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from fastapi import FastAPI, UploadFile, HTTPException, Body
from fastapi.responses import JSONResponse
from fastapi.middleware.cors import CORSMiddleware
from transformers import pipeline
from PIL import Image
import base64
from io import BytesIO
app = FastAPI()
# Load the image classification pipeline
classifier = pipeline(model="Diginsa/Plant-Disease-Detection-Project")
# CORS configuration
origins = [""] # Replace "" with the actual list of allowed origins
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# Endpoint to perform image classification
@app.post("/classify")
async def classify_image(encoded_image: str= Body(..., embed=True)):
try:
# Decode the base64 encoded image string
decoded_image = base64.b64decode(encoded_image)
# Create an Image object from the decoded content
image = Image.open(BytesIO(decoded_image))
# Use the classifier with the decoded image
result = classifier(images=image)
# Return the classification result as JSON
return JSONResponse(content=result, status_code=200)
except Exception as e:
raise HTTPException(status_code=500, detail=str(e)) |