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from fastapi import FastAPI, UploadFile, File
import json
from PIL import Image
from io import BytesIO
import numpy as np
from model import build_model
app = FastAPI()
#Load model
image_shape = (224,224,3)
num_classes = 6
model = build_model(image_shape, num_classes)
model.load_weights('./new_model_weights.h5')
classes = {
0: 'Ahegao',
1: 'Angry',
2: 'Happy',
3: 'Neutral',
4: 'Sad',
5: 'Surprise'
}
@app.get("/")
def first_api():
return {
"response": "Face Expression Prediction"
}
@app.post("/prediction")
async def prediction(image: UploadFile = File(...)):
image = await image.read()
# process image
image = Image.open(BytesIO(image))
image = image.resize((image_shape[0], image_shape[1]))
image = np.expand_dims(image, axis=0)
prediction = model.predict(image)[0]
label = np.argmax(prediction, axis=-1).tolist()
return {
"label": label,
"class": classes[label]
} |