Photos | Metropolis Building in the Urban Neighborhood
Jin Yaqin captured the towering Metropolis building in the bustling urban neighborhood during her 2006 trip to San Francisco. The apartment building stands out with its numerous signs, balconies, and lampposts, while the flag and bustling traffic add to the city vibe.
BLIP-2 Description:
a tall building with many signsChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
3504w x 2332h - (download 4k)
Usage
urban flag 永安 tai 市 更 trip burger wall 香 food 人參 若 trad railing decor services 意 shing 百 handrail sf tel high 成藥 apartment light lamppost 糕粉 中 sung wi path condo housing tung 英 building tax outdoors 越 金 metropolis 記 永 眾 jin yaqin stres 然 事務 前 rise 安 服 專業 司 大 canopy neighborhood tra architecture 東 報稅 awning jewe traffic home street town outdoor jackson bookk balcony city 形 intersection 薄 文明 day 感 生金 area 脰 apartment building road 譚 月 shelter hue 報
Detected Text
iso
100
metering mode
5
aperture
f/4.5
exposure bias
1
focal length
85mm
shutter speed
1/200s
camera make
Canon
camera model
overall
(27.76%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.44%)
failure
(-0.15%)
harmonious color
(-0.87%)
immersiveness
(0.49%)
interaction
(1.00%)
interesting subject
(-66.46%)
intrusive object presence
(-6.27%)
lively color
(-10.61%)
low light
(1.32%)
noise
(-0.61%)
pleasant camera tilt
(-8.94%)
pleasant composition
(-72.07%)
pleasant lighting
(-30.15%)
pleasant pattern
(4.64%)
pleasant perspective
(21.37%)
pleasant post processing
(0.32%)
pleasant reflection
(1.98%)
pleasant symmetry
(0.78%)
sharply focused subject
(0.34%)
tastefully blurred
(-0.62%)
well chosen subject
(-1.74%)
well framed subject
(-30.79%)
well timed shot
(-4.93%)
all
(-4.43%)
* 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.