Fork of microsoft/trocr-base-printed for an OCR
Inference endpoint.
This repository implements a custom
task for ocr-detection
for 🤗 Inference Endpoints. The code for the customized pipeline is in the pipeline.py.
To use deploy this model as an Inference Endpoint, you have to select Custom
as the task to use the pipeline.py
file. -> double check if it is selected
Run Request
The endpoint expects the image to be served as binary
. Below is an curl and python example
cURL
- get image
wget https://fki.tic.heia-fr.ch/static/img/a01-122-02-00.jpg -O test.jpg
- send cURL request
curl --request POST \
--url https://{ENDPOINT}/ \
--header 'Content-Type: image/jpg' \
--header 'Authorization: Bearer {HF_TOKEN}' \
--data-binary '@test.jpg'
- the expected output
{"text": "INDLUS THE"}
Python
- get image
wget https://fki.tic.heia-fr.ch/static/img/a01-122-02-00.jpg -O test.jpg
- run request
import json
from typing import List
import requests as r
import base64
ENDPOINT_URL=""
HF_TOKEN=""
def predict(path_to_image:str=None):
with open(path_to_image, "rb") as i:
b = i.read()
headers= {
"Authorization": f"Bearer {HF_TOKEN}",
"Content-Type": "image/jpeg" # content type of image
}
response = r.post(ENDPOINT_URL, headers=headers, data=b)
return response.json()
prediction = predict(path_to_image="test.jpg")
prediction
expected output
{"text": "INDLUS THE"}
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Inference API (serverless) does not yet support generic models for this pipeline type.