def describe(self, image):
if app_settings.ALT_GENERATOR_PREFER_UPLOAD:
if not image.is_stored_locally():
image_data = get_image_data(image.file.url)
data = describe_by_data(image_data)
else:
image_data = get_local_image_data(image.file)
data = describe_by_data(image_data)
else:
data = describe_by_url(image.file.url)
description = None
tags = []
min_confidence = float(
app_settings.ALT_GENERATOR_MIN_CONFIDENCE) / 100.0
if not data:
return DescriptionResult(
description=description,
tags=tags,
)
if 'description' in data and len(data['description']['captions']):
captions = data['description']['captions']
captions = [
caption['text'] for caption in captions
if caption['confidence'] >= min_confidence
]
if len(captions):
description = captions[0]
try:
tags = data['description']['tags']
except:
pass
return DescriptionResult(
description=description,
tags=tags,
)
def describe(self, image):
if app_settings.ALT_GENERATOR_PREFER_UPLOAD:
if not image.is_stored_locally():
rendition = get_original_rendition(image)
image_data = get_image_data(rendition.url)
data = describe_by_data(image_data)
else:
image_data = get_local_image_data(image.file)
data = describe_by_data(image_data)
else:
rendition = get_original_rendition(image)
data = describe_by_url(rendition.url)
description = None
tags = []
min_confidence = float(
app_settings.ALT_GENERATOR_MIN_CONFIDENCE) / 100.0
if not data:
return DescriptionResult(description=description, tags=tags)
if "description" in data and len(data["description"]["captions"]):
captions = data["description"]["captions"]
captions = [
caption["text"] for caption in captions
if caption["confidence"] >= min_confidence
]
if len(captions):
description = captions[0]
try:
tags = data["description"]["tags"]
except: # NOQA
pass
return DescriptionResult(description=description, tags=tags)
def test_that_text_get_described(self):
with mock.patch.object(
Cognitive,
"describe",
return_value=DescriptionResult(description="A title",
tags=["blue", "green",
"white"]),
) as mock_method:
image = ImageFactory(title=get_test_image_file().name,
file=get_test_image_file())
image.refresh_from_db()
mock_method.assert_called_with(image)
self.assertEqual(image.title, "A title")
self.assertEqual(image.tags.all().count(), 3)
self.assertTrue(image.tags.filter(slug__in=["blue"]).exists())
def describe(self, image):
if not image.is_stored_locally():
image_data = get_image_data(image.file.url)
else:
image_data = get_local_image_data(image.file)
description = None
tags = []
min_confidence = float(
app_settings.ALT_GENERATOR_MIN_CONFIDENCE) / 100.0
if image_data:
image_data_base64 = base64.b64encode(image_data)
max_results = app_settings.ALT_GENERATOR_MAX_TAGS
request_body = {
'requests': [{
'image': {
'content': image_data_base64.decode('UTF-8'),
},
'features': [{
'type': 'LABEL_DETECTION',
}]
}]
}
if max_results != -1:
request_body['requests'][0]['features'][0][
'maxResults'] = max_results # NOQA
service_request = self.service.images().annotate(body=request_body)
response = service_request.execute()
labels = response['responses'][0]['labelAnnotations']
tags = [
label['description'] for label in labels
if label['score'] >= min_confidence
]
return DescriptionResult(
description=description,
tags=tags,
)
def describe(self, image):
if not image.is_stored_locally():
image_data = get_image_data(image.file.url)
else:
image_data = get_local_image_data(image.file)
description = None
tags = []
if image_data:
response = self.client.detect_labels(
Image={"Bytes": image_data},
MinConfidence=app_settings.ALT_GENERATOR_MIN_CONFIDENCE,
)
if response["Labels"]:
tags = [label["Name"] for label in response["Labels"]]
return DescriptionResult(description=description, tags=tags)
def describe(self, image):
if not image.is_stored_locally():
rendition = get_original_rendition(image)
image_data = get_image_data(rendition.url)
else:
image_data = get_local_image_data(image.file)
description = None
tags = []
min_confidence = float(
app_settings.ALT_GENERATOR_MIN_CONFIDENCE) / 100.0
if image_data:
image_data_base64 = base64.b64encode(image_data)
max_results = app_settings.ALT_GENERATOR_MAX_TAGS
request_body = {
"requests": [{
"image": {
"content": image_data_base64.decode("UTF-8")
},
"features": [{
"type": "LABEL_DETECTION"
}],
}]
}
if max_results != -1:
request_body["requests"][0]["features"][0][
"maxResults"] = max_results # NOQA
service_request = self.service.images().annotate(body=request_body)
response = service_request.execute()
labels = response["responses"][0]["labelAnnotations"]
tags = [
label["description"] for label in labels
if label["score"] >= min_confidence
]
return DescriptionResult(description=description, tags=tags)
def test_that_text_gets_translated(self):
with mock.patch.object(
Cognitive,
"describe",
return_value=DescriptionResult(description="A title",
tags=["blue", "green",
"white"]),
):
with mock.patch.object(
GoogleTranslate,
"translate",
return_value=["En titel", "blå", "grön", "vit"],
):
image = ImageFactory(title=get_test_image_file().name,
file=get_test_image_file())
image.refresh_from_db()
self.assertEqual(image.title, "En titel")
self.assertEqual(image.tags.all().count(), 3)
self.assertTrue(image.tags.filter(slug__in=["vit"]).exists())
def translate_description_result(result):
provider = get_current_provider()()
lang_and_country_code = get_language()
lang_code = lang_and_country_code.split("-")[0]
strings = []
if result.description:
strings = [result.description]
if result.tags:
strings = [*strings, *result.tags]
translated_strings = provider.translate(strings, target_language=lang_code)
translated_description = (translated_strings[0]
if result.description else result.description)
translated_tags = (translated_strings[1:]
if result.description else translated_strings)
return DescriptionResult(description=translated_description,
tags=translated_tags)
def test_that_description_is_set_when_tags_are_none(self):
result = DescriptionResult("En bro", None)
translated_result = translate_description_result(result)
self.assertEqual(translated_result.description, "A bridge")
self.assertEqual(translated_result.tags, [])
def test_that_description_is_excluded_when_empty(self):
result = DescriptionResult("", ["cat", "house", "shoe"])
translated_result = translate_description_result(result)
self.assertEqual(translated_result.description, "")
self.assertEqual(translated_result.tags, ["katt", "hus", "sko"])
def test_translation_mapping(self):
result = DescriptionResult("My title", ["cat", "house", "shoe"])
translated_result = translate_description_result(result)
self.assertEqual(translated_result.description, "Min titel")
self.assertEqual(translated_result.tags, ["katt", "hus", "sko"])
