IBM Automation Document Processing system requirements when disabling deep learning object detection for fixed-format documents in version 22.0.2

Detailed System Requirements

Abstract

Deep learning object detection is an advanced capability that generalizes the annotations from your training documents and dynamically applies them when possible. If your documents have a fixed format and the fields are located in the same places, you don't typically need this capability. When deep learning object detection is disabled, IBM Automation Document Processing extracts the fields from the same positions where they were annotated in the page. This works well on those fixed-format documents such as tax forms. If your documents have a dynamic format or sections with variable length, such as invoices, using deep learning object detection may yield better accuracy.

If you disable deep learning object detection, the performance is improved for document processing and data extraction training.

Content

You can use the following configuration to disable the deep-learning-object-detection container when you deploy IBM Automation Document Processing version 22.0.2.

ca_configuration:
  ocrextraction:
    deep_learning_object_detection:
      enabled: false

Attention: The values in the hardware requirements tables were derived under specific operating and environment conditions. The information is accurate under the given conditions, but results that are obtained in your operating environments might vary significantly. Therefore, IBM cannot provide any representations, assurances, guarantees, or warranties regarding the performance of the profiles in your environment.

Small profile recommendations for Document Processing engine components:

ca_configuration:
  global:
    deployment_profile_size: "small"

Component	CPU Request (m)	CPU Limit (m)	Memory Request (Mi)	Memory Limit (Mi)	Number of Replicas	Pods are licensed for production/non-production	Ephemeral storage Limit
OCR Extraction	200	1000	1024	2560	5	Yes	3072Mi
Classify Process	200	500	400	2048	1	Yes	3072Mi
Processing Extraction	500	1000	1024	3584	3	Yes	3072Mi
Natural Language Extractor	200	500	600	1440	2	Yes	3072Mi
Postprocessing	200	600	400	1229	1	No	3072Mi
Setup	200	600	600	1440	2	No	3072Mi
Backend	200	1000	400	2048	2	No	4608Mi
Redis	100	250	100	640	1	No	500Mi
RabbitMQ	100	1000	100	1024	2	No	3072Mi
One Conversion	200	1000	100	4096	1	Yes	3072Mi

Medium profile recommendations for Document Processing engine components:

ca_configuration:
  global:
    deployment_profile_size: "medium"

Component	CPU Request (m)	CPU Limit (m)	Memory Request (Mi)	Memory Limit (Mi)	Number of Replicas	Pods are licensed for production/non-production	Ephemeral storage Limit
OCR Extraction	200	1000	1024	2560	6	Yes	3072Mi
Classify Process	200	500	400	2048	2	Yes	3072Mi
Processing Extraction	500	1000	1024	3584	5	Yes	3072Mi
Natural Language Extractor	200	500	600	1440	2	Yes	3072Mi
Postprocessing	200	600	400	1229	2	No	3072Mi
Setup	200	600	600	1440	4	No	3072Mi
Backend	200	1000	400	2048	4	No	4608Mi
Redis	100	250	100	640	1	No	500Mi
RabbitMQ	100	1000	100	1024	3	No	3072Mi
One Conversion	200	1000	100	4096	2	Yes	3072Mi

Large profile recommendations for Document Processing engine components:

ca_configuration:
  global:
    deployment_profile_size: "large"

Component	CPU Request (m)	CPU Limit (m)	Memory Request (Mi)	Memory Limit (Mi)	Number of Replicas	Pods are licensed for production/non-production	Ephemeral storage Limit
OCR Extraction	200	1000	1024	2560	11	Yes	3072Mi
Classify Process	200	500	400	2048	3	Yes	3072Mi
Processing Extraction	500	1000	1024	3584	8	Yes	3072Mi
Natural Language Extractor	200	500	600	1440	3	Yes	3072Mi
Postprocessing	200	600	400	1229	2	No	3072Mi
Setup	200	600	600	1440	6	No	3072Mi
Backend	200	1000	400	2048	6	No	4608Mi
Redis	100	250	100	640	1	No	500Mi
RabbitMQ	100	1000	100	1024	3	No	3072Mi
One Conversion	200	1000	100	4096	2	Yes	3072Mi

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IBM Automation Document Processing system requirements when disabling deep learning object detection for fixed-format documents in version 22.0.2

Detailed System Requirements

Abstract

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