Upload handler_template.py with huggingface_hub

handler_template.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+import os
+import base64
+import torch
+import numpy as np
+from PIL import Image
+import io
+
+class BaseHandler:
+    def __init__(self):
+        """Initialize the handler with model-specific configurations"""
+        self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+        self.model = None
+        self.initialized = False
+        
+    def initialize(self):
+        """Load model and other resources"""
+        # This method should be implemented by each specific handler
+        raise NotImplementedError
+        
+    def preprocess(self, data):
+        """Preprocess the input data"""
+        # This method should be implemented by each specific handler
+        raise NotImplementedError
+        
+    def inference(self, inputs):
+        """Run inference with the preprocessed inputs"""
+        # This method should be implemented by each specific handler
+        raise NotImplementedError
+        
+    def postprocess(self, inference_output):
+        """Post-process the model output"""
+        # This method should be implemented by each specific handler
+        raise NotImplementedError
+        
+    def __call__(self, data):
+        """Handle a request to the model"""
+        # Initialize the model if not already done
+        if not self.initialized:
+            self.initialize()
+            
+        # Process the request
+        preprocessed_data = self.preprocess(data)
+        inference_output = self.inference(preprocessed_data)
+        output = self.postprocess(inference_output)
+        
+        return output
+        
+    def encode_image(self, image):
+        """Encode a PIL Image to base64"""
+        buffered = io.BytesIO()
+        image.save(buffered, format="PNG")
+        img_str = base64.b64encode(buffered.getvalue()).decode("utf-8")
+        return img_str
+        
+    def decode_image(self, image_str):
+        """Decode a base64 string to PIL Image"""
+        img_data = base64.b64decode(image_str)
+        return Image.open(io.BytesIO(img_data))
+        
+    def svg_to_base64(self, svg_content):
+        """Convert SVG content to base64"""
+        return base64.b64encode(svg_content.encode("utf-8")).decode("utf-8")