Image classification from raw photos to reviewable results
Plan the collection, transformations, evaluation groups, and review process behind a meaningful visual classification.
Read the guide ↗VISION & IMAGERY
Image Classification Neuro Browser
Understand the steps behind a visual label: dataset definition, preprocessing, evaluation, and inspection of mistakes.
TOPIC GUIDE / 04 · READ, QUESTION, EXPLORE
Name the visual question
A classification task assigns a category under a defined label scheme. Before discussing a model, describe the image collection and the decision the label is meant to support. Avoid combining research imagery, ordinary photographs, and medical scans into one undifferentiated task. Keep the original image available when reviewers inspect a prediction.
Build a review collection
Choose examples with clear labels, ambiguous content, poor quality, and missing context. Record how images were resized and how related images were separated during evaluation. Inspect failures by category and collection source, not only as one overall score. Our visual guides explain the workflow; this website does not accept uploads or classify images.
Three questions to take with you
01What exactly does the label describe?
02Could image preparation remove relevant context?
03Have related images leaked between review groups?
Reference for this topic: TensorFlow image classification tutorial. Read the original context alongside the guide.