Image classification

Sort images into classes. Each sample is one image file plus one row in a labels CSV that names the file and its class.

Folder layout

/data/shared/cats-dogs/
├── labels.csv
└── images/
    ├── cat1.jpeg
    ├── cat2.jpeg
    ├── dog1.jpeg
    └── ...

The image folder must be named images and sit next to the labels CSV.
Every image in the dataset must have the same extension and the same width and height. Mixed extensions or mixed resolutions fail the ingest.
Supported extensions: .jpg, .jpeg, .png. The default is .jpeg; override it with spec.file_options.extension.
The ingestor copies images as they are. It does not resize them — bring them to the target size before you ingest.

Labels CSV

filename,label
cat1.jpeg,cat
cat2.jpeg,cat
dog1.jpeg,dog
dog2.jpeg,dog

Column	Required	Meaning
`filename`	yes, exactly this name	The image file, with or without extension (`cat1` resolves to `images/cat1.jpeg` under the default extension).
`label`	yes	The class of the image. Any column name works — set it with `label:`. At least two distinct classes are required.

Extra columns are ignored unless you declare them in schema.

ingest.yaml

apiVersion: tracebloc.io/v1
kind: IngestConfig
category: image_classification
table: cats_dogs_train
intent: train
csv: /data/shared/cats-dogs/labels.csv
images: /data/shared/cats-dogs/images/
label: label

Field	Required	Meaning
`csv`	yes	Path to the labels CSV inside the ingestor.
`images`	yes	The `images/` folder. Its parent becomes the dataset root.
`label`	yes	Name of the class column in the CSV.
`target_size`	no	`[width, height]` every image must have. Default `[256, 256]`.
`spec.file_options.extension`	no	`.jpg`, `.jpeg` or `.png`. Default `.jpeg`.
`spec.file_options.min_size`	no	Absolute minimum `[width, height]`; images with a smaller side are rejected. Default `[32, 32]`.
`color_mode`, `bit_depth`	no	Declare `RGB` or `grayscale` and `8` or `16` so combined datasets can be checked for consistency.

To use images of another size, set target_size (or spec.file_options.target_size) to their exact dimensions:

target_size: [512, 512]
spec:
  file_options:
    extension: .png

What the ingestor checks

Check	Rejects
File type	Any file under `images/` whose extension is not the configured one, or a mix of extensions.
Image resolution	Any image whose `(width, height)` differs from `target_size`, more than one resolution in the folder, images with a side below `min_size`, and unreadable or empty image files.
Label column	A CSV whose header has no column matching `label:`.
Label diversity	Fewer than two distinct label values.

Plus the checks every ingest runs.

Sample dataset

The template ships six 256×256 RGB JPEG images (three cats, three dogs) and a labels CSV with the two classes cat and dog. The ingest.yaml above ingests it with no overrides.

Next steps

Stage the data and run the ingest: Prepare Data
Shared rules for every template: Dataset templates

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Image classification

Folder layout

Labels CSV

ingest.yaml

What the ingestor checks

Sample dataset

Next steps

​Folder layout

​Labels CSV

​ingest.yaml

​What the ingestor checks

​Sample dataset

​Next steps

Folder layout

Labels CSV

ingest.yaml

What the ingestor checks

Sample dataset

Next steps