Photos | Nightlife Madness
Hu Qing and 18 other energetic club-goers enjoy a wild night out dancing and partying under the flashing lights of a disco ball and cool breeze of an electric fan at Respect Nightclub.
BLIP-2 Description:
a crowd of people in a nightclub with a fanChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
urban instrument rekognition_c recreation crwod night party music baby gettin appliance bag qing respect interior musical necklace entertainer jewelry pictures disco night club junglescene handbag nightclub room trace spotlight ball cup performance hu life machine hat light fun club accessories electric fan crowd
Detected Text
overall
(17.24%)
curation
(50.00%)
highlight visibility
(4.35%)
behavioral
(70.47%)
failure
(-0.78%)
harmonious color
(-0.31%)
immersiveness
(0.12%)
interaction
(1.00%)
interesting subject
(-71.24%)
intrusive object presence
(-14.33%)
lively color
(-17.61%)
low light
(87.11%)
noise
(-12.04%)
pleasant camera tilt
(-14.51%)
pleasant composition
(-91.65%)
pleasant lighting
(-65.58%)
pleasant pattern
(2.59%)
pleasant perspective
(-12.00%)
pleasant post processing
(3.02%)
pleasant reflection
(-5.25%)
pleasant symmetry
(0.15%)
sharply focused subject
(0.10%)
tastefully blurred
(-12.46%)
well chosen subject
(-8.82%)
well framed subject
(-61.62%)
well timed shot
(-9.83%)
all
(-13.67%)
* 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.
* NOTE: This image was scaled up from its original size using an AI model called GFP-GAN (Generative Facial Prior), which is a
Generative adversartial network that can be used to repair (or upscale in this case) photos, sometimes the results are a little...
weird.
* 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.