Ahmed Ibrahim Metawee / Airguard VisionEdge Public

Missing data in your test dataset. To generate test accuracy, upload test data, or perform train/test split on your existing dataset from your project dashboard

The EON Tuner helps you quickly run hyper-parameter sweeps that explore different pre-processing + model architectures optimized for your defined objectives. Clone this project to use the EON Tuner.

Target

No name set

Qualcomm Dragonwing RB3 Gen 2 Development Kit

100 ms

8388608 kB

134217728 kB

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Training output

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Click 'Run EON Tuner' to begin

The EON Tuner uses a Bayesian search algorithm to find optimal impulse configurations. To get started, select at least one run objective and configure your search space.

Name

Compute limit

Run objectives

Search space configuration

Do more with EON Tuner

Access more parallel EON Tuner jobs for faster results, a fully customizable search space, and more model variant options.

We're always looking for ways to improve Edge Impulse. If you have any feedback, please let us know!

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Target device

Define your target device requirements to inform model optimizations and performance calculations. No device yet? Use the default settings which you can change at any time.

Target device

Processor family

Clock rate

| MHz

Max

Custom device name

Application budget

Specify the available RAM and ROM for the model's operation, along with the maximum allowed latency for your specific application. Not sure yet? Start with the defaults and modify them later on.

RAM

| KB

Max

ROM

| KB

Max

Latency

| ms

Max

YEARLY

$400 /month

billed annually

SAVE 15%

MONTHLY

$475 /month

billed monthly

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