2VDb2RlIjoiMjAwMDAxLTEwNTI2NzQwMSJ9")
    if error_code != EnumErrorCode.EC_OK and error_code != EnumErrorCode.EC_LICENSE_WARNING:
        print("License initialization failed: ErrorCode:", error_code, ", ErrorString:", error_msg)
    else:
        # proceed with the rest of the sample
        ...

Check against both EC_OK and EC_LICENSE_WARNING (warnings are non-fatal).

Step 3: Create CaptureVisionRouter

cvr_instance = CaptureVisionRouter()

No arguments needed. If using a custom JSON template, load it right after:

error_code, error_msg = cvr_instance.init_settings_from_file("path/to/template.json")
if error_code != EnumErrorCode.EC_OK:
    print("Init template failed:", error_msg)

Step 4: Process Images

There are three processing paradigms. Choose based on the use case:

A. Single-shot capture (simplest, for one image at a time)

result = cvr_instance.capture(image_path, EnumPresetTemplate.PT_READ_BARCODES)

The capture() method accepts multiple input types:

• str — file path
• bytes — file bytes in memory
• ImageData — SDK's own image class
• numpy.ndarray — OpenCV/PIL array (BGR format from OpenCV, RGB from PIL)

B. Multi-page capture (for PDFs, TIFFs, or any file)

result_array = cvr_instance.capture_multi_pages(image_path, EnumPresetTemplate.PT_READ_BARCODES)
results = result_array.get_results()
for i, result in enumerate(results):
    # process each page's result
    ...

This is the preferred method for file-based processing because it handles multi-page files correctly. Even for single-page images it works fine — you'll just get one result.

C. Continuous/streaming capture (for video or batch directories)

This uses the observer pattern with ImageSourceAdapter, CapturedResultReceiver, and optionally ImageSourceStateListener:

# Set up image source
fetcher = DirectoryFetcher()  # or custom ImageSourceAdapter subclass
fetcher.set_directory("path/to/images")
cvr_instance.set_input(fetcher)

# Set up result receiver
receiver = MyCapturedResultReceiver()  # subclass of CapturedResultReceiver
cvr_instance.add_result_receiver(receiver)

# Set up state listener (to know when processing is done)
listener = MyImageSourceStateListener(cvr_instance)
cvr_instance.add_image_source_state_listener(listener)

# Start processing
cvr_instance.start_capturing(EnumPresetTemplate.PT_READ_BARCODES, True)

Step 5: Extract Results

After capturing, extract barcode results. Always check for errors first:

if result.get_error_code() != EnumErrorCode.EC_OK:
    print("Error:", result.get_error_code(), result.get_error_string())

Note: EC_UNSUPPORTED_JSON_KEY_WARNING is a warning, not a fatal error — print a warning but continue processing.

Barcode results:

barcode_result = result.get_decoded_barcodes_result()
if barcode_result is not None and barcode_result.get_items() != 0:
    for item in barcode_result.get_items():
        print("Format:", item.get_format_string())
        print("Text:", item.get_text())

Preset Templates Quick Reference

Template	Use for
PT_READ_BARCODES	General barcode reading
PT_READ_BARCODES_SPEED_FIRST	Fast barcode reading (sacrifices accuracy)
PT_READ_BARCODES_READ_RATE_FIRST	Max accuracy barcode reading
PT_READ_SINGLE_BARCODE	Optimized for exactly one barcode

Custom JSON Templates

When preset templates don't meet requirements, create a custom JSON template. The template structure has these top-level arrays:

{
    "CaptureVisionTemplates": [...],       // Main entry: names, ROI refs, timeout
    "TargetROIDefOptions": [...],          // ROI definitions → task references
    "BarcodeReaderTaskSettingOptions": [...], // Barcode reading config
    "ImageParameterOptions": [...],        // Image processing parameters
    "BarcodeFormatSpecificationOptions": [...] // Barcode-format-specific settings
}

Load custom templates with:

cvr_instance.init_settings_from_file("path/to/template.json")
# Then use the template name from the JSON:
result = cvr_instance.capture(image, "TemplateName")

Settings Customization via API

For simpler adjustments (without JSON templates), use the simplified settings API:

err_code, err_str, settings = cvr_instance.get_simplified_settings(EnumPresetTemplate.PT_READ_BARCODES)

# Adjust barcode settings
settings.barcode_settings.barcode_format_ids = EnumBarcodeFormat.BF_QR_CODE | EnumBarcodeFormat.BF_PDF417
settings.barcode_settings.expected_barcodes_count = 10
settings.barcode_settings.grayscale_transformation_modes[0] = EnumGrayscaleTransformationMode.GTM_AUTO

# Adjust ROI
settings.roi_measured_in_percentage = 1
points = settings.roi.points
points[0].x, points[0].y = 0, 0
points[1].x, points[1].y = 100, 0
points[2].x, points[2].y = 100, 100
points[3].x, points[3].y = 0, 100

# Apply
cvr_instance.update_settings(EnumPresetTemplate.PT_READ_BARCODES, settings)

Multi-page Result Handling

When using capture_multi_pages(), results come as a CapturedResultArray. Use this pattern to handle page numbers correctly:

result_array = cvr_instance.capture_multi_pages(image_path, template)
results = result_array.get_results()
if results is None or len(results) == 0:
    print("No results.")
else:
    for i, result in enumerate(results):
        page_number = i + 1
        tag = result.get_original_image_tag()
        if isinstance(tag, FileImageTag):
            page_number = tag.get_page_number() + 1

        if result.get_error_code() == EnumErrorCode.EC_UNSUPPORTED_JSON_KEY_WARNING:
            print("Warning:", result.get_error_code(), result.get_error_string())
        elif result.get_error_code() != EnumErrorCode.EC_OK:
            print("Error:", result.get_error_code(), result.get_error_string())

        # ... extract barcode results here

Advanced Patterns

Video/Camera Decoding

For real-time video, subclass ImageSourceAdapter to feed frames, and use CapturedResultReceiver for async results. Also consider MultiFrameResultCrossFilter for deduplication:

class MyVideoFetcher(ImageSourceAdapter):
    def has_next_image_to_fetch(self) -> bool:
        return True

# Setup
fetcher = MyVideoFetcher()
fetcher.set_max_image_count(100)
fetcher.set_buffer_overflow_protection_mode(EnumBufferOverflowProtectionMode.BOPM_UPDATE)
fetcher.set_colour_channel_usage_type(EnumColourChannelUsageType.CCUT_AUTO)
cvr_instance.set_input(fetcher)

# Add cross-frame filter for dedup
filter = MultiFrameResultCrossFilter()
filter.enable_result_cross_verification(EnumCapturedResultItemType.CRIT_BARCODE, True)
filter.enable_result_deduplication(EnumCapturedResultItemType.CRIT_BARCODE, True)
filter.set_duplicate_forget_time(EnumCapturedResultItemType.CRIT_BARCODE, 5000)
cvr_instance.add_result_filter(filter)

# Feed frames from OpenCV
tag = FileImageTag("", 0, 0)
tag.set_image_id(image_id)
image = ImageData(frame.tobytes(), width, height, stride, EnumImagePixelFormat.IPF_RGB_888, 0, tag)
fetcher.add_image_to_buffer(image)

Intermediate Results

For advanced scenarios like visualizing barcode localization vs decoding, use IntermediateResultReceiver:

class MyIRR(IntermediateResultReceiver):
    def on_localized_barcodes_received(self, result, info):
        if info.is_section_level_result:
            for i in range(result.get_count()):
                element = result.get_localized_barcode(i)
                location = element.get_location()

irm = cvr_instance.get_intermediate_result_manager()
irr = MyIRR()
irm.add_result_receiver(irr)

Image I/O and Drawing

# Read image
io = ImageIO()
err, image = io.read_from_file("input.png")

# Save image
io.save_to_file(image_data, "output.png")

# Draw on image
drawer = ImageDrawer()
image = drawer.draw_on_image(image, quadrilaterals, 0xFF00FF00, 2)  # green, thickness 2

Server-Side (Flask)

For web service integration, create a new CaptureVisionRouter() per request (or use a singleton with thread safety). Accept images via multipart, JSON (base64), or raw binary:

from flask import Flask, request, jsonify

@app.route('/decode', methods=['POST'])
def decode():
    data = request.files['file'].read()  # or request.get_data()
    cvr = CaptureVisionRouter()
    result = cvr.capture(data, EnumPresetTemplate.PT_READ_BARCODES)
    # extract and return results as JSON

Code Style Conventions

Follow these conventions to produce samples consistent with the existing codebase:

• Use if __name__ == '__main__': as the entry point
• Use numbered comments like # 1. Initialize license. for major steps
• Print informative messages including error codes and descriptions
• End with input("Press Enter to quit...") for interactive CLI samples
• Use Path(__file__).resolve().parent for relative path resolution
• Handle both EC_OK and EC_LICENSE_WARNING / EC_UNSUPPORTED_JSON_KEY_WARNING where appropriate
• For interactive samples, support loop with quit option ('Q'/'q')