Added first version of the model.

Training dataset metadata:
Dataset classes: ['soft', 'digital', 'hard']
Number of classes: 3
Total number of images: 18415
Number of images per class:
soft : 5482
digital : 1206
hard : 11727

The hard class contains the following categories of objects:
object, laptop, charger, pc mouse, pc, rocks, table, bed, box, sneakers, ship, wire, guitar, fork, spoon, plate, keyboard, car, bus, screwdriver, ball, door, flower, clocks, fruit , food, robot.
The soft class contains the following categories of objects:
animal, people, human, man, woman, t-shirt, hairs, hair, dog, cat, monkey, cow, medusa, clothes
The digital class contains the following categories of scenes: screenshot

The classifier uses DenseNet161 as the encoder.

scene_classifier.pth

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