Mateusz / CBM Fault Classifier Public

Data collected

33m 20s

Train / test split

79% / 21%

Dataset

Training (3,170)

Test (830)

Apply filters

Clear all filters

By label

By name or ID

By length

500

By frequency

By signature validity

Enabled & disabled samples

ID	Sample name	Label	Length	Signature	Sensors
98656577	running.23	running	500ms	HS256	pca0, pca1, pca2, pca3, pca4, pca5, pca6, pca7, pca8, pca9, pca10, pca11, pca12, pca13, pca14, pca15, pca16, pca17, pca18, pca19, pca20, pca21, pca22, pca23, pca24, pca25, pca26, pca27, pca28, pca29, pca30, pca31, pca32, pca33, pca34, pca35, pca36, pca37, pca38, pca39, pca40, pca41, pca42, pca43, pca44, pca45, pca46, pca47, pca48, pca49, pca50, pca51, pca52, pca53, pca54, pca55, pca56, pca57, pca58, pca59, pca60, pca61, pca62, pca63, pca64, pca65, pca66, pca67, pca68, pca69 @ 20Hz	Download
98656532	running.235	running	500ms	HS256	pca0, pca1, pca2, pca3, pca4, pca5, pca6, pca7, pca8, pca9, pca10, pca11, pca12, pca13, pca14, pca15, pca16, pca17, pca18, pca19, pca20, pca21, pca22, pca23, pca24, pca25, pca26, pca27, pca28, pca29, pca30, pca31, pca32, pca33, pca34, pca35, pca36, pca37, pca38, pca39, pca40, pca41, pca42, pca43, pca44, pca45, pca46, pca47, pca48, pca49, pca50, pca51, pca52, pca53, pca54, pca55, pca56, pca57, pca58, pca59, pca60, pca61, pca62, pca63, pca64, pca65, pca66, pca67, pca68, pca69 @ 20Hz	Download
98656531	running.236	running	500ms	HS256	pca0, pca1, pca2, pca3, pca4, pca5, pca6, pca7, pca8, pca9, pca10, pca11, pca12, pca13, pca14, pca15, pca16, pca17, pca18, pca19, pca20, pca21, pca22, pca23, pca24, pca25, pca26, pca27, pca28, pca29, pca30, pca31, pca32, pca33, pca34, pca35, pca36, pca37, pca38, pca39, pca40, pca41, pca42, pca43, pca44, pca45, pca46, pca47, pca48, pca49, pca50, pca51, pca52, pca53, pca54, pca55, pca56, pca57, pca58, pca59, pca60, pca61, pca62, pca63, pca64, pca65, pca66, pca67, pca68, pca69 @ 20Hz	Download
98656528	running.239	running	500ms	HS256	pca0, pca1, pca2, pca3, pca4, pca5, pca6, pca7, pca8, pca9, pca10, pca11, pca12, pca13, pca14, pca15, pca16, pca17, pca18, pca19, pca20, pca21, pca22, pca23, pca24, pca25, pca26, pca27, pca28, pca29, pca30, pca31, pca32, pca33, pca34, pca35, pca36, pca37, pca38, pca39, pca40, pca41, pca42, pca43, pca44, pca45, pca46, pca47, pca48, pca49, pca50, pca51, pca52, pca53, pca54, pca55, pca56, pca57, pca58, pca59, pca60, pca61, pca62, pca63, pca64, pca65, pca66, pca67, pca68, pca69 @ 20Hz	Download

Raw data

Click on a sample to load...

Metadata

No metadata.

Add Segment

Set sample length (ms.):

Set segment length (ms.):

Visible range: ms - ms

Use your mouse to drag a box around an object to add a label.

You can upload CBOR, JSON, CSV, WAV, JPG, PNG, AVI or MP4 files. You can also upload an annotation file named "info.labels" with your data to assign bounding boxes, labels, and/or metadata. View Uploader docs to learn more. Alternatively, you can use our Python SDK to programmatically ingest data in various formats, such as pandas or numpy.

For CSV files, configure the CSV Wizard to define how your files should be processed before uploading files.

Bounding boxes: You can upload object detection datasets in any supported format. Select both your images and the label file(s) when uploading to apply the labels.

Please give us some information about the data you are trying to upload.

Dataset annotation format

This field is required

Directory structure

This field is required

Label format

This field is required

Collect data directly from your phone, computer, device, or development board.

Device "" is now connected

Use the 'Record new data' section to collect data from this device.

You can connect almost any device over serial using our data forwarder:

$ edge-impulse-data-forwarder

Or connect a supported device or development board:

These users will be notified over email when this job finishes.

	Name
	M Mateusz

Set the label (leave empty to remove these labels):

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

Subject

This field is required

How was your experience?

This field is required

You'll need a free Edge Impulse account to clone this project. Creating an account lets you add your own data, modify models, and join a community of thousands of embedded machine learning developers!

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

Data collected

Train / test split

Dataset

Apply filters

By label

By name or ID

By length

By frequency

By signature validity

Enabled & disabled samples

Add data

Raw data

Click on a sample to load...

Metadata

updown