Instructions to use BAAI/Brainmu-SpikeCamera with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BAAI/Brainmu-SpikeCamera with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import SpikeConvFrontend model = SpikeConvFrontend.from_pretrained("BAAI/Brainmu-SpikeCamera", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,014 Bytes
4719196 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | import importlib.util,tempfile,unittest
from pathlib import Path
from PIL import Image
spec=importlib.util.spec_from_file_location("evaluation",Path(__file__).resolve().parents[1]/"scripts/infer.py")
m=importlib.util.module_from_spec(spec);spec.loader.exec_module(m)
class EvaluationTests(unittest.TestCase):
def test_complete_pair_and_hashes(self):
with tempfile.TemporaryDirectory() as d:
p=Path(d);(p/"x.dat").write_bytes(bytes(512500));Image.new("RGB",(400,250)).save(p/"x.png")
files,rows=m.validate_pairs(p,p,1)
self.assertEqual(len(files),1);self.assertEqual(len(rows[0]["spike_sha256"]),64)
with self.assertRaises(ValueError):m.validate_pairs(p,p,1000)
def test_missing_or_bad_gt(self):
with tempfile.TemporaryDirectory() as d:
p=Path(d);(p/"x.dat").write_bytes(bytes(512500))
with self.assertRaises(ValueError):m.validate_pairs(p,p,1)
Image.new("RGB",(10,10)).save(p/"x.png")
with self.assertRaises(ValueError):m.validate_pairs(p,p,1)
if __name__=="__main__":unittest.main()
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