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README.md

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+---
+tags:
+- feature-extraction
+- endpoints-template
+license: bsd-3-clause
+library_name: generic
+---
+# Fork of [salesforce/BLIP](https://github.com/salesforce/BLIP) for a `feature-extraction` task on 🤗Inference endpoint.
+This repository implements a `custom` task for `feature-extraction` for 🤗 Inference Endpoints. The code for the customized pipeline is in the [pipeline.py](https://huggingface.co/florentgbelidji/blip-embeddings/blob/main/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
+```json
+{
+  "image": "/9j/4AAQSkZJRgABAQEBLAEsAAD/2wBDAAMCAgICAgMC....", // base64 image as bytes
+}
+```
+below is an example on how to run a request using Python and `requests`.
+## Run Request 
+1. prepare an image. 
+```bash
+!wget https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg
+```
+2.run request
+```python
+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")}}
+    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
+```python
+{'feature_vector': [0.016450975090265274,
+  -0.5551009774208069,
+  0.39800673723220825,
+  -0.6809228658676147,
+  2.053842782974243,
+  -0.4712907075881958,...]
+ }
+```