Vision GAPIC client library (#1015)

* Migrate quickstart to gapic

* formatting

* updating detect_faces, failing tests

* Migrate detect_faces to gapic

* Migrate detect_labels to gapic

* Migrate detect_landmarks to gapic

* Migrate detect_logos to gapic

* remove "Likelihood" from test outputs

* Migrate detect_safe_search to gapic

* Migrate detect_text to gapic

* Migrate detect_properties to gapic

* Migrate detect_web to gapic

* Migrate crophints to gapic

* Migrate detect_document to gapic;

* Migrate crop_hints.py to gapic

* hard code the likelihood names

* Make code snippets more self-contained

* Migrate doctext.py to gapic

* Migrate web_detect.py to gapic

* Migrate faces.py to gapic

* flake8

* fix missing string format

* remove url scores from sample output

* region tags update

* region tag correction

* move region tag in get crop hints

* move region tags

* import style

* client creation

* rename bound to vertex

* add region tags

* increment client library version

* update README to include link to the migration guide

* correct version number

* update readme

* update client library version in requirements and readme

Author: dizcology

vision/cloud-client/crop_hints/README.rst

@@ -3,7 +3,11 @@
 Google Cloud Vision API Python Samples
 ===============================================================================
 
-This directory contains samples for Google Cloud Vision API. `Google Cloud Vision API`_ allows developers to easily integrate vision detection features within applications, including image labeling, face and landmark detection, optical character recognition (OCR), and tagging of explicit content
+This directory contains samples for Google Cloud Vision API. `Google Cloud Vision API`_ allows developers to easily integrate vision detection features within applications, including image labeling, face and landmark detection, optical character recognition (OCR), and tagging of explicit content.
+
+- See the `migration guide`_ for information about migrating to Python client library v0.25.1.
+
+.. _migration guide: https://cloud.google.com/vision/docs/python-client-migration
 
 
 

vision/cloud-client/crop_hints/README.rst.in

@@ -8,7 +8,13 @@ product:
     `Google Cloud Vision API`_ allows developers to easily integrate vision
     detection features within applications, including image labeling, face and
     landmark detection, optical character recognition (OCR), and tagging of
-    explicit content
+    explicit content.
+
+
+    - See the `migration guide`_ for information about migrating to Python client library v0.25.1.
+
+
+    .. _migration guide: https://cloud.google.com/vision/docs/python-client-migration
 
 setup:
 - auth

vision/cloud-client/crop_hints/crop_hints.py

@@ -26,24 +26,33 @@
 import io
 
 from google.cloud import vision
+from google.cloud.vision import types
 from PIL import Image, ImageDraw
 # [END imports]
 
 
 def get_crop_hint(path):
     # [START get_crop_hint]
     """Detect crop hints on a single image and return the first result."""
-    vision_client = vision.Client()
+    client = vision.ImageAnnotatorClient()
 
     with io.open(path, 'rb') as image_file:
         content = image_file.read()
 
-    image = vision_client.image(content=content)
+    image = types.Image(content=content)
 
-    # Return bounds for the first crop hint using an aspect ratio of 1.77.
-    return image.detect_crop_hints({1.77})[0].bounds.vertices
+    crop_hints_params = types.CropHintsParams(aspect_ratios=[1.77])
+    image_context = types.ImageContext(crop_hints_params=crop_hints_params)
+
+    response = client.crop_hints(image=image, image_context=image_context)
+    hints = response.crop_hints_annotation.crop_hints
+
+    # Get bounds for the first crop hint using an aspect ratio of 1.77.
+    vertices = hints[0].bounding_poly.vertices
     # [END get_crop_hint]
 
+    return vertices
+
 
 def draw_hint(image_file):
     """Draw a border around the image using the hints in the vector list."""
@@ -53,10 +62,10 @@ def draw_hint(image_file):
     im = Image.open(image_file)
     draw = ImageDraw.Draw(im)
     draw.polygon([
-        vects[0].x_coordinate, vects[0].y_coordinate,
-        vects[1].x_coordinate, vects[1].y_coordinate,
-        vects[2].x_coordinate, vects[2].y_coordinate,
-        vects[3].x_coordinate, vects[3].y_coordinate], None, 'red')
+        vects[0].x, vects[0].y,
+        vects[1].x, vects[1].y,
+        vects[2].x, vects[2].y,
+        vects[3].x, vects[3].y], None, 'red')
     im.save('output-hint.jpg', 'JPEG')
     # [END draw_hint]
 
@@ -67,8 +76,8 @@ def crop_to_hint(image_file):
     vects = get_crop_hint(image_file)
 
     im = Image.open(image_file)
-    im2 = im.crop([vects[0].x_coordinate, vects[0].y_coordinate,
-                  vects[2].x_coordinate - 1, vects[2].y_coordinate - 1])
+    im2 = im.crop([vects[0].x, vects[0].y,
+                  vects[2].x - 1, vects[2].y - 1])
     im2.save('output-crop.jpg', 'JPEG')
     # [END crop_to_hint]
 

vision/cloud-client/detect/README.rst

@@ -3,7 +3,11 @@
 Google Cloud Vision API Python Samples
 ===============================================================================
 
-This directory contains samples for Google Cloud Vision API. `Google Cloud Vision API`_ allows developers to easily integrate vision detection features within applications, including image labeling, face and landmark detection, optical character recognition (OCR), and tagging of explicit content
+This directory contains samples for Google Cloud Vision API. `Google Cloud Vision API`_ allows developers to easily integrate vision detection features within applications, including image labeling, face and landmark detection, optical character recognition (OCR), and tagging of explicit content.
+
+- See the `migration guide`_ for information about migrating to Python client library v0.25.1.
+
+.. _migration guide: https://cloud.google.com/vision/docs/python-client-migration
 
 
 

vision/cloud-client/detect/README.rst.in

@@ -8,7 +8,13 @@ product:
     `Google Cloud Vision API`_ allows developers to easily integrate vision
     detection features within applications, including image labeling, face and
     landmark detection, optical character recognition (OCR), and tagging of
-    explicit content
+    explicit content.
+
+
+    - See the `migration guide`_ for information about migrating to Python client library v0.25.1.
+
+
+    .. _migration guide: https://cloud.google.com/vision/docs/python-client-migration
 
 setup:
 - auth