| { | |
| "model_type": "resnet", | |
| "task": "image-classification", | |
| "framework": "pytorch", | |
| "pipeline_tag": "image-classification", | |
| "num_classes": 3, | |
| "class_labels": ["fa", "p_def", "blb"], | |
| "input_shape": [224, 224, 3], | |
| "preprocessing": { | |
| "resize": 256, | |
| "center_crop": 224, | |
| "normalize": [0.485, 0.456, 0.406], | |
| "normalize_std": [0.229, 0.224, 0.225] | |
| }, | |
| "metrics": { | |
| "validation_accuracy": "93.82%", | |
| "per_class_accuracy": { | |
| "fa": "100.00%", | |
| "p_def": "86.21%", | |
| "blb": "95.00%" | |
| } | |
| }, | |
| "license": "apache-2.0", | |
| "tags": [ | |
| "image-classification", | |
| "crop-anomaly-detection", | |
| "agriculture", | |
| "resnet50", | |
| "deep-learning" | |
| ], | |
| "description": "ResNet50 model for 3-class anomaly detection. The model classifies images as Fall Armyworm (fa), Phosphorus Deficiency (p_def), or Bacterial Leaf Blight (blb)." | |
| } | |