[formrecognizer] Update doc strings for v3 (Azure#20920)

* update docs based on Paul's feedback

* improve bounding region docs

* sample fixes

* review feedback

* spelling

sdk/formrecognizer/azure-ai-formrecognizer/azure/ai/formrecognizer/_document_analysis_client.py

@@ -86,8 +86,8 @@ def begin_analyze_document(self, model, document, **kwargs):
         :keyword str pages: Custom page numbers for multi-page documents(PDF/TIFF). Input the page numbers
             and/or ranges of pages you want to get in the result. For a range of pages, use a hyphen, like
             `pages="1-3, 5-6"`. Separate each page number or range with a comma.
-        :keyword str locale: Locale of the document. Supported locales include: en-US, en-AU, en-CA, en-GB,
-            and en-IN.
+        :keyword str locale: Locale hint of the input document.
+            See supported locales here: https://aka.ms/azsdk/formrecognizer/supportedlocales.
         :keyword str continuation_token: A continuation token to restart a poller from a saved state.
         :return: An instance of an LROPoller. Call `result()` on the poller
             object to return a :class:`~azure.ai.formrecognizer.AnalyzeResult`.
@@ -137,13 +137,13 @@ def begin_analyze_document_from_url(self, model, document_url, **kwargs):
             Use this to specify the custom model ID or prebuilt model ID. Prebuilt model IDs to use are:
             "prebuilt-receipt", "prebuilt-invoice", "prebuilt-idDocument", "prebuilt-businessCard",
             "prebuilt-document", "prebuilt-layout".
-        :param str document_url: The URL of the document to analyze. The input must be a valid, encoded URL
-            of one of the supported formats: JPEG, PNG, PDF, TIFF, or BMP.
+        :param str document_url: The URL of the document to analyze. The input must be a valid, encoded, and
+            publicly accessible URL of one of the supported formats: JPEG, PNG, PDF, TIFF, or BMP.
         :keyword str pages: Custom page numbers for multi-page documents(PDF/TIFF). Input the page numbers
             and/or ranges of pages you want to get in the result. For a range of pages, use a hyphen, like
             `pages="1-3, 5-6"`. Separate each page number or range with a comma.
-        :keyword str locale: Locale of the document. Supported locales include: en-US, en-AU, en-CA, en-GB,
-            and en-IN.
+        :keyword str locale: Locale hint of the input document.
+            See supported locales here: https://aka.ms/azsdk/formrecognizer/supportedlocales.
         :keyword str continuation_token: A continuation token to restart a poller from a saved state.
         :return: An instance of an LROPoller. Call `result()` on the poller
             object to return a :class:`~azure.ai.formrecognizer.AnalyzeResult`.

sdk/formrecognizer/azure-ai-formrecognizer/azure/ai/formrecognizer/_models.py

@@ -2071,7 +2071,8 @@ class BoundingRegion(object):
     :ivar list[~azure.ai.formrecognizer.Point] bounding_box:
         A list of 4 points representing the quadrilateral bounding box
         that outlines the text. The points are listed in clockwise
-        order: top-left, top-right, bottom-right, bottom-left.
+        order relative to the text orientation: top-left, top-right,
+        bottom-right, bottom-left.
         Units are in pixels for images and inches for PDF.
     :ivar int page_number:
         The 1-based number of the page in which this content is present.

sdk/formrecognizer/azure-ai-formrecognizer/azure/ai/formrecognizer/aio/_document_analysis_client_async.py

@@ -92,8 +92,8 @@ async def begin_analyze_document(
         :keyword str pages: Custom page numbers for multi-page documents(PDF/TIFF). Input the page numbers
             and/or ranges of pages you want to get in the result. For a range of pages, use a hyphen, like
             `pages="1-3, 5-6"`. Separate each page number or range with a comma.
-        :keyword str locale: Locale of the document. Supported locales include: en-US, en-AU, en-CA, en-GB,
-            and en-IN.
+        :keyword str locale: Locale hint of the input document.
+            See supported locales here: https://aka.ms/azsdk/formrecognizer/supportedlocales.
         :keyword str continuation_token: A continuation token to restart a poller from a saved state.
         :return: An instance of an AsyncLROPoller. Call `result()` on the poller
             object to return a :class:`~azure.ai.formrecognizer.AnalyzeResult`.
@@ -144,13 +144,13 @@ async def begin_analyze_document_from_url(
             Use this to specify the custom model ID or prebuilt model ID. Prebuilt model IDs to use are:
             "prebuilt-receipt", "prebuilt-invoice", "prebuilt-idDocument", "prebuilt-businessCard",
             "prebuilt-document", "prebuilt-layout".
-        :param str document_url: The URL of the document to analyze. The input must be a valid, encoded URL
-            of one of the supported formats: JPEG, PNG, PDF, TIFF, or BMP.
+        :param str document_url: The URL of the document to analyze. The input must be a valid, encoded, and
+            publicly accessible URL of one of the supported formats: JPEG, PNG, PDF, TIFF, or BMP.
         :keyword str pages: Custom page numbers for multi-page documents(PDF/TIFF). Input the page numbers
             and/or ranges of pages you want to get in the result. For a range of pages, use a hyphen, like
             `pages="1-3, 5-6"`. Separate each page number or range with a comma.
-        :keyword str locale: Locale of the document. Supported locales include: en-US, en-AU, en-CA, en-GB,
-            and en-IN.
+        :keyword str locale: Locale hint of the input document.
+            See supported locales here: https://aka.ms/azsdk/formrecognizer/supportedlocales.
         :keyword str continuation_token: A continuation token to restart a poller from a saved state.
         :return: An instance of an AsyncLROPoller. Call `result()` on the poller
             object to return a :class:`~azure.ai.formrecognizer.AnalyzeResult`.

sdk/formrecognizer/azure-ai-formrecognizer/samples/v3.2-beta/sample_analyze_custom_documents.py

@@ -61,8 +61,8 @@ def analyze_custom_documents(custom_model_id):
     for idx, document in enumerate(result.documents):
         print("--------Analyzing document #{}--------".format(idx + 1))
         print("Document has type {}".format(document.doc_type))
-        print("Document has document type confidence {}".format(document.confidence))
-        print("Document was analyzed with model with ID {}".format(result.model_id))
+        print("Document has confidence {}".format(document.confidence))
+        print("Document was analyzed by model with ID {}".format(result.model_id))
         for name, field in document.fields.items():
             field_value = field.value if field.value else field.content
             print("......found field of type '{}' with value '{}' and with confidence {}".format(field.value_type, field_value, field.confidence))
@@ -79,22 +79,20 @@ def analyze_custom_documents(custom_model_id):
                     word.content, word.confidence
                 )
             )
-        if page.selection_marks:
-            print("\nSelection marks found on page {}".format(page.page_number))
-            for selection_mark in page.selection_marks:
-                print(
-                    "...Selection mark is '{}' and has a confidence of {}".format(
-                        selection_mark.state, selection_mark.confidence
-                    )
+        for selection_mark in page.selection_marks:
+            print(
+                "...Selection mark is '{}' and has a confidence of {}".format(
+                    selection_mark.state, selection_mark.confidence
                 )
+            )
 
     for i, table in enumerate(result.tables):
         print("\nTable {} can be found on page:".format(i + 1))
         for region in table.bounding_regions:
             print("...{}".format(i + 1, region.page_number))
         for cell in table.cells:
             print(
-                "...Cell[{}][{}] has text '{}'".format(
+                "...Cell[{}][{}] has content '{}'".format(
                     cell.row_index, cell.column_index, cell.content
                 )
             )

sdk/formrecognizer/azure-ai-formrecognizer/samples/v3.2-beta/sample_analyze_document.py

@@ -70,8 +70,8 @@ def analyze_document():
             )
         )
 
-    for idx, page in enumerate(result.pages):
-        print("----Analyzing document from page #{}----".format(idx + 1))
+    for page in result.pages:
+        print("----Analyzing document from page #{}----".format(page.page_number))
         print(
             "Page has width: {} and height: {}, measured with unit: {}".format(
                 page.width, page.height, page.unit
@@ -80,7 +80,7 @@ def analyze_document():
 
         for line_idx, line in enumerate(page.lines):
             print(
-                "Line # {} has text content '{}' within bounding box '{}'".format(
+                "...Line # {} has text content '{}' within bounding box '{}'".format(
                     line_idx,
                     line.content,
                     format_bounding_box(line.bounding_box),
@@ -96,7 +96,7 @@ def analyze_document():
 
         for selection_mark in page.selection_marks:
             print(
-                "Selection mark is '{}' within bounding box '{}' and has a confidence of {}".format(
+                "...Selection mark is '{}' within bounding box '{}' and has a confidence of {}".format(
                     selection_mark.state,
                     format_bounding_box(selection_mark.bounding_box),
                     selection_mark.confidence,
@@ -119,7 +119,7 @@ def analyze_document():
             )
         for cell in table.cells:
             print(
-                "...Cell[{}][{}] has text '{}'".format(
+                "...Cell[{}][{}] has content '{}'".format(
                     cell.row_index,
                     cell.column_index,
                     cell.content,
@@ -134,14 +134,14 @@ def analyze_document():
                 )
 
     print("----Entities found in document----")
-    for idx, entity in enumerate(result.entities):
+    for entity in result.entities:
         print("Entity of category '{}' with sub-category '{}'".format(entity.category, entity.sub_category))
         print("...has content '{}'".format(entity.content))
         print("...within '{}' bounding regions".format(format_bounding_region(entity.bounding_regions)))
         print("...with confidence {}".format(entity.confidence))
 
     print("----Key-value pairs found in document----")
-    for idx, kv_pair in enumerate(result.key_value_pairs):
+    for kv_pair in result.key_value_pairs:
         if kv_pair.key:
             print(
                     "Key '{}' found within '{}' bounding regions".format(

sdk/formrecognizer/azure-ai-formrecognizer/samples/v3.2-beta/sample_analyze_layout.py

@@ -66,8 +66,8 @@ def analyze_layout():
             )
         )
 
-    for idx, page in enumerate(result.pages):
-        print("----Analyzing layout from page #{}----".format(idx + 1))
+    for page in result.pages:
+        print("----Analyzing layout from page #{}----".format(page.page_number))
         print(
             "Page has width: {} and height: {}, measured with unit: {}".format(
                 page.width, page.height, page.unit
@@ -76,7 +76,7 @@ def analyze_layout():
 
         for line_idx, line in enumerate(page.lines):
             print(
-                "Line # {} has text content '{}' within bounding box '{}'".format(
+                "...Line # {} has text content '{}' within bounding box '{}'".format(
                     line_idx,
                     line.content,
                     format_bounding_box(line.bounding_box),
@@ -92,7 +92,7 @@ def analyze_layout():
 
         for selection_mark in page.selection_marks:
             print(
-                "Selection mark is '{}' within bounding box '{}' and has a confidence of {}".format(
+                "...Selection mark is '{}' within bounding box '{}' and has a confidence of {}".format(
                     selection_mark.state,
                     format_bounding_box(selection_mark.bounding_box),
                     selection_mark.confidence,
@@ -115,7 +115,7 @@ def analyze_layout():
             )
         for cell in table.cells:
             print(
-                "...Cell[{}][{}] has text '{}'".format(
+                "...Cell[{}][{}] has content '{}'".format(
                     cell.row_index,
                     cell.column_index,
                     cell.content,