Tomato-leaf-Segmentation

An Interactive model designed for auto-segmentation for domain specific: Tomato Leaf segmentation.

Model Description

This model is a U-Net with a lightweight MobileNetV2 backbone, designed for interactive segmentation. It takes a 4-channel input (RGB image + user scribble) and outputs a binary segmentation mask. This model was trained on the LeafNet75/Annotated_Benchmarks400 dataset.

Training Performance

The model was trained for 60 epochs with early stopping (patience=10).

Final Validation Metrics:

  • Loss: 0.0261
  • Dice Score: 0.9475
  • IoU (Jaccard): 0.9475
  • Precision: 0.9711
  • Recall: 0.9750

Training History

Training Plots

Sample Predictions

Sample Predictions

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Dataset used to train Subh775/Tomato-leaf-Segmentation