better visualization
"\n",
"we can use the `{data}.show_batch()` method to visualize a few samples of the training data. Following parameters can be used with multispectral imagery to control the visualization.\n",
"\n",
- "- `rgb_bands`: The band combination in which we want to visualize our training data, For example [2, 1, 0] or ['nir', 'g', 'b']. \n",
- "\n",
+ "- `rgb_bands`: The band combination in which we want to visualize our training data, For example [2, 1, 0] or ['nir', 'green', 'blue']. \n",
+ "- `stretch_type`: The type of stretching we want to apply to imagery in our training data for visualization.\n",
+ " - 'minmax' - Default! This stretches each image chips by min-max values.\n",
+ " - 'percentclip' - This stretched image chips by clipping histogram by .25%.\n",
"- `statistics_type`: The type of stretching we want to apply to imagery in our training data for visualization.\n",
- " - 'DRA' - stands for Dynamic Range Adjustment. This stretches each image chip using its individual min-max values instead of using global values."
+ " - 'dataset' - Default! This stretches each image chip using global statistics.\n",
+ " - 'DRA' - stands for Dynamic Range Adjustment. This stretches each image chip using its individual statistics."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "## Validate results"
+ "## Validate results\n",
+ "\n",
+ "we can use the `{model}.show_results()` method to validate a few predictions from the validation dataset and compare them with the ground truth. Following parameters can be used with multispectral imagery to control the visualization.\n",
+ "\n",
+ "- `rgb_bands`: The band combination in which we want to visualize our training data, For example [2, 1, 0] or ['nir', 'green', 'blue']. \n",
+ "- `stretch_type`: The type of stretching we want to apply to imagery in our training data for visualization.\n",
+ " - 'minmax' - Default! This stretches each image chips by min-max values.\n",
+ " - 'percentclip' - This stretched image chips by clipping histogram by .25%.\n",
+ "- `statistics_type`: The type of stretching we want to apply to imagery in our training data for visualization.\n",
+ " - 'dataset' - Default! This stretches each image chip using global statistics.\n",
+ " - 'DRA' - stands for Dynamic Range Adjustment. This stretches each image chip using its individual statistics."
]
},
{
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.6.9"
+ "version": "3.6.10"
}
},
"nbformat": 4,
