Spaces:
Running
Running
File size: 1,272 Bytes
f8bf7d4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 |
from huggingface_hub import HfApi
import json
import tempfile
import os
#huggingface_hub
submission = {'latitude': '3.5', 'longitude': '44', 'author_email':
'super@whale.org', 'date': '2024-10-25', 'time': '12:07:04.487612',
'predicted_class': 'bottlenose_dolphin', 'class_overriden': None,
'image_filename': '000a8f2d5c316a.webp', 'image_md5':
'd41d8cd98f00b204e9800998ecf8427e'}
imgname = submission['image_filename']
api = HfApi()
# generate a tempdirectory to store the image
#tempdir = tempfile.TemporaryDirectory()
# write a tempfile
# write submission to a tempfile in json format with the name of the image, giving the filename and path as a string
f = tempfile.NamedTemporaryFile(mode="w", suffix=".json", delete=False)
jstr = json.dumps(submission)
f.write(jstr)
f.close()
#with tempfile.NamedTemporaryFile(mode="w", suffix=".json", delete=False) as f:
# jstr = json.dumps(submission)
# f.write(jstr)
# #print(f.path)
path_in_repo= f"metadata/{submission['author_email']}/{submission['image_md5']}.json"
print(f"fname: {f.name} | path: {path_in_repo}")
rv = api.upload_file(
path_or_fileobj=f.name,
path_in_repo=path_in_repo,
repo_id="Saving-Willy/Happywhale-kaggle",
repo_type="dataset",
)
print(rv)
|