Getting human perception scores from street-level imagery.

The scores are in scale of 0-10.

Safety, lively, beautiful, wealthy high score indicates strong positive feeling

Boring, depressing high score indicates strong negative feeling

The models are pre-trained on MIT Place Pulse 2.0 dataset. The backbone of the model is vision transformer pretrianed on ImageNet (ViT_B_16_Weights.IMAGENET1K_SWAG_E2E_V1). 3 Linear layers are added in ViT heads for classification.

Install packages from requirements.txt

Change the file path in eval.py

model_load_path = "./model/"   # model path
images_path = "./test_image"      # your input image path
out_Path = "./output"     # output path

Run the file eval.py

Please refer to human-perception-place-pulse for details.