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AgricultureBounding BoxImage Classification

Palm Oil Fruit Classification

Bounding boxes sorting palm oil fruits into four ripeness and quality grades separated by subtle colour differences.

SAMPLE PENDING

Sample frames for this project are available under NDA. Write to bilal@wortel.ai and we will share the relevant before and after pairs.

Challenges

  • Telling normal, underripe and overripe fruits apart relied on subtle visual differences.
  • Rotten fruits were hard to identify when damage or discolouration was partially hidden.
  • Densely packed fruit bunches had to be worked through carefully.
  • Overlapping and partially visible fruits complicated boundary placement.
  • Lighting conditions altered the appearance of fruit colour and maturity.
  • Variations in fruit size, colour and surface condition made consistent classification difficult.
  • Keeping class labels accurate across a large dataset required careful quality control.

Related work

SAMPLE PENDING

Cabbage Size Classification

Bounding boxes plus small, medium or large size labels on each cabbage, judged consistently despite shifting camera distance.

SAMPLE PENDING

Corn Detection & Growth Stage Classification

Bounding boxes separating large and small corn plants from weeds and ambiguous vegetation across complex field imagery.

SAMPLE PENDING

Cotton Detection & Size Classification

Cotton bolls boxed and split into regular and small classes among dense leaves, branches, and heavy occlusion.