Machine Vision Engineering Delivery · G05

Edge-AI Conversion and Acceleration

Commission Edge-AI Conversion and Acceleration as a scoped engineering work package. Scope: ONNX conversion, INT8/FP16, operator replacement and NPU/GPU/CPU tuning.

Scope and project-specific requirements

Task / output

ONNX conversion, INT8/FP16, operator replacement and NPU/GPU/CPU tuning

Critical decision conditions

Compare converted outputs on hard samples; report preprocessing/postprocessing as well as model execution time.

Work scope

ONNX conversion, INT8/FP16, operator replacement and NPU/GPU/CPU tuning

Compare converted outputs on hard samples; report preprocessing/postprocessing as well as model execution time.

Inputs for assessment

Provide current system versions, available documentation/issues, target platforms, responsible teams, deliverable lists, acceptance environments and permitted downtime.

Deliverables and interface agreement

Deployment models, inference program, calibration set and performance records

Specify input formats, output fields, coordinates/units, error states, versions and invocation methods. Define review and failure handling. The statement of work determines the exact scope of source code, executables, model files or analysis reports.

Acceptance method and measures

Task-specific acceptance measures

Acceptance uses named hardware, input dimensions and concurrency

Record input versions, changes, test cases and evidence by work package. Link deliverables to configurations; do not imply hardware or site outcomes outside the agreed scope.

These are measures to agree and test, not achieved-performance claims. Freeze samples, reference truth, thresholds and hardware/software versions before acceptance; report subgroup results and failures, identifying under-sampled conditions as uncovered.

Implementation and procurement stages

  1. Define scope

    Agree targets, stations, inputs and responsibilities in a statement of work, separating required and excluded conditions.

  2. Sample validation

    Use representative samples to test critical risks, document feasibility/failures and scope the next-stage estimate.

  3. Development and integration

    Implement agreed functions and interfaces with configuration/change records; use offline replay before authorized device or site integration.

  4. Acceptance and handover

    Retest against individual measures and hand over contracted artifacts with known limits; manage maintenance, expansion and changeovers as subsequent work packages.

Scope limits and licensing

Assessment, development, testing and operations may be contracted in stages. Define source-code rights, deployment count, maintenance term, third-party costs and site responsibilities in the statement of work.

Candidate technologies are not license clearance. Check code, model weights, training data and dependency versions separately. Replace, license or exclude components unsuitable for the intended commercial delivery. Customer data is not used for public training by default.

Project FAQs

What does this service produce?

ONNX conversion, INT8/FP16, operator replacement and NPU/GPU/CPU tuning. Deliverables: Deployment models, inference program, calibration set and performance records

What needs to be confirmed first?

Compare converted outputs on hard samples; report preprocessing/postprocessing as well as model execution time.

How is acceptance defined beyond a demonstration?

Task-specific measures: Acceptance uses named hardware, input dimensions and concurrency. Record input versions, changes, test cases and evidence by work package. Link deliverables to configurations; do not imply hardware or site outcomes outside the agreed scope.

How are cost and schedule assessed?

After reviewing samples for onnx conversion, int8/fp16, operator replacement and npu/gpu/cpu tuning, equipment conditions and interfaces, scope validation, development, deployment and acceptance separately. Data coverage, site changes and delivery rights affect the estimate; no fixed performance or schedule is promised before assessment.

PROJECT INQUIRY

Discuss this service for your project

Service ID: G05 · Edge-AI Conversion and Acceleration

Describe available samples, equipment and target measures. Agree confidentiality and permissions before transferring sensitive or personal data through an approved channel.

+86 13910119357
xuzhiyang0928@gmail.com

Submitted information is for this project inquiry. Do not include sensitive information without authorization.