{
"metadata": {
- "name": "ImageNet classification",
"description": "Use the pre-trained ImageNet model to classify images with the Python interface.",
- "include_in_docs": true
+ "example_name": "ImageNet classification",
+ "include_in_docs": true,
+ "signature": "sha256:4f8d4c079c30d20ef4b6818e9672b1741fd1377354e5b83e291710736cecd24f"
},
"nbformat": 3,
"nbformat_minor": 0,
"metadata": {}
}
]
-}
+}
\ No newline at end of file
{
"metadata": {
- "name": "ImageNet detection",
"description": "Run a pretrained model as a detector in Python.",
- "include_in_docs": true
+ "example_name": "R-CNN detection",
+ "include_in_docs": true,
+ "signature": "sha256:8a744fbbb9ed80acab471247eaf50c27dcbd652105404df9feca599939f0c0ee"
},
"nbformat": 3,
"nbformat_minor": 0,
{
"metadata": {
- "name": "Filter visualization",
"description": "Extracting features and visualizing trained filters with an example image, viewed layer-by-layer.",
- "include_in_docs": true
+ "example_name": "Filter visualization",
+ "include_in_docs": true,
+ "signature": "sha256:b1b0457e2b10110aca847a718a3fe631ebcfce63a61cbc33653244f52b1ff4af"
},
"nbformat": 3,
"nbformat_minor": 0,
"metadata": {}
}
]
-}
+}
\ No newline at end of file
{
"metadata": {
- "name": "Editing model parameters",
"description": "How to do net surgery and manually change model parameters, making a fully-convolutional classifier for dense feature extraction.",
- "include_in_docs": true
+ "example_name": "Editing model parameters",
+ "include_in_docs": true,
+ "signature": "sha256:0b2ad61622122fa34a40c250be2c0799a85fb65c149b802ce844c46eceba066e"
},
"nbformat": 3,
"nbformat_minor": 0,
"metadata": {}
}
]
-}
+}
\ No newline at end of file