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from transformers import pipeline
from PIL import Image
from io import BytesIO
import base64
from typing import Dict, List, Any
class EndpointHandler():
def __init__(self, model_path=""):
# Initialize the pipeline with the specified model and set the device to GPU
self.pipeline = pipeline(task="zero-shot-object-detection", model=model_path, device=0)
def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
"""
Process an incoming request for zero-shot object detection.
Args:
data (Dict[str, Any]): The input data containing an encoded image and candidate labels.
Returns:
A list of dictionaries, each containing a label and its corresponding score.
"""
# Correctly accessing the 'inputs' key and fixing the typo in 'candidates'
inputs = data.get("inputs", {})
# Decode the base64 image to a PIL image
image = Image.open(BytesIO(base64.b64decode(inputs['image'])))
# Get candidate labels
candidate_labels=inputs["candidates"]
# Correctly passing the image and candidate labels to the pipeline
detection_results = self.pipeline(image=image, candidate_labels=inputs["candidates"], threshold = 0)
# Adjusting the return statement to match the expected output structure
return detection_results
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