K-Nearest-Neighbour model of human perception of Amsterdam street view imagery. data.npz is a compressed numpy file with 10 records, it can be loaded with numpy.load and the resulting object can be indexed by any of the following keys:
- walkability_vecs, walkability_scores
- bikeability_vecs, bikeability_scores
- pleasantness_vecs, pleasantness_scores
- greenness_vecs, greenness_scores
- safety_vecs, safety_scores
The _vecs entries are matrices of size Nx1024 and the _scores entries are vectors of size N.
The _vecs are encoded by OpenCLIP ViT-H-14-378-quickgelu (pretrained: dfn5b).
The _scores are the given rating scores (1 to 5) for the corresponding vector. For example, the vector given by walkability_vecs[10,:] has a corresponding score in walkability_scores[10].
This can be used to model a score for any given vector from an image encoded by the above CLIP model.
Example spaces
- Percept-map: pick a point on a map and evaluate perception ratings for Mapillary imagery from that location
- Percept-image: evaluation perception ratings for a given image
See also: svi_percept Python package.
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