Sashimi Package
Python library for benchmarking spatio-temporal saliency prediction on videos, images, and options including face and eye detections. It predicts where human eyes might look at in naturalistic settings.
Created by Baihan Lin, Columbia University
1 maintainer
Metadata
1 maintainer
Release files for sashimi 0.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| sashimi-0.0.2.tar.gz | 16.1 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| sashimi-0.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 32.2 kB
Release files / sashimi-0.0.2.tar.gz
| Download URL | sashimi-0.0.2.tar.gz |
|---|---|
| Size | 16.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
89020780c68b4173e7f47bd9a2cea8765fd7b18eda1724952b7f78a5a17c314d
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BLAKE2b-256 checksum How to use checksums |
8124506d9b2748249689ed4b6f9a94860d481434bcd450b9ce5582bfac422e8e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.9.16
|
Release files / sashimi-0.0.2-py3-none-any.whl
| Download URL | sashimi-0.0.2-py3-none-any.whl |
|---|---|
| Size | 16.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
81d156de99ccfadb3b915f2c899a1dbca22cf20b23698f7719f420b427f6f788
|
|
BLAKE2b-256 checksum How to use checksums |
97a828bd83dc44f0317d32492cdab3832e817ec8ed3f93be44e9ef5a05a434da
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.9.16
|
Security for sashimi 0.0.2
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No provenance found
None of the files in this release were uploaded with provenance metadata.
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