Create config.json

config.json

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+{
+  "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)."
+}