Skip to main content

Pipelines for AI-Parrot planogram and vision workflows

Project description

AI-Parrot Pipelines

ai-parrot-pipelines provides vision and compliance pipelines for AI-Parrot agents. It includes planogram compliance checking, retail product detection, and image analysis workflows.

Installation

pip install ai-parrot-pipelines

Features

  • Planogram Compliance — verify product placement against planogram specifications
  • Retail Detection — detect products on shelves, graphic panels, and endcaps
  • Abstract Pipeline — base class for building custom vision pipelines
  • Abstract Detector — base class for object detection integrations

Available Pipelines

Pipeline Description
PlanogramCompliance Full planogram compliance checking pipeline
ProductOnShelves Detect and validate products on shelf displays
GraphicPanelDisplay Validate graphic panel displays
RetailDetector General retail product detection

Quick Start

from parrot_pipelines.planogram.plan import PlanogramCompliance
from parrot_pipelines.models import PlanogramConfig

config = PlanogramConfig(
    image_path="shelf_photo.jpg",
    reference_path="planogram_spec.json",
)

pipeline = PlanogramCompliance(config=config)
result = await pipeline.run()

Dependencies

Note: pytesseract requires Tesseract OCR installed on your system.

License

MIT

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ai_parrot_pipelines-0.1.78.tar.gz (117.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ai_parrot_pipelines-0.1.78-py3-none-any.whl (126.7 kB view details)

Uploaded Python 3

File details

Details for the file ai_parrot_pipelines-0.1.78.tar.gz.

File metadata

  • Download URL: ai_parrot_pipelines-0.1.78.tar.gz
  • Upload date:
  • Size: 117.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.14

File hashes

Hashes for ai_parrot_pipelines-0.1.78.tar.gz
Algorithm Hash digest
SHA256 c6497a082b98054c32cbd2a3686234578c51ce17ae64b35a9d7cf70f06f9c9ae
MD5 155517bb1226907df8b1a4262665feb5
BLAKE2b-256 ab87558661d908e5006c7db8af18f566fe865943cd7ad08915e38fc3ffa69052

See more details on using hashes here.

Provenance

The following attestation bundles were made for ai_parrot_pipelines-0.1.78.tar.gz:

Publisher: release.yml on phenobarbital/ai-parrot

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file ai_parrot_pipelines-0.1.78-py3-none-any.whl.

File metadata

File hashes

Hashes for ai_parrot_pipelines-0.1.78-py3-none-any.whl
Algorithm Hash digest
SHA256 94e6e0ddd8f704c562b291511bd5e7e97dcbff78f06630b44df9b23ef23a6454
MD5 4c4925b74dec854a6cbf71ad16b0a2ee
BLAKE2b-256 7c8e77999856bc36a04cc0bc20cdfe4fbbe01d257b6b871470b641407599824e

See more details on using hashes here.

Provenance

The following attestation bundles were made for ai_parrot_pipelines-0.1.78-py3-none-any.whl:

Publisher: release.yml on phenobarbital/ai-parrot

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page