Photos | Congregating in the City
Annegret Kramp-Karrenbauer and a crowd of 27 people walk down the busy sidewalk in front of a church in a bustling urban neighborhood. The blue sky and palm trees provide a scenic backdrop while 14 cars and other vehicles line the road.
BLIP-2 Description:
a group of people walking down the sidewalk in front of a churchMetadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
Dominant Color:
urban wheel rekognition_c street jeans glasses palm transportation town outdoor footwear bag tire path ordination sky tree pedestrian wbtla_ordination chair city automobile car karrenbauer sidewalk arch building kramp intersection shoe handbag tarmac neighborhood office pants plant area annegret spoke metropolis road vehicle architecture machine blue hat wbtla light traffic furniture shrub accessories alloy wheel walking walkway crowd land
iso
100
metering mode
5
aperture
f/8
focal length
16mm
shutter speed
1/320s
camera make
Canon
camera model
lens model
overall
(47.00%)
curation
(50.00%)
highlight visibility
(4.51%)
behavioral
(90.78%)
failure
(-0.07%)
harmonious color
(4.16%)
immersiveness
(4.35%)
interaction
(1.00%)
interesting subject
(-9.88%)
intrusive object presence
(-4.98%)
lively color
(9.88%)
low light
(0.66%)
noise
(-0.61%)
pleasant camera tilt
(-6.48%)
pleasant composition
(-48.56%)
pleasant lighting
(12.78%)
pleasant pattern
(8.94%)
pleasant perspective
(22.24%)
pleasant post processing
(-1.43%)
pleasant reflection
(-0.76%)
pleasant symmetry
(1.20%)
sharply focused subject
(0.27%)
tastefully blurred
(4.82%)
well chosen subject
(11.24%)
well framed subject
(-38.50%)
well timed shot
(0.16%)
all
(5.17%)
* NOTE: Amazon Rekognition
detected a celebrity in this image using the
Celebrity Recognition API. The API isn't perfect, but it does give you the MatchConfidence which I display
next to the celebrity's name along with links _↗ to their info.
* WARNING: The title and caption of this image were generated by an AI LLM (gpt-3.5-turbo-0301
from
OpenAI)
based on a
BLIP-2 image-to-text labeling, tags,
location,
people
and album metadata from the image and are
potentially inaccurate, often hilariously so. If you'd like me to adjust anything,
just reach out.