Update README.md

README.md

@@ -88,10 +88,10 @@ snapshot_download(repo_id="aagatti/nnunet_knee", local_dir="./nnunet_knee_models
 from scripts.inference import KneeSegmentationInference
 
 # Initialize inference
-inference = KneeSegmentationInference(model_path="./nnunet_knee_models/models")
+inference = KneeSegmentationInference(model_dir="./nnunet_knee_models/models/Dataset500_KneeMRI/nnUNetTrainer__nnUNetResEncUNetMPlans__3d_cascade_fullres")
 
 # Run segmentation
-result = inference.predict("knee_mri.nii.gz", "segmentation_output.nii.gz")
+result = inference.predict("./nnunet_knee_models/test_data/test_image.nii.gz", "segmentation_output.nii.gz")
 ```
 
 ### Command Line Usage
@@ -104,7 +104,7 @@ python scripts/inference.py --input knee_mri.nii.gz --output segmentation.nii.gz
 
 For complete setup with testing and validation:
 
-1. **Clone the inference package**: [nnunet_knee inference code](https://github.com/your-repo/nnunet_knee)
+1. **Clone the inference package**: [nnunet_knee inference code](https://github.com/gattia/nnunet_knee)
 2. **Download models**: Use the code above or HuggingFace CLI
 3. **Run tests**: Validate with provided test data and DSC metrics