Photos | Ordination Day Excitement
A crowd of 41 people gathers outside a building in the city, walking along the sidewalk and path in their best clothing and accessories, while 9 cars and other vehicles fill the street. The blue sky, decorative plants, and palm trees add to the excitement of Gill Marcus and Liu Xiaobo's ordination day.
BLIP-2 Description:
a large crowd of people standing outside of a buildingMetadata
Capture date:
Original Dimensions:
5616w x 3744h - (download 4k)
Usage
urban street jeans glasses palm transportation outdoor footwear bag path ordination sky jacket tree container wbtla_ordination pedestrian potted chair city decorative automobile car sidewalk arch building gill marcus shoe handbag xiaobo coat liu neighborhood pants plant metropolis road vehicle architecture machine blue hat wbtla light bus pemple traffic furniture accessories walking walkway luggage crowd land
Detected Text
iso
100
metering mode
5
aperture
f/8
focal length
16mm
shutter speed
1/250s
camera make
Canon
camera model
lens model
overall
(41.65%)
curation
(50.00%)
highlight visibility
(4.51%)
behavioral
(90.86%)
failure
(-0.10%)
harmonious color
(3.52%)
immersiveness
(1.93%)
interaction
(1.00%)
interesting subject
(-36.35%)
intrusive object presence
(-5.42%)
lively color
(2.08%)
low light
(1.07%)
noise
(-0.73%)
pleasant camera tilt
(-7.45%)
pleasant composition
(-75.93%)
pleasant lighting
(-2.30%)
pleasant pattern
(4.83%)
pleasant perspective
(17.97%)
pleasant post processing
(1.02%)
pleasant reflection
(-1.94%)
pleasant symmetry
(0.54%)
sharply focused subject
(0.17%)
tastefully blurred
(-2.22%)
well chosen subject
(17.31%)
well framed subject
(-65.77%)
well timed shot
(2.64%)
all
(0.85%)
* 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.