def import_product_sets(project_id, location, gcs_uri):
"""Import images of different products in the product set.
Args:
project_id: Id of the project.
location: A compute region name.
gcs_uri: Google Cloud Storage URI.
Target files must be in Product Search CSV format.
"""
client = vision.ProductSearchClient()
# A resource that represents Google Cloud Platform location.
location_path = f"projects/{project_id}/locations/{location}"
# Set the input configuration along with Google Cloud Storage URI
gcs_source = vision.ImportProductSetsGcsSource(csv_file_uri=gcs_uri)
input_config = vision.ImportProductSetsInputConfig(gcs_source=gcs_source)
# Import the product sets from the input URI.
response = client.import_product_sets(parent=location_path,
input_config=input_config)
print('Processing operation name: {}'.format(response.operation.name))
# synchronous check of operation status
result = response.result()
print('Processing done.')
for i, status in enumerate(result.statuses):
print('Status of processing line {} of the csv: {}'.format(i, status))
# Check the status of reference image
# `0` is the code for OK in google.rpc.Code.
if status.code == 0:
reference_image = result.reference_images[i]
print(reference_image)
else:
print('Status code not OK: {}'.format(status.message))
def purge_products_in_product_set(project_id, location, product_set_id, force):
"""Delete all products in a product set.
Args:
project_id: Id of the project.
location: A compute region name.
product_set_id: Id of the product set.
force: Perform the purge only when force is set to True.
"""
client = vision.ProductSearchClient()
parent = client.location_path(
project=project_id, location=location)
product_set_purge_config = vision.types.ProductSetPurgeConfig(
product_set_id=product_set_id)
# The purge operation is async.
operation = client.purge_products(
parent=parent,
product_set_purge_config=product_set_purge_config,
# The operation is irreversible and removes multiple products.
# The user is required to pass in force=True to actually perform the
# purge.
# If force is not set to True, the service raises an exception.
force=force)
operation.result(timeout=120)
print('Deleted products in product set.')
def create_product(project_id, location, product_id, product_display_name,
product_category):
"""Create one product.
Args:
project_id: Id of the project.
location: A compute region name.
product_id: Id of the product.
product_display_name: Display name of the product.
product_category: Category of the product.
"""
client = vision.ProductSearchClient()
# A resource that represents Google Cloud Platform location.
location_path = client.location_path(project=project_id, location=location)
# Create a product with the product specification in the region.
# Set product display name and product category.
product = vision.types.Product(display_name=product_display_name,
product_category=product_category)
# The response is the product with the `name` field populated.
response = client.create_product(parent=location_path,
product=product,
product_id=product_id)
# Display the product information.
print('Product name: {}'.format(response.name))
def update_product_labels(project_id, location, product_id, key, value):
"""Update the product labels.
Args:
project_id: Id of the project.
location: A compute region name.
product_id: Id of the product.
key: The key of the label.
value: The value of the label.
"""
client = vision.ProductSearchClient()
# Get the name of the product.
product_path = client.product_path(project=project_id,
location=location,
product=product_id)
# Set product name, product label and product display name.
# Multiple labels are also supported.
key_value = vision.types.Product.KeyValue(key=key, value=value)
product = vision.types.Product(name=product_path,
product_labels=[key_value])
# Updating only the product_labels field here.
update_mask = vision.types.FieldMask(paths=['product_labels'])
# This overwrites the product_labels.
updated_product = client.update_product(product=product,
update_mask=update_mask)
# Display the updated product information.
print('Product name: {}'.format(updated_product.name))
print('Updated product labels: {}'.format(product.product_labels))
def add_product_to_product_set(project_id, location, product_id,
product_set_id):
"""Add a product to a product set.
Args:
project_id: Id of the project.
location: A compute region name.
product_id: Id of the product.
product_set_id: Id of the product set.
"""
client = vision.ProductSearchClient()
# Get the full path of the product set.
product_set_path = client.product_set_path(project=project_id,
location=location,
product_set=product_set_id)
# Get the full path of the product.
product_path = client.product_path(project=project_id,
location=location,
product=product_id)
# Add the product to the product set.
client.add_product_to_product_set(name=product_set_path,
product=product_path)
print('Product added to product set.')
def import_product_sets(project_id, location, gcs_uri):
"""Import images of different products in the product set.
Args:
project_id: Id of the project.
location: A compute region name.
gcs_uri: Google Cloud Storage URI.
Target files must be in Product Search CSV format.
"""
client = vision.ProductSearchClient()
# A resource that represents Google Cloud Platform location.
location_path = client.location_path(project=project_id, location=location)
# Set the input configuration along with Google Cloud Storage URI
gcs_source = vision.types.ImportProductSetsGcsSource(csv_file_uri=gcs_uri)
input_config = vision.types.ImportProductSetsInputConfig(
gcs_source=gcs_source)
# Import the product sets from the input URI.
response = client.import_product_sets(parent=location_path,
input_config=input_config)
print('Processing operation name: {}'.format(response.operation.name))
# synchronous check of operation status
result = response.result()
print('Processing done.')
def purge_orphan_products(project_id, location, force):
"""Delete all products not in any product sets.
Args:
project_id: Id of the project.
location: A compute region name.
"""
client = vision.ProductSearchClient()
parent = f"projects/{project_id}/locations/{location}"
# The purge operation is async.
operation = client.purge_products(
request={
"parent": parent,
"delete_orphan_products": True,
# The operation is irreversible and removes multiple products.
# The user is required to pass in force=True to actually perform the
# purge.
# If force is not set to True, the service raises an exception.
"force": force
})
operation.result(timeout=500)
print('Orphan products deleted.')
def get_similar_products_file(
project_id, location, product_set_id, product_category,
file_path, filter):
"""Search similar products to image.
Args:
project_id: Id of the project.
location: A compute region name.
product_set_id: Id of the product set.
product_category: Category of the product.
file_path: Local file path of the image to be searched.
filter: Condition to be applied on the labels.
Example for filter: (color = red OR color = blue) AND style = kids
It will search on all products with the following labels:
color:red AND style:kids
color:blue AND style:kids
"""
# product_search_client is needed only for its helper methods.
product_search_client = vision.ProductSearchClient()
image_annotator_client = vision.ImageAnnotatorClient()
# Read the image as a stream of bytes.
with open(file_path, 'rb') as image_file:
content = image_file.read()
# Create annotate image request along with product search feature.
image = vision.Image(content=content)
# product search specific parameters
product_set_path = product_search_client.product_set_path(
project=project_id, location=location,
product_set=product_set_id)
product_search_params = vision.ProductSearchParams(
product_set=product_set_path,
product_categories=[product_category],
filter=filter)
image_context = vision.ImageContext(
product_search_params=product_search_params)
# Search products similar to the image.
response = image_annotator_client.product_search(
image, image_context=image_context)
index_time = response.product_search_results.index_time
print('Product set index time: ')
print(index_time)
results = response.product_search_results.results
print('Search results:')
for result in results:
product = result.product
print('Score(Confidence): {}'.format(result.score))
print('Image name: {}'.format(result.image))
print('Product name: {}'.format(product.name))
print('Product display name: {}'.format(
product.display_name))
print('Product description: {}\n'.format(product.description))
print('Product labels: {}\n'.format(product.product_labels))
def create_product_set(project_id, location, product_set_id1, product_set_display_name):
"""Create a product set.
Args:
project_id: Id of the project.
location: A compute region name.
product_set_id: Id of the product set.
product_set_display_"name": Display name of the product set.
"""
client = vision.ProductSearchClient()
# A resource that represents Google Cloud Platform location.
location_path = client.location_path(
project=project_id, location=location)
# Create a product set with the product set specification in the region.
product_set = vision.types.ProductSet(
display_name=product_set_display_name)
# The response is the product set with `name` populated.
response = client.create_product_set(
parent=location_path,
product_set=product_set,
product_set_id=product_set_id1)
prodSet_to_prods[product_set_id1] = []
# Display the product set information.
print('Product set "name": {}'.format(response.name))
def get_reference_image(project_id, location, product_id, reference_image_id):
"""Get info about a reference image.
Args:
project_id: Id of the project.
location: A compute region name.
product_id: Id of the product.
reference_image_id: Id of the reference image.
"""
client = vision.ProductSearchClient()
# Get the full path of the reference image.
reference_image_path = client.reference_image_path(
project=project_id,
location=location,
product=product_id,
reference_image=reference_image_id)
# Get complete detail of the reference image.
image = client.get_reference_image(name=reference_image_path)
# Display the reference image information.
print('Reference image name: {}'.format(image.name))
print('Reference image id: {}'.format(image.name.split('/')[-1]))
print('Reference image uri: {}'.format(image.uri))
print('Reference image bounding polygons: {}'.format(image.bounding_polys))
return image
def list_products_in_product_set(project_id, location, product_set_id):
"""List all products in a product set.
Args:
project_id: Id of the project.
location: A compute region name.
product_set_id: Id of the product set.
"""
client = vision.ProductSearchClient()
# Get the full path of the product set.
product_set_path = client.product_set_path(project=project_id,
location=location,
product_set=product_set_id)
# List all the products available in the product set.
products = client.list_products_in_product_set(name=product_set_path)
# Display the product information.
for product in products:
print('Product name: {}'.format(product.name))
print('Product id: {}'.format(product.name.split('/')[-1]))
print('Product display name: {}'.format(product.display_name))
print('Product description: {}'.format(product.description))
print('Product category: {}'.format(product.product_category))
print('Product labels: {}'.format(product.product_labels))
def import_product_sets(project_id, location, gcs_uri):
client = vision.ProductSearchClient()
# A resource that represents Google Cloud Platform location
# location_path = client.location_path(project=project_id, location=location)
# Set the input configuration along with Google Cloud Storage URI
gcs_source = vision.types.ImportProductSetsGcsSource(csv_file_uri=gcs_uri)
input_config = vision.types.ImportProductSetsInputConfig(
gcs_source=gcs_source)
# Import the product sets from the input URI.
response = client.import_product_sets(
parent=location_path(project_id=project_id, location=location), input_config=input_config)
print('Procseeing operation name : {}', format(response.operation.name))
# synchronous check of operation status
result = response.result()
print('Processing done.')
for i, status in enumerate(result.statuses):
# print('Status of processing line {} of the csv: {}', format(i, status))
# Check the status of reference image
# '0' is the code for OK in google.rpc.Code.
if status.code == 0:
reference_image = result.reference_images[i]
print(reference_image)
else:
print('Status code not OK: {}', format(status.message))
def create_reference_image(project_id, location, product_id, reference_image_id, gcs_uri):
"""Create a reference image.
Args:
project_id: Id of the project.
location: A compute region name.
product_id: Id of the product.
reference_image_id: Id of the reference image.
gcs_"uri": Google Cloud Storage path of the input image.
"""
client = vision.ProductSearchClient()
# Get the full path of the product.
product_path = client.product_path(
project=project_id, location=location, product=product_id)
# Create a reference image.
reference_image = vision.types.ReferenceImage(uri=gcs_uri)
# The response is the reference image with `name` populated.
image = client.create_reference_image(
parent=product_path,
reference_image=reference_image,
reference_image_id=reference_image_id)
# Display the reference image information.
print('Reference image "name": {}'.format(image.name))
print('Reference image "uri": {}'.format(image.uri))
def remove_product_from_product_set(project_id, location, product_id,
product_set_id):
"""Remove a product from a product set.
Args:
project_id: Id of the project.
location: A compute region name.
product_id: Id of the product.
product_set_id: Id of the product set.
"""
client = vision.ProductSearchClient()
# Get the full path of the product set.
product_set_path = client.product_set_path(project=project_id,
location=location,
product_set=product_set_id)
# Get the full path of the product.
product_path = client.product_path(project=project_id,
location=location,
product=product_id)
# Remove the product from the product set.
client.remove_product_from_product_set(name=product_set_path,
product=product_path)
print('Product removed from product set.')
def get_similar_products_file(base64IMG):
project_id='smart-tracer-250813'
location='us-east1'
product_set_id='hack6'
product_category='toys'
# product_search_client is needed only for its helper methods.
product_search_client = vision.ProductSearchClient()
image_annotator_client = vision.ImageAnnotatorClient()
# Read the image as a stream of bytes.
content = base64IMG
# Create annotate image request along with product search feature.
image = vision.types.Image(content=content)
# product search specific parameters
product_set_path = product_search_client.product_set_path(
project=project_id, location=location,
product_set=product_set_id)
product_search_params = vision.types.ProductSearchParams(
product_set=product_set_path,
product_categories=[product_category])
image_context = vision.types.ImageContext(
product_search_params=product_search_params)
# Search products similar to the image.
response = image_annotator_client.product_search(
image, image_context=image_context)
print(response)
def __init__(self, project_id, location):
self.project_id = project_id
self.location = location
self.client = vision.ProductSearchClient()
self.location_path = self.client.location_path(project=self.project_id,
location=self.location)
def get_similar_products_uri(project_id, location, product_set_id,
product_category, image_uri, filter):
"""Search similar products to image.
Args:
project_id: Id of the project.
location: A compute region name.
product_set_id: Id of the product set.
product_category: Category of the product.
image_uri: Cloud Storage location of image to be searched.
filter: Condition to be applied on the labels.
Example for filter: (color = red OR color = blue) AND style = kids
It will search on all products with the following labels:
color:red AND style:kids
color:blue AND style:kids
"""
# product_search_client is needed only for its helper methods.
product_search_client = vision.ProductSearchClient()
image_annotator_client = vision.ImageAnnotatorClient()
# Create annotate image request along with product search feature.
image_source = vision.ImageSource(image_uri=image_uri)
image = vision.Image(source=image_source)
# product search specific parameters
product_set_path = product_search_client.product_set_path(
project=project_id, location=location, product_set=product_set_id)
product_search_params = vision.ProductSearchParams(
product_set=product_set_path,
product_categories=[product_category],
filter=filter)
image_context = vision.ImageContext(
product_search_params=product_search_params)
# Search products similar to the image.
response = image_annotator_client.product_search(
image, image_context=image_context)
index_time = response.product_search_results.index_time
print('Product set index time: ')
print(index_time)
results = response.product_search_results.results
print('Search results:')
output = []
for result in results:
product = result.product
print('Score(Confidence): {}'.format(result.score))
product_id = product.name.split('/')[-1]
image_uri = get_reference_image_uri(PROJECT_ID, LOCATION_ID,
product_id)
blob_name = image_uri.split('/')[-1]
meta = get_image_metadata(IMAGE_BUCKET, blob_name)
print("Product Info: ", meta)
output.append(meta)
return output
def cleanProductIds(project_id, location, product_id):
client = vision.ProductSearchClient()
# Get the full path of the product.
product_path = client.product_path(
project=project_id, location=location, product=product_id)
# Delete a product.
client.delete_product(name=product_path)
print('Product deleted.')
def setUpModule():
VisionSystemTestBase.client = vision.ImageAnnotatorClient()
VisionSystemTestBase.ps_client = vision.ProductSearchClient()
storage_client = storage.Client()
bucket_name = "new" + unique_resource_id()
VisionSystemTestBase.test_bucket = storage_client.bucket(bucket_name)
# 429 Too Many Requests in case API requests rate-limited.
retry_429 = RetryErrors(exceptions.TooManyRequests)
retry_429(VisionSystemTestBase.test_bucket.create)()
def imageURLToFoodID(url):
project_id = 'allergy-compass'
location = 'us-east1'
product_set_id = 'product_set0'
product_category = 'packagedgoods-v1'
filter = 'style=nothing'
"""Search similar products to image.
Args:
url
"""
import requests
f = open('temp.jpg', 'wb')
f.write(requests.get(url).content)
f.close()
# product_search_client is needed only for its helper methods.
product_search_client = vision.ProductSearchClient()
image_annotator_client = vision.ImageAnnotatorClient()
with open('temp.jpg', 'rb') as image_file:
content = image_file.read()
# Create annotate image request along with product search feature.
image = vision.types.Image(content=content)
# product search specific parameters
product_set_path = product_search_client.product_set_path(
project=project_id, location=location, product_set=product_set_id)
product_search_params = vision.types.ProductSearchParams(
product_set=product_set_path,
product_categories=[product_category],
filter=filter)
image_context = vision.types.ImageContext(
product_search_params=product_search_params)
# Search products similar to the image.
response = image_annotator_client.product_search(
image, image_context=image_context)
print(response)
result = response.product_search_results.results[0]
display_name = re.sub(r"(\w)([A-Z])", r"\1 \2",
result.product.display_name)
list = result.product.name.split("/")
barcode = list[len(list) - 1]
print("Barcode found: " + barcode)
print(display_name)
return display_name + "~" + getAllergyInfo(barcode)
def list_product_sets(project_id, location):
client = vision.ProductSearchClient()
# A resource that represents Google Cloud Platform location
# location_path = client.location_path(project=project_id, location=location)
# List all the product sets available in the region
product_sets = client.list_product_sets(
parent=location_path(project_id=project_id, location=location))
# Display the product set information
for product_set in product_sets:
print('Product set name: {}', format(product_set.name))
print('Product set id: {}', format(product_set.name.split('/')[-1]))
print('Product set display name: {}', format(product_set.display_name))
def delete_product(project_id, location, product_id):
"""Delete the product and all its reference images.
Args:
project_id: Id of the project.
location: A compute region name.
product_id: Id of the product.
"""
client = vision.ProductSearchClient()
# Get the full path of the product.
product_path = client.product_path(
project=project_id, location=location, product=product_id)
# Delete a product.
client.delete_product(name=product_path)
print('Product deleted.')
def get_similar_products_uri(project_id, location, product_set_id,
product_category, image_uri, filter):
"""Search similar products to image.
Args:
project_id: Id of the project.
location: A compute region name.
product_set_id: Id of the product set.
product_category: Category of the product.
file_path: Local file path of the image to be searched.
filter: Condition to be applied on the labels.
Example for filter: (color = red OR color = blue) AND style = kids
It will search on all products with the following labels:
color:red AND style:kids
color:blue AND style:kids
"""
# product_search_client is needed only for its helper methods.
product_search_client = vision.ProductSearchClient()
image_annotator_client = vision.ImageAnnotatorClient()
# Create annotate image request along with product search feature.
image_source = vision.types.ImageSource(image_uri=image_uri)
image = vision.types.Image(source=image_source)
# product search specific parameters
product_set_path = product_search_client.product_set_path(
project=project_id, location=location, product_set=product_set_id)
product_search_params = vision.types.ProductSearchParams(
product_set=product_set_path,
product_categories=[product_category],
filter=filter)
image_context = vision.types.ImageContext(
product_search_params=product_search_params)
# Search products similar to the image.
response = image_annotator_client.product_search(
image, image_context=image_context)
print(response)
results = response.product_search_results.results
return results[0].product.name
def get_reference_image_uri(project_id, location, product_id):
"""List all images in a product.
Args:
project_id: Id of the project.
location: A compute region name.
product_id: Id of the product.
"""
client = vision.ProductSearchClient()
# Get the full path of the product.
product_path = client.product_path(project=project_id,
location=location,
product=product_id)
# List all the reference images available in the product.
reference_images = client.list_reference_images(parent=product_path)
# Display the reference image information.
for image in reference_images:
return image.uri
def delete_reference_image(project_id, location, product_id,
reference_image_id):
"""Delete a reference image.
Args:
project_id: Id of the project.
location: A compute region name.
product_id: Id of the product.
reference_image_id: Id of the reference image.
"""
client = vision.ProductSearchClient()
# Get the full path of the reference image.
reference_image_path = client.reference_image_path(
project=project_id,
location=location,
product=product_id,
reference_image=reference_image_id)
# Delete the reference image.
client.delete_reference_image(name=reference_image_path)
print('Reference image deleted from product.')
def list_product_sets(project_id, location):
"""List all product sets.
Args:
project_id: Id of the project.
location: A compute region name.
"""
client = vision.ProductSearchClient()
# A resource that represents Google Cloud Platform location.
location_path = f"projects/{project_id}/locations/{location}"
# List all the product sets available in the region.
product_sets = client.list_product_sets(parent=location_path)
# Display the product set information.
for product_set in product_sets:
print('Product set name: {}'.format(product_set.name))
print('Product set id: {}'.format(product_set.name.split('/')[-1]))
print('Product set display name: {}'.format(product_set.display_name))
print('Product set index time: ')
print(product_set.index_time)
def list_reference_images(project_id, location, product_id):
"""List all images in a product.
Args:
project_id: Id of the project.
location: A compute region name.
product_id: Id of the product.
"""
client = vision.ProductSearchClient()
# Get the full path of the product.
product_path = client.product_path(
project=project_id, location=location, product=product_id)
# List all the reference images available in the product.
reference_images = client.list_reference_images(parent=product_path)
# Display the reference image information.
for image in reference_images:
print('Reference image "name": {}'.format(image.name))
print('Reference image id: {}'.format(image.name.split('/')[-1]))
print('Reference image "uri": {}'.format(image.uri))
print('Reference image bounding polygons: {}'.format(image.bounding_polys))
def list_products(project_id, location):
"""List all products.
Args:
project_id: Id of the project.
location: A compute region name.
"""
client = vision.ProductSearchClient()
# A resource that represents Google Cloud Platform location.
location_path = client.location_path(project=project_id, location=location)
# List all the products available in the region.
products = client.list_products(parent=location_path)
# Display the product information.
for product in products:
print('Product name: {}'.format(product.name))
print('Product id: {}'.format(product.name.split('/')[-1]))
print('Product display name: {}'.format(product.display_name))
print('Product description: {}'.format(product.description))
print('Product category: {}'.format(product.product_category))
print('Product labels: {}\n'.format(product.product_labels))
def get_product(project_id, location, product_id):
"""Get information about a product.
Args:
project_id: Id of the project.
location: A compute region name.
product_id: Id of the product.
"""
client = vision.ProductSearchClient()
# Get the full path of the product.
product_path = client.product_path(
project=project_id, location=location, product=product_id)
# Get complete detail of the product.
product = client.get_product(name=product_path)
# Display the product information.
print('Product name: {}'.format(product.name))
print('Product id: {}'.format(product.name.split('/')[-1]))
print('Product display name: {}'.format(product.display_name))
print('Product description: {}'.format(product.description))
print('Product category: {}'.format(product.product_category))
print('Product labels: {}'.format(product.product_labels))
def get_product_set(project_id, location, product_set_id):
"""Get info about the product set.
Args:
project_id: Id of the project.
location: A compute region name.
product_set_id: Id of the product set.
"""
client = vision.ProductSearchClient()
# Get the full path of the product set.
product_set_path = client.product_set_path(project=project_id,
location=location,
product_set=product_set_id)
# Get complete detail of the product set.
product_set = client.get_product_set(name=product_set_path)
# Display the product set information.
print('Product set name: {}'.format(product_set.name))
print('Product set id: {}'.format(product_set.name.split('/')[-1]))
print('Product set display name: {}'.format(product_set.display_name))
print('Product set index time: ')
print(product_set.index_time)
