TensorFlow Serving Client
Client for OCR predictions against TensorFlow Serving
pip install tf-serving
Model
The served model must return the following schema:
{
preds: StringTensor[BATCH x TOP_PATHS],
logprobs: FloatTensor[BATCH x TOP_PATHS]
}
Usage
from tf.serving import predict, encode64
with open('path/to/image.jpg', 'rb') as f:
img = encode64(f.read())
await predict([img], host='http://localhost', port=8501, endpoint='/v1/models/ocr:predict')
# Right(value=[ImagePreds(preds=['Place', 'Piace', ...], logprobs=[-0.187645972, -2.03857613, ...])], tag='right')
1 maintainer
Metadata
1 maintainer
Release files for tf-serving 0.1.6
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| tf_serving-0.1.6.tar.gz | 4.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| tf_serving-0.1.6-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 10.0 kB
Release files / tf_serving-0.1.6.tar.gz
| Download URL | tf_serving-0.1.6.tar.gz |
|---|---|
| Size | 4.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Release files / tf_serving-0.1.6-py3-none-any.whl
| Download URL | tf_serving-0.1.6-py3-none-any.whl |
|---|---|
| Size | 5.6 kB |
| Tags | Python 3 |
|
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No |
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