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Image Classification API

Run a pretrained image classifier behind an API and return ranked labels and confidence. This Python project practices Python fundamentals, practical problem decomposition, validation, and maintainable implementation.

Estimate
~10h
Steps
5
Completed by
0
Proposed by
codeseed.app

pandas · Pillow

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Project roadmap

  1. 01

    Design the architecture

    ~1.5h

    Define components, data contracts, persistence boundaries, invariants, failure modes, and concurrency needs for Image Classification API.

  2. 02

    Implement the critical path

    ~2.5h

    Build the primary Image Classification API workflow with explicit invariants, validation, and controlled state transitions.

  3. 03

    Add durability and recovery

    ~2h

    Implement durable state, checkpoints, retries, or recovery behavior appropriate to Image Classification API's failure model.

  4. 04

    Control concurrency and limits

    ~2h

    Add ordering, backpressure, rate limits, bounded concurrency, or conflict handling required by Image Classification API.

  5. 05

    Add observability and tests

    ~2h

    Add structured diagnostics and test normal operation, failures, restart behavior, and important invariants for Image Classification API.

Resources

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~10h · 5 steps

Tech stack

pandasPillow