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from flask import Flask, request
from transformers import AutoModelForImageClassification
from transformers import AutoImageProcessor
from PIL import Image
from io import BytesIO
import os
import torch
app = Flask(__name__)
model = AutoModelForImageClassification.from_pretrained(
'./myModel')
image_processor = AutoImageProcessor.from_pretrained(
"google/vit-base-patch16-224-in21k")
@app.route('/upload_image', methods=['POST'])
def upload_image():
# Get the image file from the request
image_file = request.files['image']
# image = Image.open(BytesIO(image_file.read()))
image = Image.open(image_file.stream)
inputs = image_processor(image, return_tensors="pt")
with torch.no_grad():
logits = model(**inputs).logits
predicted_label = logits.argmax(-1).item()
disease = model.config.id2label[predicted_label]
# You can perform additional operations with the image here
# ...
return disease
@app.route('/', methods=['GET'])
def hi():
return "Hello world"
app.run(host='0.0.0.0', port=7860)
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