plant-classifier-39

Plant Classifier — EfficientNet-B3, 39 classes

Frozen PyTorch checkpoint for plant/crop classification. The model was trained with supervised contrastive pretraining, cross-entropy fine-tuning, and TrivialAugment.

Intended use

The model predicts the plant identity before a crop-specific disease detector and recommendation system. It is a plant classifier, not a disease classifier.

Input preprocessing

• Convert the image to RGB.
• Resize the longest side to 380 pixels while preserving aspect ratio.
• Pad to 380 × 380 with black pixels.
• Normalize with ImageNet mean (0.485, 0.456, 0.406) and standard deviation (0.229, 0.224, 0.225).
• Do not apply training augmentation during inference.

The checkpoint contains model and class_to_idx. Reconstruct torchvision.models.efficientnet_b3(weights=None), replace the final classifier with a 39-output linear layer, and load checkpoint["model"].

For confidence scores, apply softmax directly to the logits. The deployed API intentionally uses raw, uncalibrated probabilities.

Frozen evaluation

Files

• model.pt: frozen EfficientNet-B3 checkpoint.
• class_to_idx.json: authoritative output-index mapping.
• model_config.json: architecture and preprocessing contract.
• SHA256SUMS: checkpoint integrity checksum.
• FROZEN_MODEL.md: frozen-run provenance and metrics.