Updates to examples (#1022)

nfnet update
3dunet requirements via pip
3dunet requirement and nb-clean

examples/vision/python_3dunet/3dunet_inference.ipynb

@@ -10,6 +10,16 @@
     "https://github.com/naomifridman/Unet_Brain_tumor_segmentation"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "09ceec31",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install SimpleITK matplotlib scikit-image"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,

examples/vision/python_nfnet/nfnet_inference.ipynb

@@ -17,7 +17,9 @@
     "- How to optimize NFNet ONNX model with AMD MIGraphX.\n",
     "- How to run inference on AMD GPU with the optimized ONNX model.\n",
     "\n",
-    "The NFNet utilized in this example is the smallest NFNet version, F0: 71.5M parameters (83.6% top-1 accuracy on ImageNet)"
+    "The NFNet utilized in this example is the smallest NFNet version, F0: 71.5M parameters (83.6% top-1 accuracy on ImageNet)\n",
+    "\n",
+    "Please make sure MIGraphX Python API is installed following the instructions at Github page."
    ]
   },
   {
@@ -107,7 +109,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "with open('../python_api_inference/imagenet_simple_labels.json') as json_data:\n",
+    "with open('../python_resnet50/imagenet_simple_labels.json') as json_data:\n",
     "    labels = json.load(json_data)"
    ]
   },

examples/vision/python_nfnet/requirements_nfnet.txt

 opencv-python
-onnxruntime
+onnxruntime
\ No newline at end of file
+image
\ No newline at end of file