https://github.com/sayannath/image-scene-classification
Image-Scene-Classification with 30 different classes.
https://github.com/sayannath/image-scene-classification
big-transfer bit image-classification keras mobilenetv3 state-of-the-art-models tensrflow tflite visual-transformer vit
Last synced: 5 months ago
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Image-Scene-Classification with 30 different classes.
- Host: GitHub
- URL: https://github.com/sayannath/image-scene-classification
- Owner: sayannath
- Created: 2021-03-01T04:52:57.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2021-12-25T14:51:28.000Z (almost 4 years ago)
- Last Synced: 2025-05-12T14:25:42.459Z (5 months ago)
- Topics: big-transfer, bit, image-classification, keras, mobilenetv3, state-of-the-art-models, tensrflow, tflite, visual-transformer, vit
- Language: Jupyter Notebook
- Homepage: https://competitions.codalab.org/competitions/28113
- Size: 21.7 MB
- Stars: 7
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Image-Scene-Classification
Competition Link: https://competitions.codalab.org/competitions/28113
## Data overview
We are employing a newly collected Camera Scene Detection dataset consisting of images belonging to 30 different classes:
* Portrait
* Group Portrait
* Kids / Infants
* Dogs
* Cats
* Macro / Close-up
* Food / Gourmet
* Beach
* Mountains
* Waterfall
* Snow
* Landscape
* Underwater
* Architecture
* Sunrise / Sunset
* Blue Sky
* Overcast / Cloudy Sky
* Greenery / Grass
* Autumn Plants
* Flower
* Night
* Shot Stage / Concert
* Fireworks
* Candle light
* Neon Lights / Neon Signs
* Indoor
* Backlight / Contre-jour
* Text / Document
* QR Code
* Monitor Screen
The dataset is divided into:
train data: 9897 images of resolution 576 x 384 px from the above 30 classes that can be used for training the model.
validation data: 600 images of resolution 576 x 384 px provided from the beginning of the challenge and are meant for the participants to get online feedback from the validation server.
test data: 600 images of resolution 576 x 384 px; the participants will get access to them when the final evaluation phase starts and the results will be announced after the challenge is over and the winners are decided.
## Data access
Development phase / Learning:
Train Data (images divided by classes) - http://data.vision.ee.ethz.ch/ihnatova/camera_scene_detection_train.zip
Validation Data (only input images) - https://data.vision.ee.ethz.ch/ihnatova/camera_scene_detection_validation.zip