readme: ---
  tags:
  - vision
  - zero-shot-image-classification
  - endpoints-template
  library_name: generic
  ---
  
  # Fork of [openai/clip-vit-base-patch32](https://huggingface.co/openai/clip-vit-base-patch32) for a `zero-sho-image-classification` Inference endpoint.
  
  This repository implements a `custom` task for `zero-shot-image-classification` for 🤗 Inference Endpoints. The code for the customized pipeline is in the [pipeline.py](https://huggingface.co/philschmid/clip-zero-shot-image-classification/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
    "candiates":["sea","palace","car","ship"]
  }
  ```
  
  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, candiates: List[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", candiates=["sea", "palace", "car", "ship"]
  )
  ```
  
  expected output
  
  ```python
  [{'label': 'palace', 'score': 0.9996134638786316},
   {'label': 'car', 'score': 0.0002602009626571089},
   {'label': 'ship', 'score': 0.00011758189066313207},
   {'label': 'sea', 'score': 8.666840585647151e-06}]
  ```
  
  
  