On my maiden voyage to Canyonlands National Park, I found myself really excited to see the vast grand scenics offered by the Island in the Sky area overlooking the Green River. The pastel colors seen just before sunrise were quite magical. I love Utah in the winter! [fine art panoramic photography]
"Nyctophilia" - Noun - a love or preference for night and darkness. After an adventurous day of rafting down the Colorado River in the Grand Canyon, I hiked up a steep and uncharted ridge to view the night sky in its full glory. [fine art panoramic photography]
When I realized that the Milky Way would line up directly above my two favorite Colorado mountains - Vestal Peak and Arrow Peak - at 2:30 AM, I set my alarm for 1:00 AM at my 12,200 foot campsite to climb to 13,000 feet to witness it. To achieve this insane photo, I shot a series of ten photographs up and behind me with my 55 mm lens to capture the utmost detail in the core of the Milky Way. The scene was absolutely magical. [vertical panoramic photography]
To use all the features of this site you must be logged in. If you don't have an account you can sign up right now.
AI Photo Analysis
Evaluation of picture quality and feel has been a long-standing issue in photo handling. While specialized quality appraisal manages to measure pixel-level debasements, for example, commotion, obscure, pressure antiques, and so forth., tasteful evaluation catches semantic level attributes related to feelings and excellence in pictures. Hossein Talebi, Google Software Engineer said, “Our proposed network can be used to not only score images reliably and with high correlation to human perception, but also it is useful for a variety of labor-intensive and subjective tasks such as intelligent photo editing, optimizing visual quality for increased user engagement, or minimizing perceived visual errors in an imaging pipeline.”
The AI photo tagging engine are automaticaly annotating photos with multiple image tags, to enhance the quality of visual representation of the trained CNN model. It is based on a large-scale multi-label image database with 18M images and 11K categories. The AI Assessment Rating are trained using two models (AVA & TID2013) to predict the aesthetic and technical quality of photos. The models are trained via transfer learning, where ImageNet pre-trained CNNs are used and fine-tuned for the classification task. AI photo processing are running in the background using several GPU-powered backend servers. These AI technologies are based on Vedere AI Engine, you can check out the website at www.vedereai.com
AI Image Search
Full text search (e.g. 'delicious food') to search the images name and description.
Minus symbol (e.g. '-beach') to remove specific words from images name and description.
filetype:extension (e.g. 'filetype:png') to search specific images filetype.
camera:brand (e.g. 'camera:nikon') to search specific brand of camera used.
iso:speed(e.g. 'iso:1250') to search for images taken using specific ISO speed.
f:number (e.g. 'f:6.3') to search for images taken using specific aperture.
mm:number (e.g. 'mm:50') to search for images taken using specific focal length.
tags:name (e.g. 'tags:valley') to search specific image classifications detected by AI.
caption:name (e.g. 'caption:blue') to search specific wording in image captioning detected by AI.
category:name (e.g. 'category:macro') to search specific photo category.
faces:number(e.g. 'faces:3') to search for images with the number of faces.
Combining any of the above (e.g. 'caption:blue tags:gown category:fashion') to search for 'blue' in AI image captioning that is a 'gown' in AI image tagging under the 'fashion' category.
Another example (e.g. 'iso:100 camera:canon tags:bikini') to search for 'canon' camera used together with ISO setting of 100 and contains bikini in the AI image classification.