metadata
tags:
- image-to-text
- image-captioning
- endpoints-template
license: bsd-3-clause
library_name: generic
Blip Caption 🤗 Inference Endpoints
This repository implements a custom
task for image-captioning
for 🤗 Inference Endpoints. The code for the customized pipeline is in the pipeline.py.
To use deploy this model a an Inference Endpoint you have to select Custom
as task to use the pipeline.py
file. -> double check if it is selected
expected Request payload
{
"image": "/9j/4AAQSkZJRgABAQEBLAEsAAD/2wBDAAMCAgICAgMC....", // base64 image as bytes
}
below is an example on how to run a request using Python and requests
.
Run Request
- prepare an image.
!wget https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.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:
b64 = base64.b64encode(i.read())
payload = {"inputs": {"image": b64.decode("utf-8"), "candiates": candiates}}
response = r.post(
ENDPOINT_URL, headers={"Authorization": f"Bearer {HF_TOKEN}"}, json=payload
)
return response.json()
prediction = predict(
path_to_image="palace.jpg"
)
expected output
['buckingham palace with flower beds and red flowers']