
# 25K Unsplash Images for Search

This is a derivative work based on two existing datasets.

- `images.csv` metadata from [Unsplash](https://github.com/unsplash/datasets), sorted and converted to CSV.
- `images/` in 250x250 resolution by [kaggle/@jettchentt](https://www.kaggle.com/datasets/jettchentt/unsplash-dataset-images-downloaded-250x250).
- `images.fbin` is a binary file with UForm image embeddings.
- `images.usearch` is a binary file with a serialized USearch index.

The original `images.tsv` from Unsplash has been filtered to avoid missing images.
The embeddings and the index can be reconstructed with the `main.py` script.
On the Apple M2 Pro CPU:

- Image vectorization takes 100ms/image, or 10 inferences/second.
- Indexing vectors one-by-one happens at 700 vectors/second speed.

To rebuild the indexes:

```sh
./main.py
```

license:apache-2.0 region:us
{"license": "apache-2.0"}
TAGS
#license-apache-2.0 #region-us 


# 25K Unsplash Images for Search

This is a derivative work based on two existing datasets.

- 'URL' metadata from Unsplash, sorted and converted to CSV.
- 'images/' in 250x250 resolution by kaggle/@jettchentt.
- 'URL' is a binary file with UForm image embeddings.
- 'images.usearch' is a binary file with a serialized USearch index.

The original 'URL' from Unsplash has been filtered to avoid missing images.
The embeddings and the index can be reconstructed with the 'URL' script.
On the Apple M2 Pro CPU:

- Image vectorization takes 100ms/image, or 10 inferences/second.
- Indexing vectors one-by-one happens at 700 vectors/second speed.

To rebuild the indexes:



# 25K Unsplash Images for Search

This is a derivative work based on two existing datasets.

- 'URL' metadata from Unsplash, sorted and converted to CSV.
- 'images/' in 250x250 resolution by kaggle/@jettchentt.
- 'URL' is a binary file with UForm image embeddings.
- 'images.usearch' is a binary file with a serialized USearch index.

The original 'URL' from Unsplash has been filtered to avoid missing images.
The embeddings and the index can be reconstructed with the 'URL' script.
On the Apple M2 Pro CPU:

- Image vectorization takes 100ms/image, or 10 inferences/second.
- Indexing vectors one-by-one happens at 700 vectors/second speed.

To rebuild the indexes:
TAGS
#license-apache-2.0 #region-us 
 # 25K Unsplash Images for Search

This is a derivative work based on two existing datasets.

- 'URL' metadata from Unsplash, sorted and converted to CSV.
- 'images/' in 250x250 resolution by kaggle/@jettchentt.
- 'URL' is a binary file with UForm image embeddings.
- 'images.usearch' is a binary file with a serialized USearch index.

The original 'URL' from Unsplash has been filtered to avoid missing images.
The embeddings and the index can be reconstructed with the 'URL' script.
On the Apple M2 Pro CPU:

- Image vectorization takes 100ms/image, or 10 inferences/second.
- Indexing vectors one-by-one happens at 700 vectors/second speed.

To rebuild the indexes:
passage: TAGS
#license-apache-2.0 #region-us 
# 25K Unsplash Images for Search

This is a derivative work based on two existing datasets.

- 'URL' metadata from Unsplash, sorted and converted to CSV.
- 'images/' in 250x250 resolution by kaggle/@jettchentt.
- 'URL' is a binary file with UForm image embeddings.
- 'images.usearch' is a binary file with a serialized USearch index.

The original 'URL' from Unsplash has been filtered to avoid missing images.
The embeddings and the index can be reconstructed with the 'URL' script.
On the Apple M2 Pro CPU:

- Image vectorization takes 100ms/image, or 10 inferences/second.
- Indexing vectors one-by-one happens at 700 vectors/second speed.

To rebuild the indexes: