[CAT-151] v5.0 (#137)

* stash

* remove valid actions for now

* Update workflow.py

* args

* ???

* model training opts

* update

* move "wait" from create model group to get model group

* Update indico/queries/workflow.py

Co-authored-by: meghanhickey <[email protected]>

* Update indico/types/model_group.py

Co-authored-by: meghanhickey <[email protected]>

* fix tests and also deprecte an option we don't use

* redirect queries

* push questionnaire changes

* update workflow examples

* update docs

* refactor for adding different components

* handle model_training_options correctly

* filter content

* linked label component

* use enums, add extra examples

* Add all submissions option and submission id to document report (#146)

* pluggable ocr dataset options (#148)

* API token can be set with env variables (#147)

Co-authored-by: meghanhickey <[email protected]>
Co-authored-by: Nicolas Kassis <[email protected]>

Author: 3 people

docs/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 0f592c025ef0c8ba0f16b9350bad66ff
+config: c5cbe4a7624d7549079e7846d28d9da6
 tags: 645f666f9bcd5a90fca523b33c5a78b7

docs/_sources/model_groups.rst.txt

@@ -3,6 +3,7 @@ Model Groups
 
 .. automodule:: indico.queries.model_groups
 .. autoclass:: indico.queries.model_groups.CreateModelGroup
+.. autoclass:: indico.queries.model_groups.AddModelGroupComponent
 .. autoclass:: indico.queries.model_groups.ModelGroupPredict
 .. autoclass:: indico.queries.model_groups.GetModelGroup
 .. autoclass:: indico.queries.model_groups.GetModelGroupSelectedModelStatus

docs/_sources/object-detection.rst.txt

@@ -35,7 +35,7 @@ Uploading your Dataset and Training your Model
 ==============================================
 
 With your object detection labels in a CSV alongside either the URL to each image or the local 
-path to the image on your computer, you can create your dataset via the API::
+path to the image on your computer, you can create your dataset and workflow via the API::
 
     from indico.queries import CreateDataset
 
@@ -52,6 +52,10 @@ path to the image on your computer, you can create your dataset via the API::
 For the "files" parameter provide the path to your CSV and for the "image_filename_col" parameter
 provide the column name containing the paths/urls of your images. 
 
+Next, create a workflow under which your model will live::
+
+    new_workflow = client.call(CreateWorkflow(name="Name of your workflow", dataset_id=dataset.id))
+
 To train your model, you can use the parameters you see below and the dataset object 
 we created above::
 
@@ -63,17 +67,18 @@ we created above::
         "test_size": 0.0,
         "use_small_model": False,
     }
-
-    model_group = client.call(
-        CreateModelGroup(
-            name="My Model",
-            dataset_id=dataset.id,
-            source_column_id=dataset.datacolumn_by_name("urls").id,
-            labelset_id=dataset.labelset_by_name("label").id,
-            model_training_options=model_training_options,
-            wait=wait,
-        )
+    after_component_id = new_workflow.component_by_type("INPUT_IMAGE").id
+    create_model_request = AddModelGroupComponent(
+    name=workflow_name,
+    dataset_id=dataset.id,
+    after_component_id=after_component_id,
+    source_column_id=dataset.datacolumn_by_name("urls").id,
+    labelset_column_id=dataset.labelset_by_name("label").id,
+    workflow_id=new_workflow.id,
+    model_training_options = model_training_options
     )
+    client.call(create_model_request)
+
 
 In the code above, the "labelset_id" should be the CSV column name containing your bounding box labels
 (in the example above, we named the column "label"). The column "urls" will be automatically created 

docs/_static/basic.css

@@ -731,9 +731,8 @@ dl.glossary dt {
 
 .classifier:before {
     font-style: normal;
-    margin: 0 0.5em;
+    margin: 0.5em;
     content: ":";
-    display: inline-block;
 }
 
 abbr, acronym {
@@ -820,7 +819,7 @@ div.code-block-caption code {
 
 table.highlighttable td.linenos,
 span.linenos,
-div.highlight span.gp {  /* gp: Generic.Prompt */
+div.doctest > div.highlight span.gp {  /* gp: Generic.Prompt */
   user-select: none;
   -webkit-user-select: text; /* Safari fallback only */
   -webkit-user-select: none; /* Chrome/Safari */

docs/_static/css/theme.css

@@ -301,14 +301,12 @@ var Documentation = {
               window.location.href = prevHref;
               return false;
             }
-            break;
           case 39: // right
             var nextHref = $('link[rel="next"]').prop('href');
             if (nextHref) {
               window.location.href = nextHref;
               return false;
             }
-            break;
         }
       }
     });

docs/_static/doctools.js

@@ -282,10 +282,7 @@ var Search = {
                   complete: function(jqxhr, textstatus) {
                     var data = jqxhr.responseText;
                     if (data !== '' && data !== undefined) {
-                      var summary = Search.makeSearchSummary(data, searchterms, hlterms);
-                      if (summary) {
-                        listItem.append(summary);
-                      }
+                      listItem.append(Search.makeSearchSummary(data, searchterms, hlterms));
                     }
                     Search.output.append(listItem);
                     setTimeout(function() {
@@ -328,9 +325,7 @@ var Search = {
     var results = [];
 
     for (var prefix in objects) {
-      for (var iMatch = 0; iMatch != objects[prefix].length; ++iMatch) {
-        var match = objects[prefix][iMatch];
-        var name = match[4];
+      for (var name in objects[prefix]) {
         var fullname = (prefix ? prefix + '.' : '') + name;
         var fullnameLower = fullname.toLowerCase()
         if (fullnameLower.indexOf(object) > -1) {
@@ -344,6 +339,7 @@ var Search = {
           } else if (parts[parts.length - 1].indexOf(object) > -1) {
             score += Scorer.objPartialMatch;
           }
+          var match = objects[prefix][name];
           var objname = objnames[match[1]][2];
           var title = titles[match[0]];
           // If more than one term searched for, we require other words to be
@@ -502,9 +498,6 @@ var Search = {
    */
   makeSearchSummary : function(htmlText, keywords, hlwords) {
     var text = Search.htmlToText(htmlText);
-    if (text == "") {
-      return null;
-    }
     var textLower = text.toLowerCase();
     var start = 0;
     $.each(keywords, function() {