diff --git a/docs/hyperdatasets/dataviews.md b/docs/hyperdatasets/dataviews.md index 108b4513..1f26a841 100644 --- a/docs/hyperdatasets/dataviews.md +++ b/docs/hyperdatasets/dataviews.md @@ -146,6 +146,8 @@ You can retrieve the Dataview frames using [`DataView.to_list()`](../references/ This example uses an ROI query to filter for frames containing at least one ROI with the label `cat`: ```python +from allegroai import DataView, IterationOrder + # Create a Dataview object for an iterator that randomly returns frames according to queries myDataView = DataView(iteration_order=IterationOrder.random, iteration_infinite=False) @@ -166,6 +168,8 @@ list_of_frames = myDataView.to_list() This example uses an ROI query to filter for frames containing at least one ROI with either the label `cat` OR the label `dog`: ```python +from allegroai import DataView + # Add a query for a Dataset version myDataView.add_query( dataset_name='myDataset', @@ -189,6 +193,8 @@ list_of_frames = myDataView.to_list() This example uses an ROI query to filter for frames containing at least one ROI with both the label `Car` AND the label `partly_occluded`: ```python +from allegroai import DataView + # Add a query for a Dataset version myDataView.add_query( dataset_name='myDataset', @@ -207,6 +213,8 @@ This example uses an ROI query to filter for frames containing at least one ROI have the label `partly_occluded`: ```python +from allegroai import DataView + # Add a query for a Dataset version # Use a Lucene Query # "label" is a key in the rois dictionary of a frame @@ -229,6 +237,8 @@ ROI with the label `Person`. The example demonstrates using the `roi_queries` pa with a list of [`DataView.RoiQuery`](../references/hyperdataset/dataview.md#roiquery) objects: ```python +from allegroai import DataView + myDataview = DataView() myDataview.add_multi_query( dataset_id=self._dataset_id, @@ -247,6 +257,8 @@ contain ROIs with the label `Person`. To exclude an ROI, pass `must_not=True` in object. ```python +from allegroai import DataView + myDataview = DataView() myDataview.add_multi_query( dataset_id=self._dataset_id, @@ -266,6 +278,8 @@ This example demonstrates an ROI query filtering for frames containing the ROI l from two versions of one Dataset, and one version of another Dataset: ```python +from allegroai import DataView + # Add queries: # The 1st Dataset version @@ -310,6 +324,8 @@ They use the same logical OR, AND, NOT AND matching as ROI queries. This example demonstrates a frame query filtering for frames containing the meta key `city` value of `bremen`: ```python +from allegroai import DataView + # Add a frame query for frames with the meta key "city" value of "bremen" myDataView.add_query( dataset_name='myDataset', @@ -388,6 +404,8 @@ This example demonstrates creating a Dataview and setting its parameters to iter manually terminated: ```python +from allegroai import DataView, IterationOrder + # Create a Dataview object for an iterator that returns frames myDataView = DataView() @@ -399,6 +417,8 @@ myDataView.set_iteration_parameters(order=IterationOrder.random, infinite=True) This example demonstrates creating a DataView and setting its parameters to iterate and return all frames matching a query: ```python +from allegroai import DataView, IterationOrder + # Create a Dataview object for an iterator for frames myDataView = DataView(iteration_order=IterationOrder.random, iteration_infinite=False) @@ -425,6 +445,8 @@ This example demonstrates creating a Dataview and setting its parameters to iter Dataset version contains fewer than that number of frames matching the query, then fewer are returned by the iterator. ```python +from allegroai import DataView, IterationOrder + # Create a Dataview object for an iterator for frames myDataView = DataView(iteration_order=IterationOrder.random, iteration_infinite=True) @@ -447,6 +469,8 @@ This example adjusts an imbalance in the input data to improve training for `Car one ROI labeled with both `Car` and `largely_occluded` will be input. ```python +from allegroai import DataView, IterationOrder + myDataView = DataView(iteration_order=IterationOrder.random, iteration_infinite=True) myDataView.add_query( @@ -478,6 +502,8 @@ then use the labels you map **to** when setting enumeration values. For example, if the labels `truck`, `van`, and `car` are mapped **to** `vehicle`, then set enumeration for `vehicle`. ```python +from allegroai import DataView, IterationOrder + # Create a Dataview object for an iterator that randomly returns frames according to queries myDataView = DataView(iteration_order=IterationOrder.random, iteration_infinite=True) @@ -528,6 +554,8 @@ third uses `Car` (upper case "C"). The example maps `Car` (upper case "C") to `car` (lower case "c"): ```python +from allegroai import DataView, IterationOrder + # Create a Dataview object for an iterator that randomly returns frames according to queries myDataView = DataView(iteration_order=IterationOrder.random, iteration_infinite=True) @@ -567,6 +595,8 @@ Dataview objects can be retrieved by the Dataview ID or name using the [`DataVie class method. ```python +from allegroai import DataView + my_dataview = DataView.get(dataview_id='') ``` diff --git a/docs/hyperdatasets/webapp/webapp_dataviews.md b/docs/hyperdatasets/webapp/webapp_dataviews.md index a1bf2111..73e1d821 100644 --- a/docs/hyperdatasets/webapp/webapp_dataviews.md +++ b/docs/hyperdatasets/webapp/webapp_dataviews.md @@ -1,5 +1,5 @@ --- -title: The Dataview table +title: The Dataview Table --- The **Dataview table** is a [customizable](#customizing-the-dataview-table) list of Dataviews associated with a project. diff --git a/docs/img/apps_llama_form.png b/docs/img/apps_llama_form.png index 12bb2be3..d2ef9441 100644 Binary files a/docs/img/apps_llama_form.png and b/docs/img/apps_llama_form.png differ diff --git a/docs/img/apps_llama_form_dark.png b/docs/img/apps_llama_form_dark.png new file mode 100644 index 00000000..a25a4e39 Binary files /dev/null and b/docs/img/apps_llama_form_dark.png differ diff --git a/docs/release_notes/clearml_agent/ver_0_12.md b/docs/release_notes/clearml_agent/ver_0_12.md index 5b2f1d51..38e95cd3 100644 --- a/docs/release_notes/clearml_agent/ver_0_12.md +++ b/docs/release_notes/clearml_agent/ver_0_12.md @@ -22,7 +22,7 @@ title: Version 0.12 * Windows support! YES, you can now have Windows machines as part of your cluster (notice --docker is not supported on Windows). * Add initial Conda package manager support (still in beta). * Add --gpus and --cpu-only for easier GPU control when running multiple `trains-agent` instances on the same machine. -* [python_binary](https://github.com/clearml/clearml-agent/blob/master/docs/trains.conf#L35) can now be specified (the default is the same Python binary executing the `trains-agent`). +* [python_binary](https://github.com/clearml/clearml-agent/blob/831b36c4246bb4dfe150407461e0d01166bc6e92/docs/trains.conf#L35) can now be specified (the default is the same Python binary executing the `trains-agent`). * Fix Issue ([GitHub Issue #2](https://github.com/clearml/clearml-agent/issues/2)). ### Trains Agent 0.12.0 diff --git a/docs/webapp/applications/apps_llama_deployment.md b/docs/webapp/applications/apps_llama_deployment.md index 2819882c..e44fb2fd 100644 --- a/docs/webapp/applications/apps_llama_deployment.md +++ b/docs/webapp/applications/apps_llama_deployment.md @@ -80,6 +80,7 @@ values from the file, which can be modified before launching the app instance
-![llama deployment app form](../../img/apps_llama_form.png) +![llama deployment app form](../../img/apps_llama_form.png#light-mode-only) +![llama deployment app form](../../img/apps_llama_form.png#dark-mode-only)
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